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Energy-aware Management for Cluster-based Sensor Networks
Abstract
Networking unattended sensors is expected to have a significant impact on the efficiency of many military and civil applications. Sensors in such systems are typically disposable and expected to last until their energy drains. Therefore, energy is a very scarce resource for such sensor systems and has to be managed wisely in order to extend the life of the sensors for the duration of a particular mission. In this paper, we present a novel approach for energy-aware management of sensor networks that maximizes the lifetime of the sensors while achieving acceptable performance for sensed data delivery. The approach is to dynamically set routes and arbitrate medium access in order to minimize energy consumption and maximize sensor life. The approach calls for network clustering and assigns a less-energy-constrained gateway node that acts as a cluster manager. Based on energy usage at every sensor node and changes in the mission and the environment, the gateway sets routes for sensor data, monitors latency throughout the cluster, and arbitrates medium access among sensors. We also describe a time-based medium access control (MAC) protocol and discuss algorithms for assigning time slots for the communicating sensor nodes. Simulation results show an order of magnitude enhancement in the time to network partitioning, 11% enhancement in network lifetime predictability, and 14% enhancement in average energy consumed per packet.
... Energy-saving clustering techniques for hierarchical routing protocols in WSNs with several nodes [8,9]. Many objectives are pursued in network clustering, including data aggregation [10], load balancing [7,11], and fault tolerance [12], network lifetime [13,14], energy efficiency [15], scalability [16], reliability [17], quality of service (QoS) support, and security [18]. During the clustering process groups of sensor nodes form clusters, and each cluster has a Cluster Head (CH). ...
... The leader will be in charge of transmitting the aggregated data to the BS. In the IEEPB-kMO protocol, the best node will be chosen as the leader node using the weight rule shown in Equation (13). [40,41]. ...
Wireless Sensor Networks (WSNs) due to their numerous applications have become a significant research topic in recent years, which include monitoring, tracking/detection, medical, military surveillance, and industrial. Due to the small sensors' difficulty in being easily recharged after random deployment, energy consumption is a challenging research problem for WSNs in general. One popular scenario for reducing energy consumption for WSNs is to use cluster‐based technology to reduce sensor node communication distance. Along with focusing on the Chain Cluster Based routing protocol classes. Initially, the Calinski Harabasz approach is utilized to find the optimum number of clusters. This modification will take place for two stages that pass via improving techniques of enhancing the Improved Energy‐Efficient PEGASIS‐Based (IEEPB) protocol to achieve the main goal of this study. The network lifetime was then extended by using the K‐means algorithm. As a result, rather than using a single long path, data is transferred over shorter parallel lines. The protocol is simulated with the MatlabR2015b simulator, which produces clear and effective simulation results, particularly in terms of energy savings. The outcome of the simulation results shows that the Improved energy‐efficient PEGASIS‐based routing protocol‐ KMeans optimisation (Improved EEPB‐ K‐means Optimisation) protocol outperforms the Low‐energy adaptive clustering hierarchy, Power‐efficient gathering in sensor information systems, IEEPB, and MIEEPB protocols.
... By stabilizing the network at the cluster level, the overhead for topology maintenance is reduced drastically. The end devices only concern themselves with connecting to their CHs without being affected by changes at the inter-CH tier [12]. Only the CHs and gateway nodes form the backbone network, resulting in much simpler topology, less overhead, flooding and collision. ...
... A CH can implement various scheduling algorithms to ensure that nodes operate in low-power mode when not active to conserve battery resources. For instance, nodes can be engaged in a round-robin fashion by specifying transmission and reception time slots so that collisions are avoided and redundancy minimized [11][12][13][14]. ...
Internet of Things is a paradigm shift in networking that seeks to connect virtually all things on the planet. Given the constrained nature of smart devices, energy efficient routing would play a key role in successful deployment of such networks. Clustering algorithms organize nodes of a network into groups or clusters and a specific designated node, cluster head is responsible for its cluster. Clustering algorithms have been particularly suggested in the context of Wireless Sensor Networks (WSN) but their application may also address similar challenges in Internet of Things (IoT). Clustering would facilitate energy efficient routing and topology management by delegating large chunk of communication overhead to cluster head. This paper presents a review of various clustering algorithms, analyses routing characteristics of various IoT domains and suggests appropriate clustering algorithms for each domain.
... Each sensor has a unique identification code ID_si, which has a length of 2 bytes stored in the chip. After the initialization of the network is completed, all nodes automatically run the cluster formation algorithm (this algorithm is not discussed in this paper; for more information, please refer to [38]), which results in m clusters being formed randomly by all nodes. There is only one CH and n/m sensor in each cluster. ...
Wireless sensor networks are usually applied in hostile areas where nodes can easily be monitored and captured by an adversary. Designing a key distribution scheme with high security and reliability, low hardware requirements, and moderate communication load is crucial for wireless sensor networks. To address the above objectives, we propose a new key distribution scheme based on an ECC asymmetric encryption algorithm. The two-way authentication mechanism in the proposed scheme not only prevents illegal nodes from accessing the network, but also prevents fake base stations from communicating with the nodes. The complete key distribution and key update methods ensure the security of session keys in both static and dynamic environments. The new key distribution scheme provides a significant performance improvement compared to the classical key distribution schemes for wireless sensor networks without sacrificing reliability. Simulation results show that the proposed new scheme reduces the communication load and key storage capacity, has significant advantages in terms of secure connectivity and attack resistance, and is fully applicable to wireless sensor networks.
... When S0 moves into cluster2, it will send a cluster-entry request to CH2. The cluster forming and cluster head detection process is not described here, please refer to [24]. 2. CH2 detects and receives this message. ...
Wireless sensor networks are usually applied in hostile areas where nodes are easy to be moni-tored and captured by adversary. Key distribution is an essential primitive to provide most of security mechanism. However, the characteristic of limited resources of sensors restricts the direct use of conventional key distribution schemes. In this paper, a complete security key distribution scheme based on asymmetric cryptography technology is proposed in both static and mobile scenarios. Mutual authentication is guaranteed using challenge-response mechanism. The per-formance evaluation and security analysis show that the proposed scheme with low complexity not only provides better security for wireless sensor networks, but also reduces storage overhead and key exposure risks.
... Routing methods in WSN are responsible for exploring and retaining energy efficient paths, to facilitate reliable and efficient communication [4,5]. The energy efficient routing protocols (EERP) are broadly categorized as: network structured, communication modelled, topology, and reliability based routing schemes [6,7]. The network structure based protocols can be broadly categorized as: flat structured and hierarchy based protocols. ...
In previous years, wireless sensor networks (WSNs) have fascinated lot of consideration from the scientific and technical society. The distributed characteristics and dynamic topology of sensor networks initiates very peculiar necessities in routing schemes that supposed to be met. The key feature of efficient routing protocol is energy expenditure and extension in lifetime of network. In past few years, various routing algorithms have been presented for WSNs. In this work, we focus on cluster based routing algorithms and propose a new algorithm for routing in WSNs. We perform the analysis of our new cluster based algorithms with existing algorithm on the basis of performance metrics. Simulation results shows that proposed algorithm outperform the other existing algorithms of his category.
... The clustering approach can be divided into two categories: static and dynamic. In a static approach, the cluster head is fixed during the clustering [30][31][32]. In contrast, in dynamic clustering, the cluster heads are changed periodically during clustering. ...
In this study, the multi-criteria decision-making (MCDM) technique is used in collaboration with K-medoids clustering to establish a novel algorithm for extending the lifetime of wireless sensor networks (WSNs) in the presence of uncertainty. One of the most important problems in WSNs is the energy consumption. Furthermore, extending the network lifetime in WSNs is highly dependent on selecting the appropriate cluster heads (CHs), and this can be a challenging task for the decision makers. In addition, parameters associated with WSNs are completely unexpected due to uncertainty. Therefore, after proposing K-medoids clustering and a MCDM technique, we have developed a novel algorithm for extending the lifetime of WSNs. As criteria, we have taken into account four important aspects of the proposed WSN: the distance from sink, average distance of cluster nodes, reliability of cluster and residual energy. To represent uncertain parameters in this work, we have considered triangular fuzzy numbers (TFNs). Finally, an experiment involving a WSN under uncertainty was investigated, and the findings have been graphically displayed. In this research, it has been observed that the proposed strategy with the novel algorithm exhibits 42% greater network lifetime as compared with a hybrid energy efficient distributed (HEED) algorithm and 11% and 18% with respect to optimal clustering artificial bee colony (OCABC) and particle swarm optimization (PSO) applied to a clustering optimization problem. We have also conducted statistical hypotheses for the purpose of confirming the presented outcomes.
... In real-time applications where sensed data is very sensitive and critical, maximizing the network lifetime of battery constrained sensors [7] is very important. CH's needs to be rotated between the cluster members on the basis of some selected parameters and cluster maintenance techniques needs to be applied to prolong the network lifetime. ...
