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A delay-aware reliable event reporting framework for wireless sensor–actuator networks
Abstract
Wireless sensor–actuator networks (WSANs) greatly enhance the existing wireless sensor network architecture by introducing powerful and possibly even mobile actuators. The actuators work with the sensor nodes, but can perform much richer application-specific actions. To act responsively and accurately, an efficient and reliable reporting scheme is crucial for the sensors to inform the actuators about the environmental events. Unfortunately, the low-power multi-hop communications in a WSAN are inherently unreliable; frequent sensor failures and excessive delays due to congestion or in-network data aggregation further aggravate the problem.In this paper, we propose a general reliability-centric framework for event reporting in WSANs. We argue that the reliability in such a real-time system depends not only on the accuracy, but also the importance and freshness of the reported data. Our design follows this argument and seamlessly integrates three key modules that process the event data, namely, an efficient and fault-tolerant event data aggregation algorithm, a delay-aware data transmission protocol, and an adaptive actuator allocation algorithm for unevenly distributed events. Our transmission protocol adopts smart priority scheduling that differentiates event data of non-uniform importance. We further extend the protocol to handle node and link failures using an adaptive replication algorithm. We evaluate our framework through extensive simulations; the results demonstrate that it achieves desirable reliability with minimized delay.
... Although the distributed state estimation and the data fusion have been well studied in WSNs, e.g., [19], [20], these methods are hard to be directly applied to WSANs, since the locations and the outputs of actuators influence the state estimation. Previous works target at WSANs usually consider centralized schemes, e.g., [8], [16], [18], while distributed schemes are rare, e.g., [17], [21], and they focus on different contexts (see Section II for more details). ...
... Moreover, the above methods are not suitable for WSANs since the closed-loop control provided by the actuators is not taken into account. In WSANs, although distributed data routing and fusion methods can be found in [17], [21], the state estimation is not considered in these works. ...
... Hence, during the inner-layer iteration, the actuator A j needs to exchange its temporary result u j (l) with the other actuators in the set A i to update u j (l + 1). On the other hand, (17) shows that ∂R(λ(m)) ∂λj (m) is a function respective to variables u i (m) and λ j (m). Note that u i (m) is already known by the actuator A j through the inner-layer iteration. ...
Wireless Sensor and Actuator Networks (WSANs) are emerging as a new generation of Wireless Sensor Networks (WSNs). Due to the coupling between the sensing areas of the sensors and the action areas of the actuators, the efficient coordination among the nodes is a great challenge. In this paper, we address the problem of distributed node coordination in WSANs aiming at meeting the user’s requirements on the states of the Points of Interest (POIs) in a real-time and energy-efficient manner. The node coordination problem is formulated as a non-linear program. To solve it efficiently, the problem is divided into two correlated subproblems: the Sensor-Actuator (S-A) coordination and the Actuator-Actuator (A-A) coordination. In the S-A coordination, a distributed federated Kalman filter-based estimation approach is applied for the actuators to collaborate with their ambient sensors to estimate the states of the POIs. In the A-A coordination, a distributed Lagrange-based control method is designed for the actuators to optimally adjust their outputs, based on the estimated results from the S-A coordination. The convergence of the proposed method is proved rigorously. As the proposed node coordination scheme is distributed, we find the optimal solution while avoiding high computational complexity. The simulation results also show that the proposed distributed approach is an efficient and practically applicable method with reasonable complexity.
... To the best of our knowledge, the WSANs-based Edge computing systems on data storage and information discovery are emerging research areas, and not much research has to date been carried out [42][43][44][45][46][47][48][49][50][51][52][53][54]. Those existing schemes mainly follow two basic models: the query-driven model and the event-driven model. ...
... Thus, actuators can acquire the event data without launching queries, and the real-time information discovery can be achieved. In this model, the challenging problems include how to ensure the real-time, reliable, secure and lightweight routing algorithms from the sensor nodes to the actuators [45][46][47][48][49], how to improve the coordination among the sensor nodes and the actuators [50], as well as how to execute tasks efficiently for the actuators [51][52][53]. ...
... In 2010, to improve the reliability and the real-time performances of the event-data transmission from the sensor nodes to the actuators, Dr. Edith Ngai proposed a delay-aware reliable event-reporting framework for WSANs [45]. The overall reliability index R used in [45] can be formalized as ...
In the post-Cloud era, the proliferation of Internet of Things (IoT) has pushed the horizon of Edge computing, which is a new computing paradigm with data are processed at the edge of the network. As the important systems of Edge computing, wireless sensor and actuator networks (WSANs) play an important role in collecting and processing the sensing data from the surrounding environment as well as taking actions on the events happening in the environment. In WSANs, in-network data storage and information discovery schemes with high energy efficiency, high load balance and low latency are needed because of the limited resources of the sensor nodes and the real-time requirement of some specific applications, such as putting out a big fire in a forest. In this article, the existing schemes of WSANs on data storage and information discovery are surveyed with detailed analysis on their advancements and shortcomings, and possible solutions are proposed on how to achieve high efficiency, good load balance, and perfect real-time performances at the same time, hoping that it can provide a good reference for the future research of the WSANs-based Edge computing systems.
... For fire monitoring and detection application of WSNs, several important design goals and features must be considered such as energy efficiency, accurate localization, early detection, forecast capability and adaptivity to harsh environment [9]. There is a considerable amount of research works from literature related to forest fires using WSNs [20][21][22][23][24][25][26]. The authors of [27] implemented a real-world forest fire monitoring and detection system in the San Francisco area. ...
... Meanwhile, we apply a low and fair energy consumption strategy by using the proposed intra-cluster and inter-cluster protocols rather than the approach in [20], which did not consider the energy constraints of sensor node. The authors of [21] proposed a general reliability-centric framework in which event reporting in WSNs also can be used in forest fire monitoring and detection. There is also a data aggregation algorithm for filtering important data and delay-aware data transmission for rapidly delivery. ...
Forest fires are a fatal threat to environmental degradation. Wireless sensor networks (WSNs) are regarded as a promising candidate for forest fire monitoring and detection since they enable real-time monitoring and early detection of fire threats in an efficient way. However, compared to conventional surveillance systems, WSNs operate under a set of unique resource constraints, including limitations with respect to transmission range, energy supply and computational capability. Considering that long transmission distance is inevitable in harsh geographical features such as woodland and shrubland, energy-efficient designs of WSNs are crucial for effective forest fire monitoring and detection systems. In this paper, we propose a novel framework that harnesses the benefits of WSNs for forest fire monitoring and detection. The framework employs random deployment, clustered hierarchy network architecture and environmentally aware protocols. The goal is to accurately detect a fire threat as early as possible while maintaining a reasonable energy consumption level. ns-2-based simulation validates that the proposed framework outperforms the conventional schemes in terms of detection delay and energy consumption.
... In [23], a sensor-actor communication scheme with reliable event-reporting is proposed. The event reports from SNs are sent to actors within a certain time bound and with different priorities according to the importance of each event. ...
... Should there be a concern about network congestion or reduced reliability, our shortest path based communication between SNs and actors could be easily replaced by alternative anycast protocols which consider these issues (e.g. those in [18,23]). ...
The real time response of actors to events occurring in a network area is of critical importance in Wireless Sensor and Actor Networks (WSANs). This in turn requires fast notification of actors from Sensor Nodes (SNs) about events as well as effective coordination of actors for prompt event handling. In this paper, we introduce an on-line distributed protocol for event handling in a WSAN. Existing techniques usually select actors nearby the current event for handling it. However, this greedy approach may eventually lead to a slow response to events because it does not consider the spatial distribution that future events might have. In contrast, in order to cater for future events, the proposed solution probabilistically selects actors for event handling, allowing distant actors to be selected as well. This randomized approach guarantees fast average responsiveness to events, a balanced energy consumption among actors and low energy consumption for SNs. These merits have also been confirmed in the experimental results where the performance of the proposed approach has also been evaluated. In addition, the event-handling scheme presented in this work features efficient distributed algorithms for sensor to actor and actor to actor coordination which are of independent interest.
... But today, wireless sensor network is one of the active subjects to research for computer science, communications, industry, and many non-military purposes. Some of its applications include monitoring and controlling industrial processes, health monitoring of devices, monitoring the environment of firms and houses, smart houses, traffic control and etc. [5,6,8,9,13]. In recent years, wireless networks due to their potential in a wide range of practical applications have attracted interests of researchers. ...
... To act responsively and accurately, an efficient and reliable reporting scheme is crucial for the sensors to inform the actuators about the environmental events. Wireless sensor networks (WSNs), constructed by a group of sensors, have been suggested for numerous novel applications, such as monitoring for harsh environments and protecting national borders [8]. Researches in various fields of wireless sensor networks are done in several ways and each one focus on a certain case. ...
The emergence of embedded systems, mobile, and the presence of sensors in all areas of human life without the presence of humans, makes it easy to do things, and to reduce the computational complexity. Wireless sensor networks are one of the types of distributed systems in recent years has been of interest to many researchers and have been used in many places, such as the military areas, banks, airports and other places, for use in protection systems. Wireless sensor networks consisting of tens, hundreds or even thousands of self-directed sensors that are wirelessly at a distance from each other and embedded in the environment, so that are associated with each other and perform the task of finding events and gather information from the environment and transmits the information to a monitoring center. Wireless sensor networks with the introduction of powerful or even mobile Actuators have improved their existing wireless sensor networks. An actuator interacts with the environment according to information received from the sensors and processing information. In order to have reliable operation for the activation, it looks critical to design a reliable, secure, and fault tolerance report for sensors to alert activation of peripheral events. In this paper, we use machine learning techniques such as clustering and Bayesian rules to represent a reliable, fault tolerance and secure framework to report events in the wireless sensor-actuator networks, which are enable to optimal collect data received from the environment and report it to the actuators.
... Nowadays, wireless sensor networks are one of the most debated topics of research in computer science, communications, industry, and many non-military fields. Some of these huge applications include monitoring and controlling industrial processes, monitoring health condition of systems, environment monitoring of firms, centers, and houses, health care, smart homes, traffic control, and so on2346,7,9]. Wireless sensor networks have significantly advanced architectural wireless sensor networks by introducing powerful and even moving activators. ...
