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Intelligent Approach for Data Collection in Wireless Sensor Networks
Abstract
In wireless sensor networks, one of most important issues is data collection from sensors to sink. Many researchers employ a mathematical formula to select the next forwarding node in the network-wide manner. We are motivated that surrounding environments for nodes are different in time and space. Because different situations of nodes are not considered for selecting the next forwarding node, the performance of data collection is degraded. In this paper, we present an intelligent approach for data collection in sensor networks. We model a nonlinear cost function for determining the next forwarder according to the input types whether inputs are correlated or uncorrelated for generating the output of the function. In our method, the correlated inputs are presented in a weighted sum with the dependent fashion but the uncoupled inputs with an independent fashion in the nonlinear function. The weights in the functions are determined to the direction in which the reliability of data collection maximizes. In the experimental section, we show that our method outperforms other conventional methods with respect to the efficiency in data collection from sensors to sink.
... For the purpose of determining gathering path, we propose a technique that is inspired by the work in [51,52] to collect data, when a collector node intends to send its data to the BS, a path is created between them to deliver the data. This phase consists of three stages, backbone formation stage, parent selection and data collection stage. ...
One of the major challenges in realizing a reliable wireless sensor network (WSN) that can survive under the emerging applications is the constrained energy of the sensors. Hence, extending the lifetime of WSN is a major concern, which directly impacts the performance of various WSN-based applications. In this regard, various methods have been developed that either investigate the energy consumption or lifetime enhancement of WSN. A promising method to conserve the energy of the sensors is to use sleep–awake scheduling by choosing disjoint groups of nodes called dominating set (DS). By distributing the data collection duties among these DSs, one DS handles these tasks for a specified period of time before being replaced by another group, extending the lifespan of the network. This problem becomes challenging in WSN with heterogeneous energy. Despite the success of the algorithms in determining the DS, none of the existing methods consider the node’s energy while creation or selection of DS. This motivates us to utilize the DSs concept to control and maintain sleep/awake schedule of WSN nodes with heterogeneous energy. Toward this goal, we propose an energy-aware algorithm known as proposed initializer for whale optimization algorithm-based operator (PI-WOA-BO) to construct disjoint DSs that work as collector nodes for data gathering in each round and extend the total WSN lifetime. An energy-aware fitness function is introduced for selecting the best DSs that can maximize the WSN lifetime. Simulation results reveal that PI-WOA-BO exhibits enhanced performance over baseline techniques under various metrics including energy, stability, reliability and lifetime of WSN. PI-WOA-BO outperforms FUZZY-DS-ACO, CDS-FOR, BEE-VBC and CDS-LEACH by (17.4%, 40.1%, 31.1% and 53.6%), (7.7%, 33.5%, 23.4% and 48.5%) and (7.9%, 33.5%, 22.9% and 47.8%) in terms of First, Half and Last node dies, respectively.
... In order to determine the path of data gathering, we propose an intelligent data collection method that is inspired by the work in [24] and [27]. When the collector node intends to send its data, a path is established between the collector node and the BS to deliver the data. ...
Wireless Sensor Networks (WSNs) lend themselves to a wide variety of applications in our daily lives, such as environmental monitoring, safety, health-care, animal monitoring, etc. However, one of the key issues in WSN is energy constraints. This makes energy-conservation one of the major keys to the efficient functioning and lifetime of WSN. In this paper, given a network of nodes with heterogeneous energy, our goal is to determine energy-aware disjoint dominating sets (DSs) that work as data collection nodes in each round, to improve overall WSN lifetime. In order to accomplish this goal, we propose an intelligent data collection technique with two phases, the collector nodes selection, and the data gathering path formation and collection phases. In the collector nodes selection phase, an energy-aware algorithm based on swarm intelligence is proposed to construct disjoint dominating sets that work as collector nodes in each round. In the data gathering path formation and collection phase, data gathering path is determined for achieving maximal data collection efficiency and reduced energy consumption. The efficiency of our proposed technique is proved mathematically and through simulations.