Internet of Things (IoT) is about connecting and communicating between sensors nodes. Wireless sensor network (WSN) being the most appropriate network of sensors nodes plays an important role in IoT. But due to battery drainage issues of the sensor nodes WSN has limited network lifetime. An efficient way to extend the network lifetime of WSN is clustering i.e. to group the sensor nodes of the entire network into number of clusters; but it gives birth to hot-spot problem. Unequal clustering is the best solution to overcome such problems, in which sensor nodes are grouped into clusters of unequal sizes and the size varies according to the cluster head (CH) distance from the base station (BS). In this paper an attempt has been made to compare different unequal clustering algorithms highlighting their various features and objectives.
... The static part communications of the proposed NEMA method are based on the proposed protocol in [23,24]. The main assumptions of this protocol are: Fig. 3 Network structure in the proposed approach Content courtesy of Springer Nature, terms of use apply. ...
One of the applications of Sparse Linear Wireless Sensor Networks is environmental monitoring. In these networks, sensors are deployed in sensitive and strategic areas, such as highways and streets, to collect environmental data. Due to the long-term monitoring of the environment by the sensors and the lack of replacement of the energy source of the sensors, network lifetime is significantly reduced. Therefore, this paper presents the New Environment Monitoring Approach using Sparse Linear Wireless Sensor Networks (NEMA) for monitoring the environment using Dual Sinks. In the proposed NEMA method, static sensor nodes are scattered and equidistant from each other and monitor the environment. Due to being less, the number of sensor nodes relative to the area covered, data communication, and correlation are reduced. Therefore, the sensor nodes send the received packets to the destination without performing any data aggregation process. The proposed method was simulated in Simulator version 2 (NS-2). According to the criteria of average energy consumption, maximum waiting time, probability of sending data packets to the mobile sink node, average data packet delivery delay and network lifetime, the proposed method was compared with Classical approach 1 and Classical approach 2. The results obtained from the simulation data show the superiority of the proposed method over previous methods.
... It also is capable of localizing the route existing within the cluster; and, this way size of routing table inside the node would be reduced [2]. Moreover, clustering can keep communication band width intact; because, It makes intercluster interaction domain limited to cluster heads, and prevents exchange of unwanted messages [3]. Also, cluster head can keep data collected by sensors in its own cluster; so, number of relay packets would be reduced [4]. ...
Wireless sensor networks include sensor nodes communicating each other through wireless links for effective data collection and routing. These wireless nodes are of limited processing power, memory, communication range, channel band width, and battery capacity, from among which the most important is limited capacity of batteries which are unchangeable, under many conditions. The limitation encourages designing efficient protocols in terms of energy consumption. Using clustering is one of the methods to optimize energy consumption. On the other hand, a technical challenge in successful expansion of wireless sensor networks and their exploitation is effective usage made of limited channel band width. To overcome the challenge, one of the methods is dividing schedule of channel usage through TDMA method (Time-Division Multiple Access) so that each cluster head node creates a schedule for transmission of data from member nodes of the cluster through TDMA. Accordingly, in the paper, a distributed routing protocol based on clustering through usage of mimetic algorithm and time-sharing approach is proposed; and, it is capable of optimizing energy consumption and throughput rate, as well as reducing delay. The simulation results are indicative of better performance of proposed method, compared to IEEE 802.15.4 Standard.
... After network deployment, the sink node launches the cluster forming process (not discussed in this paper, please refer to [33]), which divides all sensor nodes into clusters with no cross coverage. Each cluster includes a sink node, which is called the "cluster head" (CH), and n/m sensors, which are called the "cluster members" (CM). ...
Because of the movements of sensor nodes and unknown mobility pattern, how to ensure two communicating (static or mobile) nodes authenticate and share a pairwise key is important. In this paper, we propose a mutual-authenticated key distribution scheme based on physical unclonable functions (PUFs) for dynamic sensor networks. Compared with traditional key predistribution schemes, the proposal reduces the storage overhead and the key exposure risks and thereby improves the resilience against node capture attacks. Mutual authentication is provided by the PUF challenge-response mechanism. However, the PUF response is not transmitted in plain forms so as to resist the modelling attacks, which is vulnerable in some existing PUF-based schemes. We demonstrate the proposed scheme to improve the secure connectivity and other performances by analysis and experiments.
... Clustering objectives are used to facilitate the needs of various applications used in wireless sensor networks. The different objectives used in network clustering are: Data Aggregation [143][144][145], Load balancing [93,146], Fault Tolerance [147], Network lifetime [148,149], Energy Efficiency [150,151], Scalability [152], Reliability [153], QoS support [154] and Security [155]. ...
Wireless Sensor Networks (WSNs) have attracted various academic researchers, engineers, science, and technology communities. This attraction is due to their broad research areas such as energy efficiency, data communication, coverage, connectivity, load balancing, security, reliability, scalability, and network lifetime. Researchers are looking towards cost-effective approaches to improve the existing solutions that reveal novel schemes, methods, concepts, protocols, and algorithms in the desired domain. Generally, review studies provide complete, easy access or solution to these concepts. Considering this as a driving force and the impact of clustering on the deterioration of energy consumption in wireless sensor networks, this review focus on clustering methods based on different aspects. This study’s significant contribution is to provide a brief review in the field of clustering in wireless sensor networks based on three different categories, such as classical, optimization, and machine learning techniques. For each of these categories, various performance metrics and parameters are provided, and a comparative assessment of the corresponding aspects like cluster head selection, routing protocols, reliability, security, and unequal clustering are discussed. Various advantages, limitations, applications of each method, research gaps, challenges, and research directions are considered in this study, motivating the researchers to carry out further research by providing relevant information in cluster-based wireless sensor networks.
... Furthermore, the link quality of wireless channel can affect the network characteristics, such as the energy consumption and network delay, and it is difficult and costly to be accurately calculated in practice. Therefore, a simple and effective evaluation method based on the communication distance and path-loss parameter has become an important research direction [30,31]. In [17], a reliability model evaluates the communications in wireless channel with severe obstacle or long communication distance as low success rate, and these communications requires more transmissions (retransmission mechanism) and consumes more energy. ...
The relay node deployment for wireless sensor network has many application constraints, such as the energy efficiency, stable connectivity, survivability and low cost. This paper explores this problem for static wireless sensor network. An efficient multi-constraint deployment strategy is proposed to save the deployment cost by deploying minimal relay nodes in candidate locations, to improve network lifetime by minimizing the maximum energy consumption of the relay nodes, and to improve network reliability by meeting a preset reliability threshold of the wireless communication. In order, the proposed strategy covers (a) extraction of three-dimensional discrete deployment space by shortest path search, (b) reliability evaluation of wireless channel in three-dimensional environment with electromagnetic obstacle, (c) energy consumption model for wireless communication with retransmission mechanism, (d) integer linear program-based formulation optimizing the amount, locations and lifetime of deployed relay nodes under the constraints of network survivability and reliability. The comparative simulation results indicate that the proposed strategy can reduce the solution time to minutes while the solution time of the existing methods is in hours when deploying dozens of sensors, and the result of the proposed deployment strategy can use the same number or slightly more relay nodes to achieve the best network lifetime, but the proposed strategy is not recommended to optimize the network reliability. In short, the proposed deployment strategy can ease the efficiency bottleneck while maintaining or even improving the algorithm performance.
... The network lifetime and scalability issue can be solved by hierarchical clustering [4][5][6], therefore, in this work we followed hierarchical clustering technique for node deployment. ...
In this paper, we propose a network framework for dynamic IoT applications such as smart healthcare system, animal monitoring system, which supports the core IoT feature: scalability. The proposed framework uses hierarchical topology for node deployment. To support uniform energy consumptions, the network is divided into equal size zone so that network load can be distributed equally and network lifetime can be increased. To make this framework more realistic as animal monitoring and smart healthcare system, Random Waypoint Model is used for node mobility under scheme 1 and scheme 2. In scheme 1, nodes can move in entire network and in scheme 2 nodes can move in their respective zones only. To avoid long distance communication, some nodes are promoted as relay node, zone head and zone coordinator. Sensor nodes begin the communication via nearest relay node. Relay node forward the packets to the zone head and zone head transmits these packets to base stations via upper layer zone coordinator. In the RN selection, we consider the ratio of node to zone head (ZH) distance and their residual energy. The node with shortest ratio is selected as RN. The comparison has been made of the proposed framework with static model, mobile under scheme 1 and 2.
... Clustering also has numerous advantages apart from energy saving [1]. It supports scalability, reduces the size of routing tables, saves the communication bandwidth and stabilizes network topology [2][3][4]. Two types of communication are involved in clusters: Intra-Cluster and Inter-Cluster. Cluster Head (CH) node aggregates data from Member Node (MN) during intra-cluster communication and the collected data are forwarded to sink node in inter-cluster communication. ...