... Activators are much more powerful than sensors in terms of computing capacity. A moving activator like a robot can change its position each moment to have the desired performance [7]. An activator processes information and data received from the sensors and according to the data interact with the environment. ...
Wireless sensor networks (WSNs) are consisted of tens, hundreds or even thousands of self-directed sensors which are embedded in an environment wirelessly at a distance from each other to communicate with each other, and their task is discovering and aggregation of environmental information and transmitting it to a monitoring center. Continuous movement of sensor nodes and their limited battery power causes routing problems for these types of networks. Thus, providing a reliable and secure protocol in wireless sensor networks seems crucial. Our main emphasis in this paper is on utilizing artificial intelligence techniques such as clustering and Particle Swarm Optimization (PSO) algorithm for finding a safe and efficient routing in wireless sensor networks.
... Identifying the actors that ought to handle an event is a key function of a WSAN. Such a designation can be simply based on the actor's proximity to the event [5][6] [7][8], by planning [9], or through inter-actor coordination [10] [11]. Proximitybased actor tasking suits discrete events and can be the byproduct of sensor clustering. ...
... Planning is a variant of proximity-based actor selection that factors in the probability for an event to take place in a specific region. For example, Nagi et al., [9]alters the spatial distribution of actors based on the observed frequency of event occurrences. On the other hand, Zeng et al. [10]relies on actors to decide among themselves on which node to respond based on the certainty that an application specific deadline is to be met. ...
Wireless sensors and actors networks (WSANs) have the capacity for not only monitoring some phenomena through sensor nodes but also performing appropriate actions. Most of the contemporary WSAN management solutions focus on defining communication path among sensors and actors and on tasking appropriate actors to handle the detected events. In this paper we classify events based on how they evolve over time into continuous and discrete and categorize the WSAN management strategies accordingly. Unlike discrete events, a continuous event spreads quickly and becomes more serious as time passes. Such a characteristic introduces more challenges and motivates a non-conventional management strategies. This paper presents an approach for Sensor-Actuator Coordination for Handling Spreading events (SACHS). SACHS opts to enable the network to respond quickly in order to avoid the event from growing in scope, e.g., prevent a fire from spreading, while reducing the energy overhead due to the coordination messages and due to actor's relocation to the event region. SACHS limits sensor-actor and actor-actor interactions and exploits local sensor-sensor communication to determine the scope of the event, define spots for actors to position at, and schedule the actors' response. The simulation results confirm the performance advantage of SACHS compared to competing schemes.
... In [6] a general reliability-centric framework for event reporting in WSANs is proposed, which contains an fault-tolerant event data aggregation algorithm and a delay-aware data transmission protocol. In [7], the authors study the model-based predictive networked control systems that compensate random delays and data loss of the communication, and use a predictive control scheme to avoid performance loss. ...
... Eq.(5) and Eq. (6) show that the sensor nodes in set S A i will transmit the sensing data to A i , while the actuator nodes in set S S j will influence the plant state monitored by S j . In WSANs, the sensor and actuator nodes are usually linked with wireless medium, since the actuator nodes are connected with each other directly and much more powerful than the ordinary sensor nodes, communication delay between S-A become a general problem of such network control system [14]. ...
In wireless sensor and actuator networks (WSANs), the sensor nodes are involved in gathering information about the physical phenomenon, while the actuator nodes take decisions and then perform appropriate actions upon the environment. The collaborative operation of sensor and actuator nodes brings significant advantages over WSNs, including improved accuracy and timely actions upon the sensed phenomena. However, unreliable wireless communication and finding a proper control strategy cause challenges in designing such network control system. In order to accomplish effective sensing and acting tasks, efficient coordination mechanisms among different nodes are required. In this paper, the coordination and communication problems in WSANs are studied. First, we formulate the mathematical models for the WSANs system. Then, a predictor-controller algorithm based on distributed estimation is adopted to mitigate the effects of network-induced delay. Finally, we apply a collaborative processing mechanism to meet the desired system requirements and improve the overall control performance. This approach will group the sensor and actuator nodes to work in parallel so as to reduce the computation complexity and enhance the system reacting time. Simulation results demonstrate the effectiveness of our proposed method.
... The S-A coordination manages sensors to sense the physical world and transmit sensed information to appropriate actuators (Wu, 2011). Most of existing works in this area involves data aggregation and data transmission (Gungor et al., 2008;Ngai et al., 2010;Nakayama et al., 2011). The design of S-A coordination is challenging due to: (1) the amount, the resource and the traffic load are asymmetrical between the sensors and the actuators, (2) the sensor information is usually corrupted due to factors such as noise and sensor failure, and (3) the system must satisfy the real-time requirement. ...
... However, sensor faults are not considered. Ngai et al. (2010) propose a latencyoriented fault tolerant transport protocol for WSANs. This method combine fault tolerant with data aggregation, but doesn't take sensor measurement noise into account. ...
Wireless sensor and actuator networks (WSANs) facilitate close interactions between human and the environment. Efficient coordination among the sensors and actuators plays a vital role in carrying out sensing and acting in WSANs. In this paper, we develop a collaborative estimation and actuation mechanism, which consists of a sensor-actuator coordination phase and an actuator-actuator coordination phase. The first phase is based on distributed Kalman filter in federated configuration, which is able to provide reliable and precise sensing data. On this basis, the second phase allocates proper tasks based on system requirements and coordinates actuators to accomplish the tasks. Particularly, the actuator-actuator coordination is formulated as an optimization problem and an effective method is proposed to search the solution based on sequential unconstrained minimization technique. Simulation results demonstrate the effectiveness of our proposed mechanism.
... The set of clustered sensors S A i is defined as the group of sensors clustered by a special actuator A i. The set of responsible actuators A R i is defined as the group of actuators which are responsible for processing certain events. They are usually coordinated to make correct decisions [21,22,39]. Throughout this paper, we assume that the set of responsible actuators of S A i consists of all actuators that are within a cutoff distance d from A i , i.e. ...
... The field covered by the WSAN is divided into a number of clusters for monitoring [38], as illustrated in Figure 1. We assume that S and A are all aware of their locations (such as L S i and L A i ) through various localization techniques [39]. Each sensor of S A i is responsible for probing its surroundings and sending its noisy measurement to the known actuator A i. ...
Earlier works have investigated the problem of distributed estimation in wireless sensor and actuator networks (WSANs) under packet loss. However, observation correlation was not utilized which can mitigate performance degradation due to packet loss. In this paper, the problem of distributed estimation in WSANs under packet loss and correlated observations is studied. In particular, an energy-efficient scheduling scheme for sensor-actuator and actuator-actuator coordinations is proposed based on the ordinary Kriging method. This method utilizes observation correlation by semivariogram modeling. Considering the tradeoff between estimation performance and energy efficiency of the scheduling scheme, an optimization problem is formulated. As it is difficult to derive the analytical expression of the solution to the optimization problem, a global search algorithm which integrates a genetic algorithm with a simulated annealing algorithm is designed to approximate the solution. The results show that the proposed scheduling scheme outperforms the inverse distance weighting method in terms of estimation performance. Moreover, the tradeoff between estimation performance and energy consumption exists.
... In a network it is very important that a reliable event reporting is carried from sensors to actuators. A framework is proposed that works on delay and event reporting which assimilates huge data based on priority based data accumulation that outlines the allocation of actuator [13][14]. ...
... The data collected by certain sensors have high priority and should be delivered with minimum end to end delay. Both the above mechanisms were based on delay estimation algorithm that has assessment of delay and data prioritizing stages that are implemented by application layer in addition to medium access control (MAC) layer constraints in response to delay requirements of smart grid application and network conditions [13][14]. Prioritizing the data that is adapted from multiple frames of different layers can be done by implementing the adaptive schemes that is defined by DRX. The application layer then evaluates the captured data and takes a decision, based on the priority of the monitored parameter value that is beyond an acceptable threshold (i.e., higher or lower than normal limit values), based on this threshold the algorithm estimates the delay estimation and MAC layer checks if it is above the defined threshold or not. ...
With the increasing concern for reliability and quality of service, power grid in many countries is
undergoing revolution towards a more distribute and flexible “Smart Grid”. In the development of envisioned
smart grid, situational data awareness takes a fundamental role for a number of crucial advanced operations in
the areas of sensing, communication, monitoring and decision making. It is very important that applications of
smart grid should always be monitored. The wireless sensors in combination with actuators in the smart grid
network would significantly advance the existing networks and could perform more comfortable application
preferential control actions. The smart grid needs an efficient medium access approach based on the data
prioritization and delay responsiveness. The wireless sensor communication within smart grid system is based
on data rate, delay, latency, congestion and so on. The data is collected in a reliable and timely manner from the entire system and based on collected data the entire system is monitored for more advanced controlling schemes.This article surveys a sample of algorithms that can be adaptable for smart grid applications. Copyright © 2015 IFSA Publishing, S. L.
... In [12], SNs are organized in clusters and a distributed protocol based on the Galey Shapley (GS) algorithm from stable matching theory is proposed for matching actors to cluster heads with minimum message overhead and minimum actor relocation. In [13], a sensor-actor communication scheme with reliable event-reporting is proposed. The event reports from SNs are sent to actors within a certain time bound and with different priorities according to the importance of each event. ...
... between SNs and actors could be easily replaced with other anycast protocols (e.g. those in [7], [13]) which consider these issues. ...
A critical issue dealt with in Wireless Sensor and Actor Networks (WSANs) is the real time response of actors to events occurring in the network area. The fast notification of actors from Sensor Nodes (SNs) about the events as well as the effective coordination of actors for prompt event handling is most important in these networks. In this paper, we introduce a distributed protocol for effective event handling in a WSAN. Existing approaches mainly favoring actors near the current event for handling it, may lead to highly ineffective solutions for certain worst-case scenarios. Through a randomized approach, our solution also selects distant actors for handling events, and guarantees fast average responsiveness to events and a balanced energy distribution among actors. In addition, it features efficient distributed algorithms for sensor to actor and actor to actor coordination which are of independent interest.