... Conversely, a sink may capture proper actions based on the information supplied by the sensors; the precision of the condition politeness is enhanced by reducing the data loss. To trim down the data loss, several researchers utilize a mathematical formula for data collection from sensors to sink in the network in a wide manner [1]". Vol 3(1) | January-June-2016 | semantic concept to formulate rules to identity malicious browsing behaviors in order to slice the cost [4]. ...
... Conversely, a sink may capture proper actions based on the information supplied by the sensors; the precision of the condition politeness is enhanced by reducing the data loss. To trim down the data loss, several researchers utilize a mathematical formula for data collection from sensors to sink in the network in a wide manner [1]". semantic concept to formulate rules to identity malicious browsing behaviors in order to slice the cost [4]. ...
Flooding attacks play a vital role in network. Most of the people are working on the cloud computing environment either as a provider or as a consumer. The flooding attack is a challenge to the resources of network and bandwidth of the host for web page. Nowadays, web based applications are developed in the cloud computing environment. The FAPA (Flooding Attack Prevention Architecture) is used to prevent flooding attacks in cloud based computing environment. The LEACH protocol helps to improve the system lifetime by reducing the energy used to transmit the data to the base station. The aim of this work is to prevent the flooding attacks in cloud and transfer the data in a fast and secured manner using MLEACH (Modified Low Energy Adaptive Clustering Hierarchy).
... A Congestion Aware Reliable Information Transport (ReCAIT) [18] ensured reliability in wireless sensor networks using the combined acknowledgement and retransmission scheme under different network conditions. In [19], an intelligent methodology for efficient data collection in wireless networks was presented using nonlinear cost function. Though efficient in terms of throughput, the correlation among the inputs remains unaddressed. ...
To ensure fair packet broadcasting without service disruption in wireless network from one network cell to another is the key to successful mobile services. However, enforcing fair packet broadcasting is challenging because decision policies within the network cell though works efficiently, considerably reduces the energy consumption level. Using MAC protocol, communication framework gets improved by cooperatively localizing the system and achieves space-time synchronization. But redundancy occurs on cellular wireless network for higher energy levels. This work presents the design and implementation of collision free packet broadcasting in wireless network known as Consistent Shortcut Transfigure Path Construction (CSTPC) mechanism. Under this mechanism the main objective is to develop a transfigure path (i.e., alter path) when the link failure occurs during broadcasting (i.e.,) handover the call. Initially, consistent shortcut is created for constructing alter path and when the link gets failed packet handover takes place. Consistent shortcut is created by combining the Midpoint and Simpsons rule procedure. The Midpoint and Simpsons procedure creates the shortcut and with this reduces the rate of energy consumption gradually. Secondly, error rate on call handover is reduced using CSTPC mechanism by applying Estimation of Distribution algorithm. The constructed Estimation of Distribution algorithm in CSTPC mechanism feasibly handover the packets to neighboring base station with minimal error rate. In this way, minimal error rate avoids retransmission of packets due to the collision and path failure. Furthermore, the CSTPC mechanism reduce the energy consumption level on transfigure path construction and also avoids the retransmission of packets (i.e.,) call in wireless network. Experimental work is carried out using factors such as avoidance of retransmission rate, energy consumption rate, and call broadcasting efficiency.
... A Quality of Service (QoS) based performance and resource management scheme in 3G wireless network for realistic environments is presented by [30]. An intelligent approach for data collection in Wireless Sensor Network (WSN) was presented by [19]. ...
Adaptive Resource Allocation is a prominent and necessary feature of almost all future communication systems. The transmission parameters like power, code rate and modulation scheme are adapted according to the varying channel conditions so that throughput of the OFDM system may be maximized while satisfying certain constraints like bit error rate and total power at the same time. For real time systems, it is required that the adaptive process should be fast enough to synchronize with Channel State Information (CSI) and Quality of Service (QoS) demand that change rapidly. So in this paper, we have a real time system in which once CSI and QoS is fed in as input, it gives us optimal modulation code pairs (MCPs) and power vectors for different subcarriers. Using a Fuzzy Rule Base System (FRBS) we obtain MCP by giving CSI and QoS and by using Differential Evolution (DE) the power vector is obtained. This becomes an example. A Gaussian Radial Basis Function Neural Network (GRBF-NN) is trained in offline mode using sufficient number of such examples. After training, given QoS and CSI as input GRBF-NN gives optimum power vector and FRBS gives optimum MCP immediately. Proposed scheme is compared with various other schemes of same domain and supremacy of the proposed scheme is shown by the simulations.