Lifetime enhancement of sensor nodes became most important challenge in sensor networks. Clustering is the one of the technique used to reduce energy consumption and it saves node lifetime. However, the non-uniform distribution of nodes among clusters will affect the network in two ways: First, cluster heads of the crowded clusters perform more computation and communication and hence die sooner, thereby shortening the lifetime of the sensor network. Second, sensor nodes in crowded clusters have more delay in their data transmission to cluster head. To alleviate these problems, a novel energy efficient load-balancing algorithm is proposed in this paper. Further, to enhance the energy efficiency the adaptive power control and hybrid of TDMA/FDMA medium access scheme is used along with the load balancing algorithm. To evaluate the efficiency of the proposed method, the simulation is carried out and the results are compared with existing protocols in terms of energy efficiency, delay and packet delivery ratio.
... Where as, distributed algorithms are only executed locally without the global knowledge of whole topology. So, distributed algorithms are robust against transmission errors, node failures and more scalable as compare to centralized algorithms [8]. ...
In past years there has been increasing interest in field of Wireless Sensor Networks (WSNs). WSNs consist of large number of randomly distributed energy constrained sensor nodes. Sensor nodes have ability to sense and send sensed data to Base Station (BS). Sensing as well as transmitting data towards BS require high energy. Saving energy and extending network lifetime are great challenges. One of the major issue in WSN is development of energy efficient routing protocols. Clustering is an effective way to increase energy efficiency. Mostly heterogenous WSN protocols consider two or three energy level of nodes. In this thesis, I propose multiple novel clustering based routing techniques: Enhanced Developed Distributed Energy Efficient Clustering (EDDEEC), BEENISH (Balanced Energy Efficient Network Integrated Super Heterogenous) and Improved BEENISH (i-BEENISH) for heterogeneous WSNs. EDDEEC scheme is based on dynamically changing Cluster Head (CH) selection chances with more efficiency in three level heterogeneous WSN. BEENISH and i-BEENISH consider four types of nodes; normal, advanced, super and ultra-super nodes based on their initial energy in WSN. In BEENISH, CHs selection is made on residual energy level basis of nodes. Where as, i-BEENISH adaptively and more efficiently changes the CH election probability of high energy nodes when their energy get lower. Finally, the simulation results show that EDDEEC, BEENISH and i-BEENISH perform better than current important clustering protocols in heterogeneous WSNs containing varying heterogeneity level. The proposed protocols achieve longer stability, lifetime and more effective messages than Distributed Energy Efficient Clustering (DEEC), Developed DEEC (DDEEC) and Enhanced DEEC (EDEEC).
... Clustering is the key technique for decreasing battery consumption in which members of the cluster select a Cluster Head (CH). Many clustering protocols are designed in this regard [2,3,21,30]. In clustering, member nodes of a cluster send their sensing data to CH, where CH aggregates this data and transmits it to the BS [4][5][6]. ...
Wireless Sensor Networks (WSNs) contain a huge number of sensor nodes having
bounded power energy, which transmit their sensed information to the Base Station (BS) that is highly power constrained. The importance of WSN arises from their capability for detailed monitoring in remote and inaccessible areas where it is not feasible to install conventional wired infrastructure. Many routing protocols [23-29] have been proposed in this regard achieving energy efficiency in heterogeneous scenarios. However, every protocol is not suitable for heterogeneous WSNs. Efficiency of protocol degrades while changing the heterogeneity parameters. In this thesis, firstly I test Distributed Energy Efficient Clustering (DEEC), Developed DEEC (DDEEC), Enhanced DEEC (EDEEC) and Threshold DEEC (TDEEC) under several different scenarios containing high level heterogeneity to low level heterogeneity. I thoroughly observe their performance based on stability period, network life time and throughput. EDEEC and TDEEC perform better in
all heterogeneous scenarios containing variable heterogeneity in terms of life time, however TDEEC is best of all for the stability period of the network. However, the performance of DEEC and DDEEC is highly effected by changing the heterogeneity parameters of the network.
Then, I have taken four protocols into consideration that are Distributed EnergyEfficient Clustering (DEEC), Developed DEEC (DDEEC), Enhanced DEEC (EDEEC)
and Threshold DEEC (TDEEC) for comparing their performances in different scenarios of sink and network. Former their performance is observed with static sink
and later by keeping sink mobile to various patterns in the network. This thesis
caters for real time situations where throughput rate and network life of wireless
WSNs are always needed to be improved.
... Dans un RCSFà grande dimension, la structuration du réseau, suivant une approche centralisée, est très coûteuse en termes d'énergie, aussi bien surtout dans le cas d'une topologieà plat, qui est plutôt dédiée aux petits réseaux. Par conséquent, avec le passageà l'échelle, plusieurs contraintes, liéesà la consommation d'énergie [102], aux tables de routage par noeud [103],à l'occupation de la bande passante, etc, s'imposent. Dans la suite de cette thèse, nous visonsà travailler sur des réseauxà grandeéchelle. ...
Les réseaux de capteurs sans fil (RCSF) sont des réseaux ad hoc généralement constitués d’entités autonomes miniaturisées appelés noeuds capteurs pouvant communiquer entre eux par liaison radio. Les RCSF ont suscité beaucoup d’engouement dans la recherche scientifique en raison notamment des nouveaux problèmes de routage sous forte contrainte de durée de vie du réseau et de faibles capacités des noeuds.Ce type de réseau diffère des réseaux filaires par ses caractéristiques et limitations qui ont motivé le développement d’une nouvelle approche de conception cross-layer ignorant certains paradigmes de l’approche classique permettant l’échange mutuel d’informations même entre couches non adjacentes. Cette approche qui n’est pas encore standardisée, a démontré son intérêt à travers plusieurs travaux visant un meilleur compromis entre consommation d’énergie et une certaine qualité de service.Nos contributions peuvent être classées en deux catégories suivant la stratégie de routage à savoir le routage ad-hoc et le routage suivant la technique de clustering.Dans la première partie, nous proposons une architecture cross-layer, modulaire, adaptable et extensible nommée XL-AODV (cross layer AODV) basée sur l'échange du SNR (Signal-to-Noise-Ratio) entre la couche réseau et la couche physique qui a été modélisée par la distribution K. Nous évaluons sous le simulateur NS2 les performances de notre approche XL-AODV. Une analyse comparative avec AODV, a montré pour différentes configurations de réseaux, l’efficacité de notre proposition en termes de gains énergétiques et de latence de bout en bout.Pour la deuxième partie, nous proposons une première approche XL-LEACH qui constitue une amélioration de la version originale de LEACH, en l'adaptant aux réseaux de capteurs denses et à grande échelle tout en tenant compte des caractéristiques de la couche physique modélisée par la distribution K. Dans une troisième partie, nous introduisons une amélioration de XL-LEACH par l'approche dite, XL-CLEACH (XL Cooperative LEACH) en intégrant la communication coopérative au niveau MAC. Nous avons prouvé par une étude analytique qui a été validée par les simulations, le gain apporté en termes de consommation d’énergie, de la durée de vie du réseau et du TES (Taux d'Erreur Symbol). Les architectures XL-LEACH et XL-CLEACH ont été implémentées sous MATLAB.
... Unless the base station is mobile and can interface with the WSN through any node, establishing a strongly connected network is not essential in WSNs since data are gathered at the base-station. Therefore, ensuring the presence of a data route from a node to the basestation would be sufficient and thus fewer nodes can be employed to achieve network connectivity (Younis et al. 2003). ...
Milk and dairy products are frequently contaminated with enterotoxigenic Staphylococcus aureus, which is often involved in staphylococcal food poisoning. S. aureus and its enterotoxin (SEC) production in milk were modelled at constant temperatures of 25, 20, 37, and 40 C. Bacterial growth showed the classical exponential phase followed by stationary phase. The model described the early exponential phase of a growth curve linearly with time once the cell population reached about 108 CFU/ml.
... This acknowledgement has been monitored in regular time interval which helps to determine the route trust. 23 Notwithstanding this the course trust is figured by considering the measure of bundle transmitted and measure of parcel got. At that point the directing trust is computed as takes after. ...
Wireless Sensor Network (WSN) is a data communication network comprising of small sensor nodes having minimum energy that are randomly placed in the dynamically changing environment. At Present Scenario Noninvasive blood glucose sensors are still being worked on organizes considering that they are a long way from being appropriate for use in an artificial pancreas. The last has three fundamental parts: the blood glucose sensor, the insulin pump and the controller. In any case, for the biosensor data processing investigated here, some basic disappointments, for example , flag shifts and unbelievable picks were found. They should be considered, for processing the right insulin measurement for diabetic people. Compromising data in this mission critical environment are intolerable because they require reliable and timely information to offer their service. There exist several risk factors that compromise the data and the network performance. Thus, security in bio sensor network while transferring patient information over the sensor mesh for remote monitoring has become vital to protect the information in the network. During the data transmission process, the network handles various issues such as data security, network energy which leads to reduce the network lifetime which reduces the entire system quality as well as performance. For overcoming these issues, in this paper introduces the Secure Quality Aware Energy Efficient Zonal based Lifetime Maximizing Multi Path Routing Protocol (SQEZLMRP) for overcoming the mentioned challenges. Initially the particular zone related nodes are detected according to the conditions such as node energy, trust value of the node, because it helps to increase the network lifetime. Then multi path routing process is initiated for minimizing the intermediate attacks with effective manner. In addition to this quality of the network is handled by predicted zonal based multiple path which saves the network energy as well as life time. At last efficiency of the system is evaluated using simulation results such as energy consumption, packet delivery ratio, delay and so on.