... In [6] a general reliability-centric framework for event reporting in WSANs is proposed, which contains an fault-tolerant event data aggregation algorithm and a delay-aware data transmission protocol. In [7], the authors study the model-based predictive networked control systems that compensate random delays and data loss of the communication, and use a predictive control scheme to avoid performance loss. ...
... Eq.(5) and Eq. (6) show that the sensor nodes in set S A i will transmit the sensing data to A i , while the actuator nodes in set S S j will influence the plant state monitored by S j . In WSANs, the sensor and actuator nodes are usually linked with wireless medium, since the actuator nodes are connected with each other directly and much more powerful than the ordinary sensor nodes, communication delay between S-A become a general problem of such network control system [14]. ...
In wireless sensor and actuator networks (WSANs), the sensor nodes are involved in gathering information about the physical phenomenon, while the actuator nodes take decisions and then perform appropriate actions upon the environment. The collabora-tive operation of sensor and actuator nodes brings significant advantages over WSNs, including improved accuracy and timely actions upon the sensed phenomena. How-ever, unreliable wireless communication and finding a proper control strategy cause challenges in designing such network control system. In order to accomplish effective sensing and acting tasks, efficient coordination mechanisms among different nodes are required. In this paper, the coordination and communication problems in WSANs are studied. First, we formulate the mathematical models for the WSANs system. Then, a predictor-controller algorithm based on distributed estimation is adopted to miti-gate the effects of network-induced delay. Finally, we apply a collaborative processing mechanism to meet the desired system requirements and improve the overall control performance. This approach will group the sensor and actuator nodes to work in parallel so as to reduce the computation complexity and enhance the system reacting time. Simulation results demonstrate the effectiveness of our proposed method.
... Here, A10)l = 0 implies that it is not forwarding any event data with importance lower than that considering by node i; if node i forwards the data to this node, it will not affect the transmission time for the existing packets in that node; Similarly, Ahigh = ° means that it is not transmitting any data with higher importance, so the data from node i, if forwarded, can be served with the highest priority. For each candidate above, node i calculates the maximum data rate Ai that it can forward while satisfying the latency bound [24] ...
... The process repeats recursively for Al and A2, until each subfield contains only one actuator. Detailed algorithm can be found in [24]. Figures 3 demonstrates our actuator allocation results with 6 actuators, respectively. ...
Wireless sensor-actuator networks, or WSANs, greatly enhance the existing wireless sensor network architecture by introducing powerful and even mobile actuators. The actuators work with the sensor nodes, but can perform much richer application-specific actions. To act responsively and accurately, an efficient and reliable reporting scheme is crucial for the sensors to inform the actuators about the environmental events. Unfortunately, the low-power multi-hop communications in a WSAN are inherently unreliable; the frequent sensor failures and the excessive delays due to congestion or in-network data aggregation further aggravate the problem. In this paper, we propose a general reliability-centric framework for event reporting in WSANs. We argue that the reliability in such a real-time system depends not only on the accuracy, but also the importance and freshness of the reported data. Our design follows this argument and seamlessly integrates three key modules that process the event data, namely, an efficient and fault-tolerant event data aggregation algorithm, a delay-aware data transmission protocol, and an adaptive actuator allocation algorithm for unevenly distributed events. Our transmission protocol also adopts smart priority scheduling that differentiates the event data of non-uniform importance. We evaluate our framework through extensive simulations, and the results demonstrate that it achieves desirable reliability with minimized delay
... Other approach of using sensor network is the use of sensors which remain unaffected by the line of sight. No wonder the range is compromised but at the same time the cost is reduced and accuracy of the system increases [30], [31], [32], [33], [34], [35]. The drawback of such systems is that such systems are still in development phase and are constrained by the limitations offered WSN, power and network connection [30], [36]. ...
This paper proposes a generic Sensor Network (SN) based forest fire detection and management system, which is scalable and readily deployable for all environments and terrains. SN are being deployed in critical and hazardous areas, for monitoring as well as for collection of useful environmental data for analysis. In these particular contexts, active fire detection and management in forest prove to be challenging, especially in areas which are remote, unapproachable or at the epicenter of such incident. The proposed system caters to the above said problem by allowing a visual representation of status of the sensor nodes (in real-time) through the use of web map system, connected to the strategically deployed nodes based on geography. This deployment is enhanced with the usage of a low power, high range and low data rate wireless protocol, for which the lifetime of the nodes can be further increased through an appropriate scheduling. Moreover, a system with environmental sensors and 3 level hierarchical network covering a total of 4 sq. km has been designed, to investigate the feasibility of the underlying system with the experimental scenarios of fire incident at certain nodes. Software modules providing detection functionalities have been implemented as prototype in the proposed system. The real time system has proved to provide a better visualization and real time tracking of the fire incidents, which in turn facilitates the fire management system as a whole.
... Further, Hefeeda et al. [13] suggested that for fire monitoring and detection several factors have to be considered such as energy efficiency, accurate localization, early detection, forecast capability and adaptability to harsh environment. The architecture of WSNs had to be re-evaluated for such an application [15]. A real-world application for forest-fire monitoring and detection system is implemented in San Francisco area [16]. ...
Wireless sensor networks (WSNs) have been
imperative means for the collection of information in various
fields. Integration of WSN with the latest technology like
unmanned aerial vehicles (UAVs) can increase the overall
performance of the WSN by increasing the sensor coverage
or reducing the latency. However, for full coverage of the
sensors to avoid data loss, to reduce the time required to
deliver the data to sink and to minimize the calculation of the
total path length, overall trajectory optimization is required.
In order to solve these challenges, in this work, trajectory
of the UAV is considered as a hamiltonian path that covers
all the cluster heads in the WSN. The proposed scheme is
able to calculate path in polynomial time which is otherwise
considered to be NP-Hard. Moreover, data of sensor nodes is
sent directly to the UAV thereby eliminating the need of any
routing protocol. Simulation results show that the coverage
of nodes is improved along with minimized data loss in
comparison with single-hop and multi-hop routing protocols
of WSN
... In the smart grid environment, wireless sensor nodes can collect different types of data such as current, voltage, and frequency etc. while the actor nodes perform different tasks including the opening/closing of circuit breakers and the turning on/off of the loads. [19]. ...
The conventional electric grid converting in to the new emerging smart grid by utilizing information and communication technologies. The smart grid allows both the utilities and consumers to monitor and manage energy consumption effectively with the help of wireless sensor and actor networks (WSANs). WSANs have large number of low-power, low-cost, and multi-functional wireless sensor and actor nodes. The wireless sensor nodes collect the data from the physical condition of environment, while actor nodes perform different tasks according to the application requirements. For the monitoring and controlling of smart grid assets, WSANs can be considered as potential tools having the capability of low cost, high latency, and flexibility. In smart grid environment, WSANs have the problem of delay in channel access due to packet collisions. In this research work, we compare the performance results of various medium access control (MAC) protocols in order to analyze which one among them is the best with respect to better throughput and minimum delay for WSANs in the smart grid environment.
... In [11], Ngai et al. have proposed a centric approach, which combines an event data aggregation algorithm, a delay-aware priority based transmission protocol, and an adaptive actuator allocation algorithm. The routing process adopts smart priority scheduling that differentiates event data of non-uniform importance. ...
Wireless sensor and actuator networks are composed of sensor and actuator nodes interconnected via wireless links. The actuators are responsible for taking prompt decisions and react accordingly to the data gathered by sensor nodes. In order to ensure efficient actions in such networks, we propose a new routing protocol that provides QoS in terms of delay and energy consumption. The network is organized in clusters supervised by CHs (Cluster-Heads), elected according to important metrics, namely the energy capability, the riches of connectivity, which is used to select the CH with high node density, and the accessibility degree regarding all the actuators. The latter metric is the distance in number of hops of sensor nodes relative to the actuator nodes. This metric enhances more the network reliability by reducing the communication delay when alerting the actuator nodes, and hence, reducing the energy consumption. To reach efficiently the actuator nodes, we design a delay and energy sensitive routing protocol based on-demand routing approach. Our protocol incurs less delay and is energy efficient. We perform an evaluation of our approach through simulations. The obtained results show out performance of our approach while providing effective gain in terms of communication delay and energy consumption.
... Chen et al. (2010) develop a distributed estimation and collaborative control scheme for industrial control systems with WSANs, which can achieve robust control against inaccurate system parameters. Ngai et al. (2010) divide the network area into cells, and a selected actuator periodically collects the event frequency of all cells in the network. Though a relocation algorithm, the selected actuator node can balance load and move more actuators to areas with higher event frequencies. ...
Wireless sensor and actuator networks (WSANs) are emerging as a new generation of sensor networks. To accomplish effective sensing and acting tasks, efficient coordinate mechanisms among the nodes are desirable. As an attempt in this direction, this paper develops a collaborative estimation and control mechanism, which addresses the nodes coordination in a distributed manner. First, we discuss the system model and system partition that are used to construct the distributed architecture. Then, a collaborative estimation and control scheme is proposed to coordinate sensor and actuator nodes. This scheme includes two components, namely recursive least squares based federated Kalman filter (RLS-FKF) and PID neural network (PIDNN). It schedules the corresponding nodes based on the characteristics of current events, deals with data fusion and system estimation problems through RLS-FKF, and utilises PIDNN controller to improve system transient and steady-state responses. Simulations demonstrate the effectiveness of proposed methods.
... This constraint is simply taken as an input parameter to our proposed framework, and should be propagated to the sensor network through the sink gateway, so that it can be considered and respected throughout the operation of the algorithm. Though the determination of the actual value of this parameter is not the main focus of the paper, it is expected that the delay QoS metric relates more to monitoring applications, such as indoor living monitoring [20,21] and event detection and reporting [22], as well as other delay sensitive applications such as emergency response [23], plant automation and control [24], healthcare [25], etc. ...