Wireless sensor networks (WSN) are event based systems that rely on the collective effort of several microsensor nodes. Reliable event detection at the sink is based on collective information provided by source nodes and not on any individual report. Hence, conventional end-to-end reliability definitions and solutions are inapplicable in the WSN regime and would only lead to a waste of scarce sensor resources. However, the absence of reliable transport altogether can seriously impair event detection. Hence, the WSN paradigm necessitates a collective phevent-to-sink reliability notion rather than the traditional end-to-end notion. To the best of our knowledge, reliable transport in WSN has not been studied from this perspective before.In order to address this need, a new reliable transport scheme for WSN, the event-to-sink reliable transport (ESRT) protocol, is presented in this paper. ESRT is a novel transport solution developed to achieve reliable event detection in WSN with minimum energy expenditure. It includes a congestion control component that serves the dual purpose of achieving reliability and conserving energy. Importantly, the algorithms of ESRT mainly run on the sink, with minimal functionality required at resource constrained sensor nodes. ESRT protocol operation is determined by the current network state based on the reliability achieved and congestion condition in the network. If the event-to-sink reliability is lower than required, ESRT adjusts the reporting frequency of source nodes aggressively in order to reach the target reliability level as soon as possible. If the reliability is higher than required, then ESRT reduces the reporting frequency conservatively in order to conserve energy while still maintaining reliability. This self-configuring nature of ESRT makes it robust to random, dynamic topology in WSN. Analytical performance evaluation and simulation results show that ESRT converges to the desired reliability with minimum energy expenditure, starting from any initial network state.
We present a new metric for routing in multi-radio, multi-hop wireless networks. We focus on wireless networks with stationary nodes, such as community wireless networks.The goal of the metric is to choose a high-throughput path between a source and a destination. Our metric assigns weights to individual links based on the Expected Transmission Time (ETT) of a packet over the link. The ETT is a function of the loss rate and the bandwidth of the link. The individual link weights are combined into a path metric called Weighted Cumulative ETT (WCETT) that explicitly accounts for the interference among links that use the same channel. The WCETT metric is incorporated into a routing protocol that we call Multi-Radio Link-Quality Source Routing.We studied the performance of our metric by implementing it in a wireless testbed consisting of 23 nodes, each equipped with two 802.11 wireless cards. We find that in a multi-radio environment, our metric significantly outperforms previously-proposed routing metrics by making judicious use of the second radio.
This article advocates a new computing paradigm, called computing with time, that is capable of efficiently performing a certain class of computation, namely, searching in parallel for the closest
value to the given parameter. It shares some features with the idea of computing with action potentials proposed by Hopfield, which originated in the field of artificial neuron networks. The basic idea of computing with time
is captured in a novel distributed algorithm based on broadcast communication called the lecture hall algorithm, which can compute the minimum among n positive numbers, each residing on a separate processor, using only O(1) broadcasts. When applied to sensor networks, the lecture hall algorithm leads to an interesting routing protocol having several
desirable properties.
This paper proposes a new method to model partially connected feedforward neural networks (PCFNNs) from the identified input type (IT) which refers to whether each input is coupled with or uncoupled from other inputs in generating output. The identification is done by analyzing input sensitivity changes as amplifying the magnitude of inputs. The sensitivity changes of the uncoupled inputs are not correlated with the variation on any other input, while those of the coupled inputs are correlated with the variation on any one of the coupled inputs. According to the identified ITs, a PCFNN can be structured. Each uncoupled input does not share the neurons in the hidden layer with other inputs in order to contribute to output in an independent manner, while the coupled inputs share the neurons with one another. After deriving the mathematical input sensitivity analysis for each IT, several experiments, as well as a real example (blood pressure (BP) estimation), are described to demonstrate how well our method works.