... Maximal network longevity: Since sensor nodes are energy-constrained, the network's lifetime is a major concern; especially for applications of WSNs in harsh environments. When CHs are richer in resources than sensors, it is imperative to minimize the energy for intra-cluster communication [52]. If possible, CHs should be placed close to most of the sensors in its clusters [51,53]. ...
... The majority of the algorithms intended for WSNs focus mostly on maximising the network lifetime by minimising the energy utilisation. Researchers suggest that a successful method for dealing with the scalability and lifetime for WSNs is clustering (Banerjee and Khuller, 2001;Younis et al., 2003). Clustering offers numerous advantages, besides supporting network scalability; it can confine the set-up of a route inside the cluster and consequently decrease the routing table size maintained by individual nodes. ...
... The majority of the algorithms intended for WSNs focus mostly on maximising the network lifetime by minimising the energy utilisation. Researchers suggest that a successful method for dealing with the scalability and lifetime for WSNs is clustering (Banerjee and Khuller, 2001;Younis et al., 2003). Clustering offers numerous advantages, besides supporting network scalability; it can confine the set-up of a route inside the cluster and consequently decrease the routing table size maintained by individual nodes. ...
... For the sake of tackling the challenging issue, various technologies have been studied such as low-power radio communication hardware [13], energy-aware medium access control (MAC) layer protocols [61]. However, hierarchical clustering [1,8,10,43,51] has been testified to be an effective technique to conserve sensor energy [34,62] and also be a promising solution to schedulable tasks . ...
The design of energy efficiency is a very challenging issue for wireless sensor networks (WSNs). Clustering provides an effective means of tackling the issue. It could reduce energy consumption of the nodes and prolong the network lifetime. However, cluster heads deplete more energy since they bear great load of receiving, aggregation and transmission data than sensor nodes in WSNs. Therefore, the load-balanced clustering is the most significant problem for WSNs with unequal load of the sensor nodes but it is known to be an NP-hard problem. In this paper, we introduce a new model for this problem in which the objective function is to maximize the overall minimum lifetime of the cluster heads. To solve this model, we propose a novel estimation of distribution algorithm based dynamic clustering approach (EDA-MADCA). In EDA-MADCA, a new vector encoding is introduced for representing a complete clustering solution and a probability matrix model is constructed to guide the individual search. In addition, EDA-MADCA merges the EDA based exploration and the local search based exploitation within the memetic algorithm framework. A minimum-lifetime-based local search strategy is presented to avoid invalid search and enhance the local exploitation of the EDA. Experiment results demonstrate that EDA-MADCA can prolong network lifetime, it outperforms the existing DECA algorithm in terms of various performance metrics.
... For the sake of tackling the challenging issue, various technologies have been studied such as low-power radio communication hardware [3], energy-aware medium access control (MAC) layer protocols [4]. However, hierarchical clustering [5], [6] has been testified to be an effective technique to conserve sensor energy [7], [8] and also be a promising solution to schedulable tasks . ...
... lifetime. The metrics are a number of rounds that elapse before first node, half of the nodes and last node respectively, run out of energy [28,29]. ...
... Clustering in WSN context can be defined as a way of organizing a set of sensor nodes with its main objective is to prolong the lifetime of these sensors and increased network scalability by optimizing the energy consumption (Katiyar, Chand, & Soni, 2011;Younis, Youssef, & Arisha, 2003). Some of the major benefits derived from the implementation of clustering approach in WSN are briefly explain as below: ...
... Clustering in WSN context can be defined as a way of organizing a set of sensor nodes with its main objective is to prolong the lifetime of these sensors and increased network scalability by optimizing the energy consumption (Katiyar, Chand, & Soni, 2011;Younis, Youssef, & Arisha, 2003). Some of the major benefits derived from the implementation of clustering approach in WSN are briefly explain as below: ...
One of the biggest obstacles to the development of wireless sensor network (WSN) is achieving energy efficiency. Since transmission accounts for the majority of energy consumption, clustering of the network is adopted by the research community to address this issue. In clustering protocols, the prime focus is given on cluster head selection method to achieve better network lifetime. In this paper, the cluster head selection is optimized by using Firefly method where the attractiveness of the nodes is computed using Firefly which optimizes the head selection process. The protocol was simulated in MATLAB and the performance of the network was analyzed based on energy consumed in the network and number of nodes alive. The proposed protocol showed better performance than the other two indicating the achievement of better network lifetime. Keywords: Wireless sensor network (WSN), Firefly Optimization, Clustering, Energy efficiency
In a wireless sensor network, concealing the location of the sink is critical. Location of the sink can be revealed (or at least guessed with a high probability of success) through traffic analysis. In this paper, we proposed an energy efficient technique for concealing sink location named EESLP (Energy Efficient Sink Location Privacy) scheme. Here we proposed an approach, in which we are concealing the sink location in such a way so that node energy utilization while securing sink in network can be minimum, to defending sink's location privacy and identity when the network is subjected to multiple traffic analysis attack. EESLP designs the network area of coverage with multiple spots generating fake message traffic for fake sink location creation that resembles the traffic behavior that is expected to be observed in the area where the sink is located. To achieve this we select some sensors away from the actual sink location which act as fake sinks by generating dummy or fake packet. The simulation results prove that EESLP can improve network life time and QOS (congestion, throughput, packet delivery rate) of sensor network while protecting sinks Location privacy.
A new networking paradigm, which is seen as a cutting-edge approach to networks, is currently a priority research area: nature-inspired networking (NiN),
which is inspired from nature such as biological, social, and physical phenomena.
The book is a place for highly original ideas about how the nature is going to
shape networking systems of the future. Hence, it focuses on theory and applications, which encompass rigorous approaches and cutting-edge solutions that
take inspiration from nature for the development of novel problem solving techniques. To this end, we will take advantage of formal engineering methods and
establish in this book formal and practical aspects of NiN to achieve foundations
and practice of NiN.
The book is a reference for readers who already have a basic understanding of networking and are now ready to know how to use rigorous approaches
to develop networking that is inspired by nature. Hence, the book includes both
theoretical contributions and reports on applications. To keep a reasonable trade off between theoretical and practical issues, chapters were carefully selected to,
on one hand, cover a broad spectrum of formal and practical aspects and, on the
other hand, achieve as much as possible in a self-contained book.
Formal and practical aspects are presented in a straightforward fashion by
discussing in detail the necessary components and briefly touching on the more
advanced components. Therefore, theory and applications demonstrating how
to use the formal engineering methods for NiN will be described using sound
judgment and reasonable justifications.
This book, with chapters contributed by prominent researchers from
academia and industry, will serve as a technical guide and reference material for engineers, scientists, practitioners, and researchers by providing them
with state-of-the-art research findings and future opportunities and trends. These
contributions include state-of-the-art architectures, protocols, technologies, and
applications in NiN. In particular, the book covers existing and emerging research issues in NiN. The book has nine chapters addressing various topics from theory
to applications of NiN based on rigorous interdisciplinary approaches.
Background
The energy-constrained heterogeneous nodes are the most challenging wireless sensor networks (WSNs) for developing energy-aware clustering schemes. Although various clustering approaches are proven to minimise energy consumption and delay and extend the network lifetime by selecting optimum cluster heads (CHs), it is still a crucial challenge.
Methods
This article proposes a genetic algorithm-based energy-aware multi-hop clustering (GA-EMC) scheme for heterogeneous WSNs (HWSNs). In HWSNs, all the nodes have varying initial energy and typically have an energy consumption restriction. A genetic algorithm determines the optimal CHs and their positions in the network. The fitness of chromosomes is calculated in terms of distance, optimal CHs, and the node's residual energy. Multi-hop communication improves energy efficiency in HWSNs. The areas near the sink are deployed with more supernodes far away from the sink to solve the hot spot problem in WSNs near the sink node.
Results
Simulation results proclaim that the GA-EMC scheme achieves a more extended network lifetime network stability and minimises delay than existing approaches in heterogeneous nature.