Among the key aspects of the Internet of Things (IoT) is the integration of heterogeneous sensors in a distributed system that performs actions on the physical world based on environmental information gathered by sensors and application-related constraints and requirements. Numerous applications of Wireless Sensor Networks (WSNs) have appeared in various fields, from environmental monitoring, to tactical fields, and healthcare at home, promising to change our quality of life and facilitating the vision of sensor network enabled smart cities. Given the enormous requirements that emerge in such a setting-both in terms of data and energy-data aggregation appears as a key element in reducing the amount of traffic in wireless sensor networks and achieving energy conservation. Probabilistic frameworks have been introduced as operational efficient and performance effective solutions for data aggregation in distributed sensor networks. In this work, we introduce an overall optimization approach that improves and complements such frameworks towards identifying the optimal probability for a node to aggregate packets as well as the optimal aggregation period that a node should wait for performing aggregation, so as to minimize the overall energy consumption, while satisfying certain imposed delay constraints. Primal dual decomposition is employed to solve the corresponding optimization problem while simulation results demonstrate the operational efficiency of the proposed approach under different traffic and topology scenarios.
... The real-time routing framework by Shah et al. [20] addresses the coordination of sensor and actor nodes through the delay bound for distributed routing. Another coordination algorithm among actors is introduced with the real-time communication framework by Ngai et al. [21], where an event reporting algorithm for sensor-actor communication is also given to minimize the transmission delay. Ad Hoc On Demand Delay Constrained Distance Vector Routing (AOD 2 V) by Sama and Akkaya [22] also uses delay as the main constraint. ...
Wireless sensor and actor networks (WSANs) have been increasingly popular for environmental monitoring applications in the last decade. While the deployment of sensor nodes enables a fine granularity of data collection, resource-rich actor nodes provide further evaluation of the information and reaction. Quality of service (QoS) and routing solutions for WSANs are challenging compared to traditional networks because of the limited node resources. WSANs also have different QoS requirements than wireless sensor networks (WSNs) since actors and sensor nodes have distinct resource constraints. In this paper, we present, LRP-QS, a lightweight routing protocol with dynamic interests and QoS support for WSANs. LRP-QS provides QoS by differentiating the rates among different types of interests with dynamic packet tagging at sensor nodes and per flow management at actor nodes. The interests, which define the types of events to observe, are distributed in the network. The weights of the interests are determined dynamically by using a nonsensitive ranking algorithm depending on the variation in the observed values of data collected in response to interests. Our simulation studies show that the proposed protocol provides a higher packet delivery ratio and a lower memory consumption than the existing state of the art protocols.
... Ngai et al. [25] provide a general reliability-centric framework for event reporting in wireless sensor networks which can also be used in forest fire detection systems. They consider the accuracy, importance, and freshness of the reported data in environmental event detection systems. ...
ontext. Apart from causing tragic loss of lives and valuable natural and individual properties including thousands of hectares of forest and hundreds of houses, forest fires are a great menace to ecologically healthy grown forests and protection of the environment. Every year, thousands of forest fires across the globe cause disasters beyond measure and description. This issue has been the research interest for many years; there are a huge amount of very well studied solutions available out there for testing or even ready for use to resolve this problem. Aim. This work will summarise all the technologies that have been used for forest fire detection with exhaustive surveys of their techniques/methods used in this application. Methods. A lot of methods and systems are available in the market and for research. The paper reviews all the methods and discusses examples of research experiment results and some market product methods for better understanding. Result. Each technique has its own advantages and disadvantages. A full discussions provided after each type. Conclusion. A full table is provided at the end to summarise a comparison between the four methods.
... Each packet should be reported to the actuator within the latency bound of 2 sec. For comparison, we also show the results of the priority-based event reporting with event importance approach (PREI) [98], where priority-based forwarding is employed, but the link failures are not considered. We repeat the experiments for 10 times by changing the random seed and show the average results. ...
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... A general reliability-centric framework for event reporting in wireless sensor networks which can also be used in forest fire detection systems is provided in [16]. They consider the accuracy, importance and freshness of the reported data in environmental event detection systems. ...
Forest fires lead to high amount of environmental and economic loss all over the world. Prevention and early detection efforts aim to eliminate or minimize the damage that will be caused by a fire incident. Current surveillance systems for forest fires do not provide dense real-time monitoring and hence they lack prevention or early detection of a fire threat. Wireless sensor networks (WSNs), on the other hand, can collect real-time information such as temperature and humidity from almost all points of a forest and can provide fresh and accurate data for the fire-fighting management center quickly. In this work, we aim to evaluate the reporting performance of a WSN under realistic workload. Since fires are destructive and burning a deployed WSN is not feasible, simulation is the appropriate way to assess the reporting capability of a WSN during a forest fire. We integrate WSN simulator with a realistic fire propagation simulator which is modified to provide time based temperature field information while the fire propagates through the deployment area. Temperature information is used for the generation of realistic workloads and the determination of sensor destruction times that affects the routing decisions in WSN simulations. We present the effects of WSN related factors; such as reporting rate, number of the sinks, and the sink locations together with the effects of environmental factors such as the wind speed and the number of ignition points in terms of temperature reporting performance and freshness of temperature map.
... A reliable framework is proposed in [4] for general reportage over the WSNs. The experiment shows that this general frame work can be used for fire detection. ...
Environment degradation around the world has motivated many researchers to deal with an important yet endangering aspect of rural and forest fires. Most of the current developed technologies are based on detection of the fire rather than verifying it. Detecting the fire can be useful in many cases but it is still not efficiently implemented in real time systems.
To reduce healthcare costs and improve human well-being, a promising technology known as wireless body area networks (WBANs) has recently emerged. It is comprised of various on-body as well as implanted sensors which seamlessly monitor the physiological characteristics of the human body. The information is heterogeneous in nature, requires different QoS factors. The information may be classified as delay-sensitive, reliability-sensitive, critical, and routine. On-time delivery and minimum losses are the main QoS-factors required to transmit the captured information. Various researchers have work to provide the required QoS, and some have also considered the other constraints due to the characteristics and texture of the human body. In this research work, we have discussed the communication architecture of WBANS along with the various challenges of WBANS. Furthermore, we have classified and discussed the existing QoS-aware data dissemination mechanisms. In the end, a comparative study of existing QoS-aware data dissemination mechanisms highlights the pros and cons of each mechanism.
An efficient protocol is modified in improving the metric: energy. Clustering is performed in mobile adhoc network (MANET) with two approaches: static clustering and dynamic clustering. The goal is to achieve improved energy life time resulting in dynamic clustering for the specified metric. The protocol in proactive, reactive and hybrid mode for static clustering possess more energy consumption. The proposed Enhanced Optimized Polymorphic Hybrid Multicast Routing Protocol (EOPHMR) save more energy than proactive, reactive and hybrid. The performance comparison of results on energy consumption and saved energy for proactive, reactive, hybrid and EOPHMR are presented.
In order to minimize energy dissipation and obtain higher fault sensor nodes recognition rate for deploying multi-target monitoring wireless sensor networks (WSN), a fault-tolerant strategy for virtual sensor networks (VSN) based on statistical hypothesis testing was proposed. On the cluster tree based VSN architecture, the fault occurring was judged by checking the matching degree between local data reading sequence and event statistical characteristics. The simulation results showed that before any node energy exhaustion, the multi-event monitoring produced less unicast messages and more multicast messages than single-event monitoring. In addition, the proposed strategy can maintain the fault identification rate and event region monitoring probability at the satisfactory level with increase of the sensor nodes fault probability.
The Appearance of new generation of computer systems, embedded systems, mobile, and also advances in mobile wireless networks, cause to extension of the computation fields. This process, lead to a scenario which is called: "pervasive computing". The aim of pervasive computing is the presence of computers in all fields of the human life, without the need to his presence, coordinating among all computer systems which related to each other and also the reduction of the calculations complexity. As the computations being pervasive, the nature of the requests be changed. The requests awareness of context is one of the most important features in pervasive computing, Because being aware of the context enable system to make automatic decisions. Context including any information about the person or object, such as location, identity, surrounding objects, feelings, environmental conditions and etc. For ease of planning requests, Context is collected, managed, and then finally a general conclusion had be done. pervasive computing include three major subsystems, Sensing subsystem, thinking subsystem, and the Acting subsystem. In this paper, by using the context, a reliable and context-aware framework for pervasive computing is presented which we called it, intelligent pervasive computing system. This system can evaluate received data from environment optimally by using machine learning technique.
Using Wireless Sensor Networks (WSNs) in delay
and reliability critical environments is highly desired due to their
unique advantages such as low cost, ease of deployment and
redundancy. However successful deployment of resource limited
WSNs in such applications, require strict Quality of Service (QoS)
provisioning techniques to meet the desired latency and reliability
targets of those applications. Implementation of QoS techniques
in WSNs is significantly challenging since WSNs have been
initially devised for low data rate, non-real-time applications.
Therefore, WSN designers and developers resort to different
cross-layer interaction and optimization techniques to provision
QoS in WSNs. In this paper, we present a survey on the state
of the art of cross-layer QoS approaches in wireless terrestrial
sensor networks to achieve delay and reliability bounds in critical
applications. Our paper provides a unique classification of crosslayer
QoS approaches in WSNs which allows surveying a large
amount of studies with utmost clarity. Furthermore, we highlight
the main challenges of implementing QoS protocols in WSNs and
present an overview of QoS-aware WSN applications.
This paper proposes a scheme for non-collocated moving actuating and sensing devices which is unitized for improving performance in distributed parameter systems. By Lyapunov stability theorem, each moving actuator/sensor agent velocity is obtained. To enhance state estimation of a spatially distributes process, two kinds of filters with consensus terms which penalize the disagreement of the estimates are considered. Both filters can result in the well-posedness of the collective dynamics of state errors and can converge to the plant state. Numerical simulations demonstrate that the effectiveness of such a moving actuator–sensor network in enhancing system performance and the consensus filters converge faster to the plant state when consensus terms are included.