In this paper a new criterion called Energy-Cost Function is presented according to which in each round the energy cost for any individual node is calculated. When transmitting their data, the nodes make decisions based on this very cost function. In case the nodes decides that it will cost a lower amount of energy transmitting the data to the sink by itself rather than by the cluster-head to the sink, then the node transmits the data directly. In this way the cluster overload is reduced and both the network lifetime and instability period is boosted. Based on the conditions of the problem, cost function parameters are variable and since all the decisions are made locally, network scalability potential is retained. Simulation results show that the network lifetime or its instability period based on the cost function employed will be improved up to 40% in relation to the LEACH protocol.
In Wireless Sensor Networks, Broadcast communication is the most fundamental and prevailing communication pattern. Securing the broadcast messages from the adversary is critical issue. To defend the WSNs against the adversary attacks of impersonation of a broadcast source or receiver, modification/fabrication of the broadcast message, attacker injecting malicious traffic to deplete the energy from the sensors, broadcast authentication of source and receivers becomes extremely inevitable. In this paper, we propose a novel ECC based public key distribution protocol and broadcast authentication scheme. The proposed method provides high security and has low overhead.
Wireless Sensor Network finds its extensive use in healthcare applications for the transfer of time-critical data through wireless connectivity. The primary cause of network failure is the transfer of time-critical multimedia data. The article presents a new differentiated service modelsupported (DSM) cluster-based routing in wireless sensor networks (WSNs) that overcomes the above issue. DSM prioritizes the transfer of different flow types based on packet type and packet size. The employment of computational offloading minimizes delay for critical and small-sized data packets and by carrying out data reduction of large-sized packets at proxy server. It outperforms the existing protocols in terms of energy efficiency, throughput, and reliability by prioritizing the transfer of time-critical health application data
This chapter describes routing and medium access control (MAC) mechanisms for providing Quality of Service (QoS) together with energy savings in wireless ad hoc networks. The proposed mechanisms operate in a cross-layer optimization logic, in the direction of either minimizing total energy consumption in the network or maximizing network lifetime, while at the same time providing QoS to the end users. The authors present a multi-cost routing approach, where various cost parameters and optimization functions are defined and used for selecting the paths to be followed. Also, routing and MAC protocols are investigated for the case where nodes have variable transmission power capabilities. Finally, the performance of the proposed protocols is evaluated and compared to that of other well-known routing and MAC protocols.
The 18 full and 13 short papers presented were carefully reviewed and selected from 255 submissions. There were organized in topical sections named: Image Processing, Pattern Analysis and Machine Vision; Information and Data Convergence; Disruptive Technologies for Future; E-Governance and Smart World
Analyzing the temporal behavior of frequent patterns and decreasing the size of discovered patterns are two major challenges in the area of temporal data mining. Several methods are available in this context, among them, constraint based pattern mining approach contributed a lot in this field. There are several methods have been proposed in this direction. However, while exploring the patterns based on time granularities: cyclic and partial cyclic patterns, the existing methods use the traditional Apriori algorithm or Interleaved algorithm, that takes lots of time while generating candidates. In this paper, a new strategy – Frequent Pattern Growth technique Incorporated with Special Constraints (FPGSC) is proposed. Here, complete cyclic and partial cyclic constraints are imposed on the framework consists of a Frequent pattern growth method for generating frequent patterns. This algorithm is able to discover complete cyclic and partial cyclic patterns in an efficient way. We also analyze the experimental results that show that it is as efficient as other algorithms in this field and it is better to generate more appropriate temporal patterns.
The last few years have seen an increased interest in the potential use of wireless sensor networks(WSNs) in various fields like disaster management, battle field surveillance, and border security surveillance as described by Quaritsch (2010), Hart (2006), Bokareva (2006) and Dudek (2009). In such applications, a large number of sensor nodes are deployed, which are often unattended and work autonomously. Clustering is a key technique used to extend the lifetime of a sensor network by reducing energy consumption (Younis 2003). It can also increase network scalability. Researchers in all fields of wireless sensor network believe that nodes are homogeneous, but some nodes may be of different energy to prolong the lifetime of a WSN and its reliability. In this paper, we study the impactof heterogeneity and survey different clustering algorithms for heterogeneous WSNs highlighting their objectives, features, complexity, etc.
Cette thèse considère les réseaux de capteurs sans fil (RCSF) de grande dimension (de l'ordre du million de noeuds). Les questions posées sont les suivantes : comment prédire le bon fonctionnement et calculer avant déploiement les performances d'un tel réseau, sachant qu'aucun simulateur ne peut simuler un réseau de plus de 100 000 noeuds ? Comment assurer sa configuration pour garantir performance, passage à l'échelle, robustesse et durabilité ? La solution proposée dans cette thèse s'appuie sur une architecture de RCSF hétérogène à deux niveaux, dont le niveau inférieur est composé de capteurs et le niveau supérieur de collecteurs. La première contribution est un algorithme d'auto-organisation multi-canal qui permet de partitionner le réseau inférieur en plusieurs sous-réseaux disjoints avec un collecteur et un canal de fréquence par sous-réseau tout en respectant le principe de réutilisation de fréquence. La seconde contribution est l'optimisation du déploiement des collecteurs car leur nombre représente celui des sous-réseaux. Les problèmes traités ont été : l'optimisation des emplacements des puits pour un nombre prédéfini de puits et la minimisation du nombre de puits ou du coût pour un nombre prédéfini de sauts dans les sous-réseaux. Une solution intuitive et appropriée pour assurer à la fois performances réseaux et coût, est de partitionner le réseau inférieur en sous-réseaux équilibrés en nombre de sauts. Pour ce faire, la topologie physique des puits est une répartition géographique régulière en grille (carrée, triangulaire, etc.). Des études théoriques et expérimentales par simulation des modèles de topologie montrent, en fonction des besoins applicatifs et physiques, la méthodologie de choix et le calcul des meilleures solutions de déploiement.
A Wireless Sensor Network (WSN) consists of sensor nodes which are distributed over the network, where each sensor node composed of sensing unit along with limited computational power, low storage capacity and limited non-rechargeable battery source, resulting WSN to be energy constrained. In the proposed work a heterogeneous network is considered, in which uniformly placed nodes are divided into two levels of heterogeneity on the basis of energy. For the sake of long network lifetime, transmission to BS is done via Cluster Heads (CH’s) resulting in faster drainage of CH node. So to manage the load on CH’s, a new static clustering technique gained into its inception which includes CH’s of higher energy, that in addition to increase network lifetime, also will reduce hop count to BS. The simulation result shows a significant improvement in stability as well as network lifetime of the proposed technique.
Wireless sensor networks (WSNs) form an important part of industrial application. There has been growing interest in the potential use of WSNs in applications such as environment monitoring, disaster management, health care monitoring, intelligence surveillance and defence reconnaissance. In these applications, the sensor nodes (SNs) are envisaged to be deployed in sizeable numbers in an outlying area, and it is quite difficult to replace these SNs after complete deployment in many scenarios. Therefore, as SNs are predominantly battery powered devices, the energy consumption of the nodes must be properly managed in order to prolong the network lifetime and functionality to a rational time. Different energy-efficient and energy-balanced routing protocols have been proposed in literature over the years. The energy-efficient routing protocols strive to increase the network lifetime by minimizing the energy consumption in each SN. On the other hand, the energy-balanced routing protocols protract the network lifetime by uniformly balancing the energy consumption among the nodes in the network. There have been various survey papers put forward by researchers to review the performance and classify the different energy-efficient routing protocols for WSNs. However, there seems to be no clear survey emphasizing the importance, concepts, and principles of load-balanced energy routing protocols for WSNs. In this paper, we provide a clear picture of both the energy-efficient and energy-balanced routing protocols for WSNs. More importantly, this paper presents an extensive survey of the different state-of-the-art energy-efficient and energy-balanced routing protocols. A taxonomy is introduced in this paper to classify the surveyed energy-efficient and energy-balanced routing protocols based on their proposed mode of communication towards the base station (BS). In addition, we classified these routing protocols based on the solution types or algorithms, and the input decision variables defined in the routing algorithm. The strengths and weaknesses of the choice of the decision variables used in the design of these energy-efficient and energy-balanced routing protocols are emphasised. Finally, we suggest possible research directions in order to optimize the energy consumption in sensor networks.
This paper describes simulations of the power saving mechanism of the upcoming standard for wireless Local Area Networks IEEE 802.11[1]. They were performed in order to see how typical parameters influence the performance. Simulations were made for a adhoc -network with 8 stations. Figures for optimum Beacon intervals and ATIM window sizes were obtained. 1. Introduction Wireless Local Area Networks (WLANs) are a rapidly growing area in networking. This is basically due to the upcoming of portable devices like notebooks and mobile phones. A key feature of these devices is that the limited battery capacity, which limits their time in action. This results in a need of power saving mechanisms, which prolong the life time of the batteries. The next chapter describes in short different ways to address the power saving problem. Chapter 2 shows the way power saving is implemented in the IEEE standard 802.11. After that we describe the simulated environment, the source model and the parameter...