In many wireless sensor network applications, it should be considered that how to trade off the inherent conflict between energy efficient communication and desired quality of service such as real-time and reliability of transportation. In this paper, a novel routing protocols named balance energy-efficient and real-time with reliable communication (BERR) for wireless sensor networks (WSNs) are proposed, which considers the joint performances of real-time, energy efficiency and reliability. In BERR, a node, which is preparing to transmit data packets to sink node, estimates the energy cost, hop count value to sink node and reliability using local information gained from neighbor nodes. BERR considers not only each sender' energy level but also that of its neighbor nodes, so that the better energy conditions a node has, the more probability it will be to be chosen as the next relay node. To enhance real-time delivery, it will choose the node with smaller hop count value to sink node as the possible relay candidate. To improve reliability, it adopts retransmission mechanism. Simulation results show that BERR has better performances in term of energy consumption, network lifetime, reliability and small transmitting delay.
Wireless Sensor–Actuator Networks (WSANs) have a myriad of applications, ranging from pacifying bulls to controlling light intensity in homes automatically. An important aspect of WSANs is coordination. Unlike conventional Wireless Sensor Networks (WSNs), sensor and actuator nodes must work hand-in-hand to collect and forward data, and act on any sensed data collaboratively, promptly and reliably. To this end, this paper reviews current state-of-the-art techniques that address this fundamental problem. More specifically, we review techniques in the following areas: (i) sensor–actuator coordination, (ii) routing protocols, (iii) transport protocols, and (iv) actuator-to-actuator coordination protocols. We provide an extensive qualitative comparison of their key features, advantages and disadvantages. Finally, we present unresolved problems and future research directions.
Forest fires are one of the main causes of environmental degradation nowadays. Current surveillance systems for forest fires lack in supporting real-time monitoring of every point of a region at all times and early detection of fire threats. Solutions using wireless sensor networks, on the other hand, can gather sensory data values, such as temperature and humidity, from all points of a field continuously, day and night, and, provide fresh and accurate data to the fire-fighting center quickly. However, sensor networks face serious obstacles like limited energy resources and high vulnerability to harsh environmental conditions, that have to be considered carefully. In this paper, we propose a comprehensive framework for the use of wireless sensor networks for forest fire detection and monitoring. Our framework includes proposals for the wireless sensor network architecture, sensor deployment scheme, and clustering and communication protocols. The aim of the framework is to detect a fire threat as early as possible and yet consider the energy consumption of the sensor nodes and the environmental conditions that may affect the required activity level of the network. We implemented a simulator to validate and evaluate our proposed framework. Through extensive simulation experiments, we show that our framework can provide fast reaction to forest fires while also consuming energy efficiently.
Wireless sensor and actuator networks (WSANs) are composed of a large number of heterogeneous sensors and actuators that enable to make reactions toward the physical information sensed. Reactive WSANs are widely used in a range of applications, and some of them are used in delay-sensitive surveillance systems. Compared to sensors, actuators have more capabilities, which can move with self-awareness and then help to fulfill reaction tasks according to application requirements. By taking advantage of mobile actuators, we present a novel framework of real-time data report and task execution (RTRE) for automated WSANs in this paper. The real-time sensor–actuator data collection is achieved through coordination among sensors and mobile actuators. The real-time task execution is achieved through multi-actuator coordination with priority-based multi-event task assignment. The schemes provide energy efficiency with timely reactions. Simulation results are shown to demonstrate the advantage of RTRE when compared with the other related work in terms of timeliness and energy efficiency.
Wireless sensor and actor networks (WSANs) are likely to become a pervasive technology in the near future due to the special characteristics of these devices and to the great number of applications where it can be applied. One of these applications is the critical infrastructure protection (CIP). In fact, WSANs have actually been identified as having the potential to become an integral part of the CIP. However, in order to achieve that goal, WSANs need to provide a set of features which includes a robust QoS. Unfortunately QoS support mechanisms in WSANs are still largely undeveloped. This paper studies the state-of-the-art of QoS management in WSANs by exploring existing proposals, challenges and open issues in the field. Emphasis is put on QoS in the context of CIP by focusing on the QoS requirements and the needs of CIP applications. Existing middleware and protocols are surveyed and the challenges and open issues in the field are presented.
Wireless sensor-actuator networks, or WSANs, greatly enhance the existing wireless sensor network architecture by introducing powerful and even mobile actuators. The actuators work with the sensor nodes, but can perform much richer application-specific actions. To act responsively and accurately, an efficient and reliable reporting scheme is crucial for the sensors to inform the actuators about the environmental events. Unfortunately, the low-power multi-hop communications in a WSAN are inherently unreliable; the frequent sensor failures and the excessive delays due to congestion or in-network data aggregation further aggravate the problem. In this paper, we propose a general reliability-centric framework for event reporting in WSANs. We argue that the reliability in such a real-time system depends not only on the accuracy, but also the importance and freshness of the reported data. Our design follows this argument and seamlessly integrates three key modules that process the event data, namely, an efficient and fault-tolerant event data aggregation algorithm, a delay-aware data transmission protocol, and an adaptive actuator allocation algorithm for unevenly distributed events. Our transmission protocol also adopts smart priority scheduling that differentiates the event data of non-uniform importance. We evaluate our framework through extensive simulations, and the results demonstrate that it achieves desirable reliability with minimized delay
Wireless sensor-actuator network (WSAN) comprises of a group of distributed sensors and actuators that communicate through wireless links. Sensors are small and static devices with limited power, computation, and communication capabilities responsible for observing the physical world. On the other hand, actuators are equipped with richer resources, able to move and perform appropriate actions. Sensors and actuators cooperate with each other: While sensors perform sensing, actuators make decisions and react to the environment with the right actions. WSAN can be applied in a wide range of applications, like environmental monitoring, battlefield surveillance, chemical attack detection, intrusion detection, space missions, etc. Since actuators perform actions in response to the sensed events, real-time communications and quick reaction are necessary. To provide effective applications by WSAN, two major problems remain: how to minimize the transmission delay from sensors to actuators, and how to improve the coordination among the actuators for fast reaction. To tackle these problems, we designed a real-time communication framework to support event detection, reporting, and actuator coordination. This paper explores the timely communication and coordination problems among the sensors and actuators. Moreover, we proposed two self-organized and distributed algorithms for event reporting and actuator coordination. Some preliminary results are presented to demonstrate the advantages of our approach
Wireless sensor networks fuse data from a multiplicity of sensors of different modalities and spatiotemporal scales to provide information for reconnaissance, surveillance, and situational awareness in many defense applications. For decisions to be based on information returned by sensor networks it is crucial that such information be of sustained high quality. While the Quality of Information (QoI) depends on many factors, perhaps the most crucial is the integrity of the sensor data sources themselves. Even ignoring malicious subversion, sensor data quality may be compromised by non-malicious causes such as noise, drifts, calibration, and faults. On-line detection and isolation of such misbehaviors is crucial not only for assuring QoI delivered to the end-user, but also for efficient operation and management by avoiding wasted energy and bandwidth in carrying poor quality data and enabling timely repair of sensors. We describe a two-tiered system for on-line detection of sensor faults. A local tier running at resource-constrained nodes uses an embedded model of the physical world together with a hypothesis-testing detector to identify potential faults in sensor measurements and notifies a global tier. In turn, the global tier uses these notifications on the one hand during fusion for more robust estimation of physical world events of interest to the user, and on the other hand for consistency checking among notifications from various sensors and generating feedback to update the embedded physical world model at the local nodes. Our system eliminates the undesirable attributes of purely centralized and purely distributed approaches that respectively suffer from high resource consumption from sending all data to a sink, and high false alarms due to lack of global knowledge. We demonstrate the performance of our system on diverse real-life sensor faults by using a modeling framework that permits injection of sensor faults to study their impact on the application QoI.
Wireless sensor-actuator networks, or WSANs, refer to a group of sensors and actuators which collect data from the environment and perform application-specific actions in response. To act responsively and accurately, an efficient and reliable data transport protocol is crucial for the sensors to inform the actuators about the environmental events. Unfortunately, the low-power multi-hop communications in WSANs are inherently unreliable; the frequent sensor and link failures as well as the excessive delays due to congestion further aggravate the problem. In this paper, we propose a latency-oriented fault tolerant data transport protocol in WSANs. We argue that reliable data transport in such a real-time system should resist to the transmission failures, and should also consider the importance and freshness of the reported data. We articulate this argument and provide a cross-layer two-step data transport protocol for on- time and fault tolerant data delivery from sensors to actuators. Our protocol adopts smart priority scheduling that differentiates the event data of non-uniform importance. It balances the workload of sensors by checking their queue utilization and copes with node and link failures by an adaptive replication algorithm. We evaluate our protocol through extensive simulations, and the results demonstrate that it achieves the desirable reliability for WSANs.
This paper describes the concept of sensor networks which has been made viable by the convergence of micro-electro-mechanical systems technology, wireless communications and digital electronics. First, the sensing tasks and the potential sensor networks applications are explored, and a review of factors influencing the design of sensor networks is provided. Then, the communication architecture for sensor networks is outlined, and the algorithms and protocols developed for each layer in the literature are explored. Open research issues for the realization of sensor networks are also discussed.
The presence of heterogeneous nodes (i.e., nodes with an enhanced energy capacity or communication capability) in a sensor network is known to increase network reliability and lifetime. However, questions of where how many, and what types of heterogeneous resources to deploy remain largely unexplored. We focus on energy and link heterogeneity in ad hoc sensor networks and consider resource-aware MAC and routing protocols to utilize those resources. Using analysis, simulation, and real testbed measurements, we evaluate the impact of number and placement of heterogeneous resources on performance in networks of different sizes and densities. While we prove that optimal deployment is very hard in general, we also show that only a modest number of reliable, long-range backhaul links and line-powered nodes are required to have a significant impact. Properly deployed, heterogeneity can triple the average delivery rate and provide a 5-fold increase in the lifetime (respectively) of a large batten-powered network of simple sensors.
Determining node positions is essential for many next-generation network functionalities. Previous localization algorithms lack cor- rectness guarantees or require network density higher than required for unique localizability. In this paper, we describe a class of al- gorithms for fine-grained localization called Sweeps. Sweeps cor- rectly finitely localizes all nodes in bilateration networks. Sweeps also handles angle measurements and noisy measurements. We demonstrate the practicality of our algorithm through extensive sim- ulations on a large number of networks, upon which it consistently localizes one-thousand-node networks of average degree less than five in less than two minutes on a consumer PC.
We consider a heterogeneous sensor network in which nodes are to be deployed over a unit area for the purpose of surveillance. An aircraft visits the area periodically and gathers data about the activity in the area from the sensor nodes. There are two types of nodes that are distributed over the area using two-dimensional homogeneous Poisson point processes; type 0 nodes with intensity (average number per unit area) ‚0 and battery energy E0; and type 1 nodes with intensity ‚1 and battery energy E1. Type 0 nodes do the sensing while type 1 nodes act as the cluster heads besides doing the sensing. Nodes use multi-hopping to communicate with their closest cluster heads. We determine the optimum node intensities (‚0, ‚1) and node energies (E0, E1) that guarantee a lifetime of at least T units, while ensuring connectivity and coverage of the surveillance area with a high probability. We minimize the overall cost of the network under these constraints. Lifetime is de£ned as the number of successful data gathering trips (or cycles) that are possible until connectivity and/or coverage are lost. Conditions for a sharp cutoff are also taken into account, i.e., we ensure that almost all the nodes run out of energy at about the same time so that there is very little energy waste due to residual energy. We compare the results for random deployment with those of a grid deployment in which nodes are placed deterministically along grid points. We observe that in both cases ‚1 scales approximately as p ‚0. Our results can be directly extended to take into account unreliable nodes.
The paper presents a routing algorithm that maximizes the lifetime of a sensor network in which all data packets are destined for a single collection node. Lifetime is maximized by adjusting the number of packets traversing each node. The adjustment is carried out by transmitting over alternative routes. The first part of the paper assumes that the worst case delay resulting from energy efficient routing is less than the maximum tolerable value. Ignoring the delay constraint of the network, the routes are selected as the solution to a linear programming (LP) problem in which the objective is to maximize the minimum lifetime of each node. The solution is implemented in a centralized algorithm, and then approximated by an iterative algorithm based on least cost path routing, in which each step is implemented efficiently in a distributed manner. The second part of the paper incorporates delay guarantee into energy efficient routing by constraining the length of the routing paths from each sensor node to the collection node. Simulations reveal that the lifetime of the network increases significantly by optimal routing, and including delay constraint in energy efficient routing improves the network performance since the delay of the network keeps increasing as the delay constraint is relaxed beyond the value at which the optimal lifetime is achieved.
Wireless Sensor and Actor Networks (WSANs) are composed of a large number of heterogeneous nodes called sensors and actors. The collaborative operation of sensors enables the distributed sensing of a physical phenomenon, while the role of actors is to collect and process sensor data and perform appropriate actions.In this paper, a coordination framework for WSANs is addressed. A new sensor-actor coordination model is proposed, based on an event-driven clustering paradigm in which cluster formation is triggered by an event so that clusters are created on-the-fly to optimally react to the event itself and provide the required reliability with minimum energy expenditure. The optimal solution is determined by mathematical programming and a distributed solution is also proposed. In addition, a new model for actor-actor coordination is introduced for a class of coordination problems in which the area to be acted upon is optimally split among different actors. An auction-based distributed solution of the problem is also presented.Performance evaluation shows how global network objectives, such as compliance with real-time constraints and minimum energy consumption, can be reached in the proposed framework with simple interactions between sensors and actors that are suitable for large-scale networks of energy-constrained devices.
This paper presents the Simple Packet Combining (SPaC) error-correction scheme for wireless sensor networks. Nodes buffer corrupt packets, and when two or more corrupt versions of a packet have been received, a packet combining procedure attempts to recover the original packet from the corrupt copies. Packet combining exploits the broadcast medium and spatial diversity of a multi-hop wireless network by using packets overheard at any node, in addition to the next-hop destination of the packet itself. Unlike point-to-point forward error correction (FEC), packet combining therefore helps multi-node interactions such as multi-hop routing or broadcasting as well as to hop-by-hop communication. Also, SPaC does not transmit redundant overhead on good links and does not require costly probes to estimate channel conditions. We have implemented SPaC as a link-layer extension on sensor nodes; it is transparent to upper layer protocols and has low memory and CPU footprints. We evaluate performance through a combination of analysis, trace-driven simulation, indoor and outdoor testbed micro-benchmarks, and deployment on a live network. The results show significant performance gains, even when accounting for the energy cost of CPU processing. We also present detailed bit-level link measurements and the design and evaluation of a new preamble detection scheme motivated by these measurements.
This paper describes a framework for achieving node-level fault tolerance (NLFT) in distributed real-time systems. The objective of NLFT is to mask errors at the node level in order to reduce the probability of node failures and thereby improve system dependability. We describe an approach called lightweight NLFT where transient faults are masked locally in the nodes by time-redundant execution of application tasks. The advantages of light-weight NLFT is demonstrated by a reliability analysis of an example brake-by-wire architecture. The results show that the use of light-weight NLFT may provide 55% higher reliability after one year and almost 60% higher MTTF, compared to using fail-silent nodes.
The paper investigates an anycast communication paradigm for a hybrid sensor/actuator network, consisting of both resource-rich and resource-impoverished devices. The key idea is to exploit the capabilities of resource-rich devices (called micro-servers) to reduce the communication burden on smaller sensor nodes which are energy, bandwidth and memory constrained. The goal is to deliver sensor data to the nearest micro-server, which can (i) store it, (ii) forward it to other micro-servers using out-of-band communication, or (iii) perform the desired actuation. Our approach is to construct an anycast tree rooted at each potential event source, which micro-servers can dynamically join and leave. Our anycast mechanism is self-organizing, distributed, robust, scalable, and incurs very little overhead. Simulations using ns-2 show that our anycast mechanism can reduce network energy consumption by more than 50%, both the mean end-to-end latency of the transmission and the mean number of transmissions by more than 50%, and achieves 99% data delivery rate for low and moderate micro-server mobility rate.
The growing complexity of hardware and software mandates the recognition of fault occurrence in system deployment and management. While there are several techniques to prevent and/or handle faults, there continues to be a growing need for an in-depth understanding of system errors and failures and their empirical and statistical properties. This understanding can help evaluate the effectiveness of different techniques for improving system availability, in addition to developing new solutions. In this paper, we analyze the empirical and statistical properties of system errors and failures from a network of nearly 400 heterogeneous servers running a diverse workload over a year. While improvements in system robustness continue to limit the number of actual failures to a very small fraction of the recorded errors, the failure rates are significant and highly variable. Our results also show that the system error and failure patterns are comprised of time-varying behavior containing long stationary intervals. These stationary intervals exhibit various strong correlation structures and periodic patterns, which impact performance but also can be exploited to address such performance issues.
Multi-criteria scheduling problems, involving optimization of more than one criterion, are subject to a growing interest. In this paper, we present a new bi-criteria scheduling heuristic for scheduling data-flow graphs of operations onto parallel heterogeneous architectures according to two criteria: first the minimization of the schedule length, and second the maximization of the system reliability. Reliability is defined as the probability that none of the system components will fail while processing. The proposed algorithm is a list scheduling heuristics, based on a bi-criteria compromise function that introduces priority between the operations to be scheduled, and that chooses on what subset of processors they should be scheduled. It uses the active replication of operations to improve the reliability. If the system reliability or the schedule length requirements are not met, then a parameter of the compromise function can be changed and the algorithm re-executed. This process is iterated until both requirements are met.
In this paper, we present a novel packet delivery mechanism called Multi-Path and Multi-SPEED Routing Protocol (MMSPEED) for probabilistic QoS guarantee in wireless sensor networks. The QoS provisioning is performed in two quality domains, namely, timeliness and reliability. Multiple QoS levels are provided in the timeliness domain by guaranteeing multiple packet delivery speed options. In the reliability domain, various reliability requirements are supported by probabilistic multipath forwarding. These mechanisms for QoS provisioning are realized in a localized way without global network information by employing localized geographic packet forwarding augmented with dynamic compensation, which compensates for local decision inaccuracies as a packet travels towards its destination. This way, MMSPEED can guarantee end-to-end requirements in a localized way, which is desirable for scalability and adaptability to large scale dynamic sensor networks. Simulation results show that MMSPEED provides QoS differentiation in both reliability and timeliness domains and, as a result, significantly improves the effective capacity of a sensor network in terms of number of flows that meet both reliability and timeliness requirements up to 50 percent (12 flows versus 18 flows).
We study the problem of using path diversification to provide low probability of packet loss (PPL) in wireless networks. Path diversification uses erasure codes and multiple paths in the network to transmit packets. The source uses Forward Error Correction (FEC) to encode each packet into multiple fragments and transmits the fragments to the destination using multiple disjoint paths. The source uses a load balancing algorithm to determine how many fragments should be transmitted on each path. The destination can reconstruct the packet if it receives a number of fragments equal to or higher than the number of fragments in the original packet. We study the load balancing algorithm in two general cases. In the first case, we assume that no knowledge of the performance along the paths is available at the source. In such a case, the source decomposes traffic uniformly among the paths; we call this case blind load balancing. We show that for low PPL, blind load balancing outperforms single-path transmission. In the second case, we assume that a feedback mechanism periodically provides the source with information about the performance along each path. With that information, the source can optimally distribute the fragments. We show how to distribute the fragments for minimized PPL, and maximized efficiency given a bound on PPL. We evaluate the performance of the scheme through numerical simulations.