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 classic problem of finding the shortest path over a network has been the target of many research efforts over the years. These research efforts have resulted in a number of different algorithms and a considerable amount of empirical findings with respect to performance. Unfortunately, prior research does not provide a clear direction for choosing an algorithm when one faces the problem of computing shortest paths on real road networks. Most of the computational testing on shortest path algorithms has been based on randomly generated networks, which may not have the characteristics of real road networks. In this paper, we provide an objective evaluation of 15 shortest path algorithms using a variety of real road networks. Based on the evaluation, a set of recommended algorithms for computing shortest paths on real road networks is identified. This evaluation should be particularly useful to researchers and practitioners in operations research, management science, transportation, and Geographic Information Systems.
Advances in micro-sensor and radio technology will enable small but smart sensors to be deployed for a wide range of environmental monitoring applications. Moreover, the low per-node cost will allow these wireless networks of sensors and actuators to be densely distributed. The nodes in these dense networks will coordinate to perform the distributed sensing tasks. Moreover, as described in this paper, the nodes can also coordinate to exploit the redundancy provided by high density, so as to extend overall system lifetime. The large number of nodes deployed in these systems will preclude manual configuration, and the environmental dynamics will preclude design-time pro-configuration. Therefore, nodes will have to self-configure to establish a topology that provides communication and sensing coverage under stringent energy constraints. In ASCENT, each node assesses its connectivity and adapts its participation in the multi-hop network topology based on the measured operating region. This paper motivates and describes the ASCENT algorithm and presents results from experiments conducted on our wireless testbed.
Wireless sensor networks have potential to monitor environments for both military and civil applications. Due to inhospitable conditions these sensors are not always deployed uniformly ion the area of interest. Since sensors are generally constrained in on-board energy supply, efficient management of the network is crucial to extend the life of the sensors. Sensors' energy cannot support long haul communication to reach a remote command site and thus requires many levels of hops or a gateway to forward the data on behalf of the sensor. In this paper, we propose an algorithm to network these sensors in to well define clusters with less energy-constrained gateway nodes acting as cluster-heads, and balance load among these gateways. Simulation results show how our approach can balance the load and improve the lifetime of the system.
During the past few years distributed wireless sensor networks have been the focus of considerable research for both military and civil applications. Sensors are generally constrained in on-board energy supply therefore efficient management of the network is crucial to extend the life of the system. Sensors' energy cannot support long haul communication to reach a remote command site, thus they require multi-tier architecture to forward data. An efficient way to enhance the lifetime of the system is to partition the network into distinct clusters with a high-energy node called a gateway as cluster-head. Failures are inevitable in sensor networks due to the inhospitable environment and unattended deployment. However, failures in higher level of hierarchy e.g. cluster-head cause more damage to the system because they also limit accessibility to the nodes that are under their supervision. In this paper we propose an efficient mechanism to recover sensors from a failed cluster. Our approach avoids a full-scale re-clustering and does not require deployment of redundant gateways.
Advances in microsensor and radio technology enable small but smart sensors to be deployed for a wide range of environmental monitoring applications. The low-per node cost allows these wireless networks of sensors and actuators to be densely distributed. The nodes in these dense networks coordinate to perform the distributed sensing and actuation tasks. Moreover, as described in this paper, the nodes can also coordinate to exploit the redundancy provided by high density so as to extend overall system lifetime. The large number of nodes deployed in this systems preclude manual configuration, and the environmental dynamics precludes design-time preconfiguration. Therefore, nodes have to self-configure to establish a topology that provides communication under stringent energy constraints. ASCENT builds on the notion that, as density increases, only a subset of the nodes is necessary to establish a routing forwarding backbone. In ASCENT, each node assesses its connectivity and adapts its participation in the multihop network topology based on the measured operating region. This paper motivates and describes the ASCENT algorithm and presents analysis, simulation, and experimental measurements. We show that the system achieves linear increase in energy savings as a function of the density and the convergence time required in case of node failures while still providing adequate connectivity.
The advancement in wireless communications and electronics has enabled the development of low-cost sensor networks. The sensor networks can be used for various application areas (e.g., health, military, home). For different application areas, there are different technical issues that researchers are currently resolving. The current state of the art of sensor networks is captured in this article, where solutions are discussed under their related protocol stack layer sections. This article also points out the open research issues and intends to spark new interests and developments in this field.
The IEEE 802.11 MAC protocol is the standard for wireless LANs; it
is widely used in testbeds and simulations for wireless multihop ad hoc
networks. However, this protocol was not designed for multihop networks.
Although it can support some ad hoc network architecture, it is not
intended to support the wireless mobile ad hoc network, in which
multihop connectivity is one of the most prominent features. In this
article we focus on the following question: can the IEEE 802.11 MAC
protocol function well in multihop networks? By presenting several
serious problems encountered in an IEEE 802.11-based multihop network
and revealing the in-depth cause of these problems, we conclude that the
current version of this wireless LAN protocol does not function well in
multihop ad hoc networks. We thus doubt whether the WaveLAN-based system
is workable as a mobile ad hoc testbed
The authors describe the type of signals that occur in various
environments and the modeling of the propagation parameters. Models are
essentially of two classes. The first class consists of parametric
statistical models that on average describe the phenomenon within a
given error. They are simple to use, but relatively coarse. In the last
few years a second class of environment-specific models has been
introduced. These models are of a more deterministic nature,
characterizing a specific street, building, etc. They are necessarily
more time consuming to use, but are also more revealing concerning
physical details and hopefully more accurate. Some key parameters and
the measurement of them are discussed and then the different wireless
environments are treated. The latter topic is divided into outdoor
environments, indoor environments, and radio penetration from outdoor to
indoor environments
Sensor networks are poised for increasingly wider uses in many military and civil applications. We present a bootstrapping protocol for a class of sensor networks in which the network has high-energy entities called gateways apart from the low-energy sensors. Most research activity in the field of sensor networks focuses on organizing the network and then proceeds to look for energy saving. However, we argue that bootstrapping done inefficiently can be a major source of energy wastage. We present an energy-aware mechanism for initializing the network. Our proposed approach focuses on avoiding collisions in the bootstrapping phase and stresses on keeping receiver/transmitter units off whenever possible to preserve energy. In addition, our mechanism synchronizes the sensor nodes to the gateway's time base so that TDMA based communication can be used. We study the performance of our mechanism using simulation and compare it to the performance of a basic approach in which sensor nodes have to keep their receivers ON throughout the bootstrapping process, and show the scalability of our system as compared to such approaches.
This paper describes simulations of the power saving mechanism of the upcoming standard for wireless Local Area Networks IEEE 802.11[1]. They were performed in order to see how typical parameters influence the performance. Simulations were made for a adhoc -network with 8 stations. Figures for optimum Beacon intervals and ATIM window sizes were obtained. 1. Introduction Wireless Local Area Networks (WLANs) are a rapidly growing area in networking. This is basically due to the upcoming of portable devices like notebooks and mobile phones. A key feature of these devices is that the limited battery capacity, which limits their time in action. This results in a need of power saving mechanisms, which prolong the life time of the batteries. The next chapter describes in short different ways to address the power saving problem. Chapter 2 shows the way power saving is implemented in the IEEE standard 802.11. After that we describe the simulated environment, the source model and the parameter...
This paper presents Span, a power saving technique for multi-hop ad hoc wireless networks that reduces energy consumption without significantly diminishing the capacity or connectivity of the network. Span builds on the observation that when a region of a shared-channel wireless network has a sufficient density of nodes, only a small number of them need be on at any time to forward traffic for active connections. Span is a distributed, randomized algorithm where nodes make local decisions on whether to sleep, or to join a forwarding backbone as a coordinator. Each node bases its decision on an estimate of how many of its neighbors will benefit from it being awake, and the amount of energy available to it. We give a randomized algorithm where coordinators rotate with time, demonstrating how localized node decisions lead to a connected, capacity-preserving global topology. Improvement in system lifetime due to Span increases as the ratio of idle-to-sleep energy consumption increases. Our simulations show that with a practical energy model, system lifetime of an 802.11 network in power saving mode with Span is a factor of two better than without. Additionally, Span also improves communication latency and capacity.
In this paper, we ask a fundamental question concerning the limits of energy eciency of wireless sensor networks - what is the upper bound on the lifetime of a sensor network that collects data from a speciÞed region using a certain number of energy-constrained nodes? The answer to this question is valuable for two main reasons. First, it allows calibration of real world data-gathering protocols and an un- derstanding of factors that prevent these protocols from approaching fundamental limits. Second, the dependence of lifetime on factors like the region of observation, the source behavior within that region, basestation location, number of nodes, radio path loss characteristics, eciency of node electronics and the energy available on a node, is exposed. This allows architects of sensor networks to focus on fac- tors that have the greatest potential impact on network lifetime. By employing a combination of theory and extensive simulations of con- structed networks, we show that in all data gathering scenarios pre- sented, there exist networks which achieve lifetimes equal to or >85% of the derived bounds. Hence, depending on the scenario, our bounds are either tight or near-tight.
The current trend to develop low cost, miniature unattended ground sensor (UGS) will enable a cost-effective, covert means for surveillance in both urban and remote border areas. Whereas the functionality (e.g., sensing range and life in the field) of these individual UGS (i.e., acoustic, seismic, magnetic, chemical or biological) are limited due to size and cost constraints, a network of these sensors working cooperatively together can provide an effective surveillance capability. A key factor is the ability of these sensors to work cooperatively to achieve a `collective' functionality that can meet the surveillance objective. For example, a realistic mission objective would be to use the minimum number of sensors necessary (i.e., preserve the life of the network) to detect, identify and track vehicles in a desert canyon area that has variable wind and temperature conditions. The network would have to assess the effect of the wind direction and temperature on the sensing range of its acoustic sensors, turn on those sensors that can initially detect the target and dynamically activate other appropriate sensors (e.g., seismic, acoustic or imaging sensors) that can identify and track the vehicle as it moves into and across the canyon area covered by the sensor network. To achieve this type of functionality requires system algorithms that are capable of optimizing the utilization of the sensors. This paper describes results that show improved target tracking accuracy by optimizing the selection of acoustic sensors that measure bearing angles to the target. Also, recent results are described from testing the tracking algorithm with real data.
It is well known that computing shortest paths over a network is an important task in many network and transportation related analyses. Choosing an adequate algorithm from the numerous algorithms reported in the literature is a critical step in many applications involving real road networks. In a recent study, a set of three shortest path algorithms that run fastest on real road networks has been identified. These three algorithms are: 1) the graph growth algorithm implemented with two queues, 2) the Dijkstra algorithm implemented with approximate buckets, and 3) the Dijkstra algorithm implemented with double buckets. As a sequel to that study, this paper reviews and summarizes these three algorithms, and demonstrates the data structures and procedures related to the algorithms. This paper should be particularly useful to researchers and practitioners in transportation, GIS, operations research and management sciences.
This paper presents Span, a power saving technique for multi-hop ad hoc wireless networks that reduces energy consumption without significantly diminishing the capacity or connectivity of the network. Span builds on the observation that when a region of a shared-channel wireless network has a sufficient density of nodes, only a small number of them need be on at any time to forward traffic for active connections. Span is a distributed, randomized algorithm where nodes make local decisions on whether to sleep, or to join a forwarding backbone as a coordinator. Each node bases its decision on an estimate of how many of its neighbors will benefit from it being awake, and the amount of energy available to it. We give a randomized algorithm where coordinators rotate with time, demonstrating how localized node decisions lead to a connected, capacity-preserving global topology. Improvement in system lifetime due to Span increases as the ratio of idle-to-sleep energy consumption increases, and increases as the density of the network increases. For example, our simulations show that with a practical energy model, system lifetime of an 802.11 network in power saving mode with Span is a factor of two better than without. Span integrates nicely with 802.11 - when run in conjunction with the 802.11 power saving mode, Span improves communication latency, capacity, and system lifetime.
This paper describes a novel method for organizing a randomly distributed group of sensors. The group is heterogeneous in the sense that it contains sensors of different types that can detect either unique or multiple target types. For a given distribution of sensors, the goal of the system is to determine the optimal combination of sensors that can detect and/or locate the targets. An optimal combination is the one that minimizes the power consumption of the entire sensor network and gives the best accuracy of location of desired targets. We approach the problem in two phases. First, sensors are clustered according to morphology and location. Next, a genetic algorithm determines the optimal combination of sensors to achieve a given objective. The genetic algorithm restricts reproduction, crossover and mutation operations to sensors belonging to the same cluster. We devised a chromosome decoder that changes the original constrained optimization problem into an unconstrained problem. The technique developed is tested on a simulated data set and the results are described.
In this paper we study the energy efficiency and channel efficiency of TDMA MAC protocol scheduling mechanisms. Most MAC protocols are based on phase grouping that basically has three phases in a frame: uplink, downlink and reservation. We propose a new mechanism in which we have multiple uplink and downlink phases. These phases are grouped per mobile in a frame. Although this has a negative effect on the capacity of the channel, it allows the mobile to turn the power off from the wireless interface for a longer period. We made this choice since in a mobile multimedia environment it is more important that connections have a certain QoS, than highest possible bandwidth. We present an analysis in which these two basic mechanisms are compared in respect to bandwidth efficiency and energy efficiency. We have developed and implemented a novel MAC protocol based on mobile grouping that provides Quality of Service (QoS) support for diverse traffic types.
The up-coming Gbps high-speed networks are expected to support a wide range of real-time, communication-intensive applications. The quality-of-service (QoS) requirements for the timely delivery of multimedia information raise new challenges for the development of integrated-service broadband networks. One of the key issues is QoS routing, which allows selecting network routes with sufficient resources for requested QoS parameters. The goal of QoS routing solutions is two-folded: satisfying the QoS requirements for every admitted connection and achieving global efficiency in resource utilization. Many unicast/multicast QoS routing algorithms were published recently. However, there still exist a lot of unsolve problems in this area. A few examples are listed as follows. (1) There lacks a simple solution with predictable performance and adjustable overhead for the NP-complete multi-constraint routing problem. (2) All existing algorithms are tailored towards specific problems, and there lacks a simple, general routing framework which can be easily extended to handle new problems. (3) Most routing algorithms assume the availability of precise state information about the network, which however is impractical in the real world. We address the above problems, and the goal of this dissertation is to provide simple, general and extensible solutions for QoS routing. We study different routing strategies, compare them and outline the challenges. We propose various algorithms based on different network state models, evaluate these algorithms by analysis and simulation, discuss their strengths and weaknesses of different routing strategies, and compare them with the existing algorithms. The major achievement of this dissertation is outline in the following. 1. A heuristic approach is proposed to solve the multi-constraint routing problem. It allows the dynamic tradeoff between performance and overhead. 2. A distributed routing framework is proposed to integrate a family of routing algorithms which support applications with QoS requirements on bandwidth, delay, delay jitter, cost, path length, and their combination. 3. Source and distributed routing algorithms are proposed to work with state information which has a high degree of imprecision. 4. Distributed QoS routing algorithms are proposed for mobile ad-hoc networks whose topologies change as nodes move, join, or leave the networks. 5. An integrated framework is proposed to support routing and scheduling of co-existing QoS and best-effort flows.
Wireless microsensor networks lend themselves to trade-offs in energy and quality. In these networks, the individual sensor data per se are not necessarily important to the end user. Rather, it is the combined knowledge of all the sensors that describes what is occurring in the environment. By allowing the algorithms and protocols to adapt the quality of this description, with a corresponding change in energy dissipation, sensor networks can be flexible to the end-user's requirements. In this paper, we provide models for predicting quality and energy and show the advantages of trading off these two parameters. By ensuring that the system operates at a minimum energy for each quality point, the system can achieve both flexibility and energy efficiency, allowing the end-user to maximize system lifetime.
Wireless distributed microsensor systems will enable the reliable monitoring of a variety of environments for both civil and military applications. In this paper, we look at communication protocols, which can have significant impact on the overall energy dissipation of these networks. Based on our findings that the conventional protocols of direct transmission, minimum-transmission-energy, multi-hop routing, and static clustering may not be optimal for sensor networks, we propose LEACH (Low-Energy Adaptive Clustering Hierarchy), a clustering-based protocol that utilizes randomized rotation of local cluster based station (cluster-heads) to evenly distribute the energy load among the sensors in the network. LEACH uses localized coordination to enable scalability and robustness for dynamic networks, and incorporates data fusion into the routing protocol to reduce the amount of information that must be transmitted to the base station. Simulations show the LEACH can achieve as much as a factor of 8 reduction in energy dissipation compared with conventional outing protocols. In addition, LEACH is able to distribute energy dissipation evenly throughout the sensors, doubling the useful system lifetime for the networks we simulated.
Portable products are being used increasingly. Because these systems are battery powered, reducing power consumption is vital. In this report we give the properties of low-power design and techniques to exploit them on the architecture of the system. We focus on: minimizing capacitance, avoiding unnecessary and wasteful activity, and reducing voltage and frequency. We review energy reduction techniques in the architecture and design of a hand-held computer and the wireless communication system including error control, system decomposition, communication and MAC protocols, and low-power short range networks.
Five efficient shortest path algorithms are implemented and compared in this report. The selected algorithms are the most efficient, measured either in terms of worst case bounds or from previous computational studies. The algorithms include two using threshold functions, two using heaps, and one using buckets for sorting node labels. The last three algorithms have not been studied in detail before. The computational experiment employs a rigorous design to ensure that the results have statistical validity. Three different cost functions are generated to measure the sensitivity of each algorithm to cost distributions. Curve fittings are performed to summarize the results and they show high degrees of goodness-of-fit. The results reveal some heretofore unknown properties of some of the algorithms.