We consider a heterogeneous sensor network in which nodes are to be deployed over a unit area for the purpose of surveillance. An aircraft visits the area periodically and gathers data about the activity in the area from the sensor nodes. There are two types of nodes that are distributed over the area using two-dimensional homogeneous Poisson point processes; type 0 nodes with intensity (average number per unit area) λ<sub>0</sub> and battery energy E<sub>0</sub>; and type 1 nodes with intensity λ<sub>1</sub> and battery energy E<sub>1</sub>. Type 0 nodes do the sensing while type 1 nodes act as the cluster heads besides doing the sensing. Nodes use multihopping to communicate with their closest cluster heads. We determine them optimum node intensities (λ<sub>0</sub>, λ<sub>1</sub>) and node energies (E<sub>0</sub>, E<sub>1</sub>) that guarantee a lifetime of at least T units, while ensuring connectivity and coverage of the surveillance area with a high probability. We minimize the overall cost of the network under these constraints. Lifetime is defined as the number of successful data gathering trips (or cycles) that are possible until connectivity and/or coverage are lost. Conditions for a sharp cutoff are also taken into account, i.e., we ensure that almost all the nodes run out of energy at about the same time so that there is very little energy waste due to residual energy. We compare the results for random deployment with those of a grid deployment in which nodes are placed deterministically along grid points. We observe that in both cases λ<sub>1</sub> scales approximately as √(λ<sub>0</sub>). Our results can be directly extended to take into account unreliable nodes.
In an ad hoc network, all communication is done over wireless
media, typically by radio through the air, without the help of wired
base stations. Since direct communication is allowed only between
adjacent nodes, distant nodes communicate over multiple hops. The
quality-of-service (QoS) routing in an ad hoc network is difficult
because the network topology may change constantly, and the available
state information for routing is inherently imprecise. In this paper, we
propose a distributed QoS routing scheme that selects a network path
with sufficient resources to satisfy a certain delay (or bandwidth)
requirement in a dynamic multihop mobile environment. The proposed
algorithms work with imprecise state information. Multiple paths are
searched in parallel to find the most qualified one. Fault-tolerance
techniques are brought in for the maintenance of the routing paths when
the nodes move, join, or leave the network. Our algorithms consider not
only the QoS requirement, but also the cost optimality of the routing
path to improve the overall network performance. Extensive simulations
show that high call admission ratio and low-cost paths are achieved with
modest routing overhead. The algorithms can tolerate a high degree of
information imprecision
In this paper, the problem of the surveillance and the security of indoor environments is addressed through the development of an autonomous surveillance vehicle (ASV). The ASV has been designed to perform, in addition to the classical robotic tasks (e.g., navigation and obstacle avoiding), the tracking of objects (e.g., persons) moving in indoor environments. The selection of the target object to be tracked can be decided by a remote operator or autonomously by the ASV itself in the case that a suspicious behavior has been detected (e.g., a person entering a forbidden area, etc.). The tracking procedure allows the ASV to maintain the interesting objects in the center of the image and in specific cases to localize particular parts of the object (e.g., face of a person, etc.) in order to recognize it. Experimental results have been performed on different real scenarios where no objects move inside the monitored scene and where a group of people move in a hallway
Large-scale wireless sensor networks represent a new generation of real-time embedded systems with significantly different communication constraints from traditional networked systems. This paper presents RAP, a new real-time communication architecture for large-scale sensor networks. RAP provides convenient, high-level query and event services for distributed micro -sensing applications. Novel location-addressed communication models are supported by a scalable and light-weight network stack. We present and evaluate a new packet scheduling policy called velocity monotonic scheduling that inherently accounts for both time and distance constraints. We show that this policy is particularly suitable for communication scheduling in sensor networks in which a large number of wireless devices are seamlessly integrated into a physical space to perform real-time monitoring and control. Detailed simulations of representative sensor network environments demonstrate that RAP significantly reduces the end-to-end deadline miss ratio in the sensor network.
This paper is concerned with coordinated delivery of messages in sensor networks. The notion of multicast is re-examined in light of a new set of requirements that are specific to such networks. The result of this investigation is a new concept called mobicast. It entails the delivery of messages to large sets of nodes in a manner that satisfies a potentially dynamic set of spatiotemporal constraints. In order to demonstrate the feasibility of mobicast, we present a novel topology-aware protocol for sensor networks. Worst-case analysis shows that the protocol provides strong spatial and temporal delivery guarantees under a set of reasonable assumptions about the network. The design of the protocol relies on new notions of compactness for spatially distributed networks. By explicitly addressing the temporal domain associated with message delivery, mobicast is more general than geocast and makes it possible to save precious resources in sensor networks by exploiting its inherent just-in-time delivery semantics.
Wireless sensor networks (WSNs) have gained considerable attention due to its significant potential in delivering a smart communication paradigm which enables setting up an intelligent network capable of handling wide range of applications and make sensor networks an integral part of our lives. The research in WSN put a great impact on our real-life activities, at the same time it also impose some unique communication challenges. The aim of this chapter is to address these cutting -edge research issues and challenges.
This paper focuses on the Delay/Fault-Tolerant Mobile Sensor Network (DFT-MSN) for pervasive information gathering. We develop simple and efficient data delivery schemes tailored for DFT-MSN, which has several unique characteristics such as sensor mobility, loose connectivity, fault tolerability, delay tolerability, and buffer limit. We first study two basic approaches, namely, direct transmission and flooding. We analyze their performance by using queuing theory and statistics. Based on the analytic results that show the tradeoff between data delivery delay/ratio and transmission overhead, we introduce an optimized flooding scheme that minimizes transmission overhead in flooding. Then, we propose a simple and effective DFT-MSN data delivery scheme, which consists of two key components for data transmission and queue management, respectively. The former makes decision on when and where to transmit data messages based on the delivery probability, which reflects the likelihood that a sensor can deliver data messages to the sink. The latter decides which messages to transmit or drop based on the fault tolerance, which indicates the importance of the messages. The system parameters are carefully tuned on the basis of thorough analyses to optimize network performance. Extensive simulations are carried out for performance evaluation. Our results show that the proposed DFT-MSN data delivery scheme achieves the highest message delivery ratio with acceptable delay and transmission overhead.
In this paper, we present a real-time communication protocol, called SPEED, for sensor networks. The protocol provides three types of real-time communication services, namely, real-time unicast, real-time area-multicast and real-time area-anycast. SPEED is specifically tailored to be a stateless, localized algorithm with minimal control overhead. End-to-end real-time communication guarantees are achieved using a novel combination of feedback control and non-deterministic QoS-aware geographic forwarding with a bounded hop count. SPEED is a highly efficient and scalable protocol for the sensor networks where node density is high while the resources of each node are scarce. Theoretical analysis and simulation experiments are provided to validate our claims.
Wireless sensor and actor networks (WSANs) refer to a group of sensors and actors linked by wireless medium to perform distributed sensing and acting tasks. The realization of wireless sensor and actor networks (WSANs) needs to satisfy the requirements introduced by the coexistence of sensors and actors. In WSANs, sensors gather information about the physical world, while actors take decisions and then perform appropriate actions upon the environment, which allows a user to effectively sense and act from a distance. In order to provide effective sensing and acting, coordination mechanisms are required among sensors and actors. Moreover, to perform right and timely actions, sensor data must be valid at the time of acting. This paper explores sensor-actor and actor-actor coordination and describes research challenges for coordination and communication problems.
An abstract is not available.
With an increasing acceptance of Wireless Sensor Networks (WSNs), the health of individual sensor is becoming critical in identifying important events in the region of interest. One of the key challenges in detecting event in a WSN is how to detect it accurately transmitting minimum information providing sufficient details about the event. At the same time, it is also important to devise a strategy to handle multiple events occurring simultaneously. In this paper, we propose a Polynomial-based scheme that addresses these problems of Event Region Detection (PERD) by having a aggregation tree of sensor nodes. We employ a data aggregation scheme, TREG (proposed in our earlier work) to perform function approximation of the event using a multivariate polynomial regression. Only coefficients of the polynomial (P) are passed instead of aggregated data. PERD includes two components: event recognition and event report with boundary detection. This can be performed for multiple simultaneously occurring events. We also identify faulty sensor(s) using the aggregation tree. Performing further mathematical operations on the calculated P can identify the maximum (max) and minimum (min) values of the sensed attribute and their locations. Therefore, if any sensor reports a data value outside the [min, max] range, it can be identified as a faulty sensor. Since PERD is implemented over a polynomial tree on a WSN in a distributed manner, it is easily scalable and computation overhead is marginal. Results reveal that event(s) can be detected by PERD with error in detection remaining almost constant achieving a percentage error within a threshold of 10% with increase in communication range. Results also show that a faulty sensor can be detected with an average accuracy of 94% and it increases with increase in node density.
We consider the problem of routing in a delay tolerant network (DTN) in the presence of path failures. Previous work on DTN routing has focused on using precisely known network dynamics, which does not account for message losses due to link failures, buffer overruns, path selection errors, unscheduled delays, or other problems. We show how to split, replicate, and erasure code message fragments over multiple delivery paths to optimize the probability of successful message delivery. We provide a formulation of this problem and solve it for two cases: a 0/1 (Bernoulli) path delivery model where messages are either fully lost or delivered, and a Gaussian path delivery model where only a fraction of a message may be delivered. Ideas from the modern portfolio theory literature are borrowed to solve the underlying optimization problem. Our approach is directly relevant to solving similar problems that arise in replica placement in distributed file systems and virtual node placement in DHTs. In three different simulated DTN scenarios covering a wide range of applications, we show the effectiveness of our approach in handling failures.