In this paper we develop a new multiaccess protocol for ad hoc radio networks. The protocol is based on the original MACA protocol with the adition of a separate signalling channel. The unique feature of our protocol is that it conserves battery power at nodes by intelligently powering off nodes that are not actively transmitting or receiving packets. The manner in which nodes power themselves off does not influence the delay or throughput characteristics of our protocol. We illustrate the power conserving behavior of PAMAS via extensive simulations performed over ad hoc networks containing 10-20 nodes. Our results indicate that power savings of between 10% and 70% are attainable in most systems. Finally, we discuss how the idea of power awareness can be built into other multiaccess protocols as well.
We ask a fundamental question concerning the limits of energy
efficiency of sensor networks-what is the upper bound on the lifetime of
a sensor network that collects data from a specified region using a
certain number of energy-constrained nodes? The answer to this question
is valuable for two main reasons. First, it allows calibration of real
world data-gathering protocols and an understanding of factors that
prevent these protocols from approaching fundamental limits. Secondly,
the dependence of lifetime on factors like the region of observation,
the source behavior within that region, basestation location, number of
nodes, radio path loss characteristics, efficiency of node electronics
and the energy available on a node, is exposed. This allows architects
of sensor networks to focus on factors that have the greatest potential
impact on network lifetime. By employing a combination of theory and
extensive simulations of constructed networks, we show that in all data
gathering scenarios presented, there exist networks which achieve
lifetimes equal to or >95% of the derived bounds. Hence, depending on
the scenario, our bounds are either tight or near-tight
Networks of distributed microsensors are emerging as a compelling
solution for a wide range of data gathering applications. Perhaps the
most substantial challenge facing designers of small but long-lived
microsensor nodes is the need for significant reductions in energy
consumption. We propose a power-aware design methodology that emphasizes
the graceful scalability of energy consumption with factors such as
available resources, event frequency, and desired output quality, at all
levels of the system hierarchy. Our architecture for a power-aware
microsensor node highlights the collaboration between software that is
capable of energy-quality tradeoffs and hardware with scalable energy
consumption
Energy efficiency is an important issue for mobile computers since
they must rely on their batteries. We present an energy-efficient highly
adaptive architecture of a network interface and novel data link layer
protocol for wireless networks that provides quality of service (QoS)
support for diverse traffic types. Due to the dynamic nature of wireless
networks, adaptations are necessary to achieve energy efficiency and an
acceptable quality of service. The paper provides a review of ideas and
techniques relevant to the design of an energy efficient adaptive
wireless network
An ad-hoc network of wireless static nodes is considered as it
arises in a rapidly deployed, sensor-based, monitoring system.
Information is generated in certain nodes and needs to reach a set of
designated gateway nodes. Each node may adjust its power within a
certain range that determines the set of possible one hop away
neighbors. Traffic forwarding through multiple hops is employed when the
intended destination is not within immediate reach. The nodes have
limited initial amounts of energy that is consumed at different rates
depending on the power level and the intended receiver. We propose
algorithms to select the routes and the corresponding power levels such
that the time until the batteries of the nodes drain-out is maximized.
The algorithms are local and amenable to distributed implementation.
When there is a single power level, the problem is reduced to a maximum
flow problem with node capacities and the algorithms converge to the
optimal solution. When there are multiple power levels then the
achievable lifetime is close to the optimal (that is computed by linear
programming) most of the time. It turns out that in order to maximize
the lifetime, the traffic should be routed such that the energy
consumption is balanced among the nodes in proportion to their energy
reserves, instead of routing to minimize the absolute consumed power
The concept of energy aware software is introduced. A simple
energy model for software is presented that separates the switching and
leakage components and predicts its total energy consumption with less
than 5% error for a set of benchmark programs. The experiments have been
performed on the StrongARM SA-1100 microprocessor. A mathematical model
for the total leakage current has also been proposed and it has been
shown that they can account for about 10% of the energy dissipation for
low threshold voltage microprocessors and, assuming continuous
operation, the leakage energy fraction gets significantly higher for
lowest duty cycle
Transmitter power control can be used to concurrently achieve
several key objectives in wireless networking, including minimizing
power consumption and prolonging the battery life of mobile nodes,
mitigating interference and increasing the network capacity, and
maintaining the required link QoS by adapting to node movements,
fluctuating interference, channel impairments, and so on. Moreover,
power control can be used as a vehicle for implementing on-line several
basic network operations, including admission control, channel selection
and switching, and handoff control. We consider issues associated with
the design of power-sensitive wireless network architectures, which
utilize power efficiently in establishing user communication at required
QoS levels. Our focus is mainly on the network layer and less on the
physical one. Besides reviewing some of the developments in power
control, we also formulate some general associated concepts which have
wide applicability to wireless network design. A synthesis of these
concepts into a framework for power-sensitive network architectures is
done, based on some key justifiable points. Various important relevant
issues are highlighted and discussed, as well as several directions for
further research in this area. Overall, a first step is taken toward the
design of power-sensitive network architectures for next-generation
wireless networks
This paper describes a self-organizing, multihop, mobile radio
network which relies on a code-division access scheme for multimedia
support. In the proposed network architecture, nodes are organized into
nonoverlapping clusters. The clusters are independently controlled, and
are dynamically reconfigured as the nodes move. This network
architecture has three main advantages. First, it provides spatial reuse
of the bandwidth due to node clustering. Second, bandwidth can be shared
or reserved in a controlled fashion in each cluster. Finally, the
cluster algorithm is robust in the face of topological changes caused by
node motion, node failure, and node insertion/removal. Simulation shows
that this architecture provides an efficient, stable infrastructure for
the integration of different types of traffic in a dynamic radio network
Most ad hoc mobile devices today operate on batteries. Hence,
power consumption becomes an important issue. To maximize the lifetime
of ad hoc mobile networks, the power consumption rate of each node must
be evenly distributed, and the overall transmission power for each
connection request must be minimized. These two objectives cannot be
satisfied simultaneously by employing routing algorithms proposed in
previous work. We present a new power-aware routing protocol to satisfy
these two constraints simultaneously; we also compare the performance of
different types of power-related routing algorithms via simulation.
Simulation results confirm the need to strike a balance in attaining
service availability performance of the whole network vs. the lifetime
of ad hoc mobile devices
An ad-hoc network of wireless static nodes is considered as it arises in a rapidly deployed, sensor based, monitoring system. Information is generated in certain nodes and needs to reach some designated gateway node. Each node may adjust its power within a certain range that determines the set of possible one hop away neighbors. Traffic forwarding through multiple hops is employed when the intended destination is not within immediate reach. The nodes have limited initial amounts of energy that are consumed in different rates depending on the power level and the intended receiver. We propose algorithms to select the routes and the corresponding power levels such that the time until the batteries of the nodes drain-out is maximized. The algorithms are local and amenable to distributed implementation.
In this paper we present a case for using new power-aware metrics for determining routes in wireless ad hoc networks. We present five different metrics based on battery power consumption at nodes. We show that using these metrics in a shortest-cost routing algorithm reduces the cost/packet of routing packets by 5-30% over shortest-hop routing (this cost reduction is on top of a 40-70% reduction in energy consumption obtained by using PAMAS, our MAC layer protocol). Furthermore, using these new metrics ensures that the mean time to node failure is increased significantly. An interesting property of using shortest-cost routing is that packet delays do not increase. Finally, we note that our new metrics can be used in most traditional routing protocols for ad hoc networks. 1
We introduce a geographical adaptive delity (GAF) algorithm that reduces energy consumption in ad hoc wireless networks. GAF conserves energy by identifying nodes that are equivalent from a routing perspective and then turning o unnecessary nodes, keeping a constant level of routing delity. GAF moderates this policy using application- and system-level information; nodes that source or sink data remain on and intermediate nodes monitor and balance energy use. GAF is independent of the underlying ad hoc routing protocol; we simulate GAF over unmodied AODV and DSR. Analysis and simulation studies of GAF show that it can consume 40% to 60% less energy than an unmodi ed ad hoc routing protocol. Moreover, simulations of GAF suggest that network lifetime increases proportionally to node density; in one example, a four-fold increase in node density leads to network lifetime increase for 3 to 6 times (depending on the mobility pattern). More generally, GAF is an example of adaptive delity, a technique proposed for extending the lifetime of self-conguring systems by exploiting redundancy to conserve energy while maintaining application delity. 1.
A self-organizing, cooperative UGS network for target tracking
- R Burne
R. Burne et al., A self-organizing, cooperative UGS network for target tracking, in: Proceedings of SPIE Conference on Unattended Ground Sensor Technologies and Applications II, Orlando, April 2000.
Data sheet for the acoustic ballistic module, Available from 〈http
- Sentech Inc
SenTech Inc., Data sheet for the acoustic ballistic module, Available from <http://www.sentech-acoustic.com/>.