It was recently reported that all known face and combined greedy-face routing variants cannot guarantee message de- livery in arbitrary undirected planar graphs. The purpose of this article is to clarify that this is not the truth in gen- eral. We show that specifically in relative neighborhood and Gabriel graphs recovery from a greedy routing failure is al- ways possible without changing between any adjacent faces. Guaranteed delivery then follows from guaranteed recovery while traversing the very first face. In arbitrary graphs, however, a proper face selection mechanism is of impor- tance since recovery from a greedy routing failure may re- quire visiting a sequence of faces before greedy routing can be restarted again. A prominent approach is to visit a se- quence of faces which are intersected by the line connecting the source and destination node. Whenever encountering an edge which is intersecting with this line, the critical part is to decide if face traversal has to change to the next ad- jacent one or not. Failures may occur from incorporating face routing procedures that force to change the traversed face at each intersection. Recently observed routing failures which were produced by the GPSR protocol in arbitrary planar graphs result from incorporating such a face rout- ing variant. They cannot be constructed by the well known GFG algorithm which does not force changing the face any- time. Beside methods which visit the faces intersected by the source destination line, we discuss face routing variants which simply restart face routing whenever the next face has to be explored. We give the first complete and formal proofs that several proposed face routing, and combined greedy- face routing schemes do guarantee delivery in specific graph classes or even any arbitrary planar graphs. We also discuss the reasons why other methods may fail to deliver a message or even end up in a loop.
Many sensor network applications require location awareness, but it is often too expensive to include a GPS receiver in a sensor network node. Hence, localization schemes for sensor networks typically use a small number of seed nodes that know their location and protocols whereby other nodes estimate their location from the messages they receive. Several such localization techniques have been proposed, but none of them consider mobile nodes and seeds. Although mobility would appear to make localization more difficult, in this paper we introduce the sequential Monte Carlo Localization method and argue that it can exploit mobility to improve the accuracy and precision of localization. Our approach does not require additional hardware on the nodes and works even when the movement of seeds and nodes is uncontrollable. We analyze the properties of our technique and report experimental results from simulations. Our scheme outperforms the best known static localization schemes under a wide range of conditions.
In this paper, a new power aware many-to-many routing protocol for wireless sensor and actuator networks is introduced. The protocol has two versions adapted for three cases. The first version is designed for networks where every node transmits at the same power level. The transmission power level may not be adjustable, or can be adjusted according to a deployment scenario and changed before or after the deployment. The second version is for the case where nodes can individually adjust the transmission power according to the channel conditions and communications distance.
In this paper we present a data dissemination protocol for efficiently distributing data through a sensor network in the face of node and link failures. Our work is motivated by the SPIN protocol which uses metadata negotiation to minimize data transmissions. We propose a protocol called shortest path minded SPIN (SPMS) in which every node has a zone defined by its maximum transmission radius. A data source node advertises the availability of data to all the nodes in its zone. Any interested node requests the data and gets sent the data using multi-hop communication via the shortest path. The failure of any node in the path is detected and recovered using backup routes. We build simulation models to compare SPMS against SPIN. The simulation results show that SPMS reduces the delay over 10 times and consumes 30% less energy in the static failure free scenario. Even with the addition of mobility, SPMS outperforms SPIN by energy gains between 5% and 21%. An analytical model is also constructed to compare the two protocols under a simplified topology.
In this paper, we present a real-time communication protocol for sensor networks, called SPEED. The protocol provides three types of real-time communication services, namely, real-time unicast, real-time area-multicast and real-time area-anycast. SPEED is specifically tailored to be a stateless, localized algorithm with minimal control overhead End-to-end soft real-time communication is achieved by maintaining a desired delivery speed across the sensor network through a novel combination of feedback control and non-deterministic geographic forwarding. SPEED is a highly efficient and scalable protocol for sensor networks where the resources of each node are scarce. Theoretical analysis, simulation experiments and a real implementation on Berkeley motes are provided to validate our claims.
CEDAR is an algorithm for QoS routing in ad hoc network
environments. It has three key components: (a) the establishment and
maintenance of a self-organizing routing infrastructure called the core
for performing route computations, (b) the propagation of the link-state
of stable high-bandwidth links in the core through increase/decrease
waves, and (c) a QoS route computation algorithm that is executed at the
core nodes using only locally available state. But preliminary
performance evaluation shows that CEDAR is a robust and adaptive QoS
routing algorithm that reacts effectively to the dynamics of the network
while still approximating link-state performance for stable networks
We propose an approach to QoS (quality of service) routing in a
multimedia, multihop, wireless network. The wireless net can be either
stand alone, or connected to the wired net. The main focus of the paper
is the QoS routing procedure which can inform the source of the
bandwidth and quality of service available to any destination in the
wireless network. This knowledge enables the establishment of QoS
connections within the wireless network and the efficient support of
real time, multimedia traffic. In addition, it enables more effective
call acceptance control. In the case of an ATM interconnection, QoS
information permits one to extend the ATM virtual circuit service to the
wireless network, with possible renegotiation of QoS parameters at the
gateway. Simulation experiments show the efficiency of QoS routing in
selected multihop, mobile radio network scenarios
We present CEDAR, a core-extraction distributed ad hoc routing
algorithm for quality-of-service (QoS) routing in ad hoc network
environments, CEDAR has three key components: (a) the establishment and
maintenance of a self-organizing routing infrastructure called the core
for performing route computations; (b) the propagation of the link-state
of high bandwidth and stable links in the core through increase/decrease
waves; and (c) a QoS-route computation algorithm that is executed at the
core nodes using only locally available state. The performance
evaluations show that CEDAR is a robust and adaptive QoS routing
algorithm that reacts quickly and effectively to the dynamics of the
network while still approximating the performance of link-state routing
for stable networks
Communication security and reliability are two important issues in any network. A typical communication task in a wireless sensor network is for every sensor node to sense its local environment, and upon request, send data of interest back to a base station (BS). In this paper, a hybrid multipath scheme (H-SPREAD) to improve both the security and reliability of this task in a potentially hostile and unreliable wireless sensor network is proposed. The new scheme is based on a distributed N-to-1 multipath discovery protocol, which is able to find multiple node-disjoint paths from every sensor node to the BS simultaneously in one route discovery process. Then, a hybrid multipath data collection scheme is proposed. On the one hand, end-to-end multipath data dispersion, combined with secret sharing, enhances the security of the end-to-end data delivery in the sense that the compromise of a small number of paths will not result in the compromise of a data message in the face of adversarial nodes. On the other hand, in the face of unreliable wireless links and/or sensor nodes, alternate path routing available at each sensor node improves the reliability of each packet transmission significantly. The extensive simulation results show that the hybrid multipath scheme is very efficient in improving both the security and reliability of the data collection service seamlessly
The paper provides a top-level perspective on how the global
positioning system works, how its services are used, and delves into the
most important technical and geo-political factors affecting its
long-term availability in an international setting
Timely wireless communication is essential to allow real-time mobile applications, such as communication between mobile robots or inter-vehicle communication to be realized. The real-time event-based communication paradigm has been recognized as an appropriate highlevel communication scheme to connect autonomous components in large distributed control systems [1]. We investigate whether real-time event constraints can be guaranteed in a mobile ad hoc wireless network.
Wireless Sensor Networks have been proposed for a multitude of location-dependent applications. For such systems, the cost and limitations of hardware on sensing nodes prevent the use of range-based localization schemes that depend on absolute point-to-point distance estimates. Because coarse accuracy is sufficient for most sensor network applications, solutions in range-free localization are being pursued as a cost-effective alternative to more expensive range-based approaches. In this paper, we present APIT, a novel localization algorithm that is range-free. We show that our APIT scheme performs best when an irregular radio pattern and random node placement are considered, and low communication overhead is desired. We compare our work via extensive simulation, with three state-of-the-art range-free localization schemes to identify the preferable system configurations of each. In addition, we study the effect of location error on routing and tracking performance. We show that routing performance and tracking accuracy are not significantly affected by localization error when the error is less than 0.4 times the communication radio radius. 1.
The recent advances in radio and embedded system technologies have enabled the proliferation of wireless microsensor net works. Such wirelessly connected sensors are released in many diverse environments to perform various monitoring tasks. In many such tasks, location awareness is inherently one of the most essential system parameters. It is not only needed to report the origins of events, but also to assist group querying of sensors, routing, and to answer questions on the network coverage. In this paper we present a novel approach to the localization of sensors in an adhoc network. We describe a system called AHLoS (Ad-Hoc Localization System) that enables sensor nodes to discover their locations using a set distributed iterative algorithms. The operation of AHLoS is demonstrated with an accuracy of a few centimeters using our prototype testbed while scalability and performance are studied through simulation.
this paper, we propose using multipath routing to increase resilience to node failure. Multipath routing techniques have been discussed in the literature for several years now (Section V). However, the application of multipath routing to sensor networks and other systems that permit data-centric routing with localized path setup has not yet been explored. We consider two different approaches to constructing multipaths between two nodes. One is the classical node-disjoint multipath adopted by prior work, where the alternate paths do not intersect the original path (or each other). The disjoint property ensures that, when k alternate paths are constructed, no set of k node failures can eliminate all the paths. The other approach abandons the requirement for disjoint paths and instead builds many braided paths. With braided paths, there are typically no completely disjoint paths but rather many partially disjoint alternate paths
In this paper, we present a real-time communication protocol for sensor networks, called SPEED. The protocol provides three types of real-time communication services, namely, real-time unicast, real-time area-multicast and real-time area-anycast. SPEED is specifically tailored to be a stateless, localized algorithm with minimal control overhead. End-to-end soft real-time communication is achieved by maintaining a desired delivery speed across the sensor network through a novel combination of feedback control and non-deterministic geographic forwarding. SPEED is a highly efficient and scalable protocol for sensor networks where the resources of each node are scarce. Theoretical analysis, simulation experiments and a real implementation on Berkeley motes are provided to validate our claims.
We present Greedy Perimeter Stateless Routing (GPSR), a novel routing protocol for wireless datagram networks that uses the positions of routers and a packet's destination to make packet forwarding decisions. GPSR makes greedy forwarding decisions using only information about a router's immediate neighbors in the network topology. When a packet reaches a region where greedy forwarding is impossible, the algorithm recovers by routing around the perimeter of the region. By keeping state only about the local topology, GPSR scales better in per-router state than shortest-path and ad-hoc routing protocols as the number of network destinations increases. Under mobility's frequent topology changes, GPSR can use local topology information to find correct new routes quickly. We describe the GPSR protocol, and use extensive simulation of mobile wireless networks to compare its performance with that of Dynamic Source Routing. Our simulations demonstrate GPSR's scalability on densely deployed wir...