While traditional routing protocols try to minimize the end-to-end delay or maximize the throughput, most energy-aware routing protocols for wireless sensor networks try to extend the life time of the network by minimizing the energy consumption sacrificing other performance metrics. We introduce a new energy-aware routing protocol that tries to minimize the energy consumption and, at the same time, maintain good end-to-end delay and throughput performance. The new algorithm is based on a constrained shortest-path algorithm. We compare the new algorithm with some traditional routing and energy-aware routing algorithms. The results show that the new algorithm performance is acceptable under all performance metrics and presents a performance balance between the traditional routing algorithms and the energy-aware routing algorithms. The constraint value can be chosen to achieve different performance objectives for different sensor network missions.
In the recent past, wireless sensor networks have found their way into a wide variety of applications and systems with vastly varying requirements and characteristics. As a consequence, it is becoming increasingly difficult to discuss typical requirements regarding hardware issues and software support. This is particularly problematic in a multidisciplinary research area such as wireless sensor networks, where close collaboration between users, application domain experts, hardware designers, and software developers is needed to implement efficient systems. In this article we discuss the consequences of this fact with regard to the design space of wireless sensor networks by considering its various dimensions. We justify our view by demonstrating that specific existing applications occupy different points in the design space.
Wireless sensor networks consist of small nodes with sensing, computation, and wireless communications capabilities. Many routing, power management, and data dissemination protocols have been specifically designed for WSNs where energy awareness is an essential design issue. Routing protocols in WSNs might differ depending on the application and network architecture. In this article we present a survey of state-of-the-art routing techniques in WSNs. We first outline the design challenges for routing protocols in WSNs followed by a comprehensive survey of routing techniques. Overall, the routing techniques are classified into three categories based on the underlying network structure: flit, hierarchical, and location-based routing. Furthermore, these protocols can be classified into multipath-based, query-based, negotiation-based, QoS-based, and coherent-based depending on the protocol operation. We study the design trade-offs between energy and communication overhead savings in every routing paradigm. We also highlight the advantages and performance issues of each routing technique. The article concludes with possible future research areas.
When compared with now classical MANETs, sensor networks have different characteristics, and present different design and engineering challenges. One of the main aspects of sensor networks is that the solutions tend to be very application-specific. For this reason, a layered view like the one used in OSI imposes a large penalty, and implementations more geared toward the particular are desirable. This survey presents the three main paradigms for communication in ad hoc networks and discusses their applicability for routing, querying, and discovery. We conclude that the node-centric approach, although the oldest and best understood, is not the most appropriate for large-size low-energy application-specific sensor networks.
A wireless sensor network consists of many low-cost, low-power sensor nodes, which can perform sensing, simple computation, and transmission of sensed information. Long distance transmission by sensor nodes is not energy efficient since energy consumption is a superlinear function of the transmission distance. One approach to prolonging network lifetime while preserving network connectivity is to deploy a small number of costly, but more powerful, relay nodes whose main task is communication with other sensor or relay nodes. In this paper, we assume that sensor nodes have communication range r>0, while relay nodes have communication range Rgesr, and we study two versions of relay node placement problems. In the first version, we want to deploy the minimum number of relay nodes so that, between each pair of sensor nodes, there is a connecting path consisting of relay and/or sensor nodes. In the second version, we want to deploy the minimum number of relay nodes so that, between each pair of sensor nodes, there is a connecting path consisting solely of relay nodes. We present a polynomial time 7-approximation algorithm for the first problem and a polynomial time (5+epsi)-approximation algorithm for the second problem, where epsi>0 can be any given constant
A new energy-efficient wireless sensor network routing algorithm is proposed. The algorithm obtains optimization routing paths using global information of wireless sensor network. And the optimizing process can be reproduced in distribution by constructing a neural network for each node. Simulation results show the algorithm can accomplish routing process correctly and rapidly, and increase network lifetime evidently.
This paper studies a multi-cluster sensor network which is applied for source extraction in a sensing field. Both the performance of source extraction and the total energy consumption in the sensor network are functions of the number of clusters. In this paper, we aim at finding the optimal number of clusters by minimizing the effective energy consumption which is defined as the ratio of the performance of source extraction to the total energy consumption in the sensor network. A particle swarm optimization (PSO) algorithm is employed to form the clusters which enables every cluster to perform source extraction. The existence and the uniqueness of the optimum number of clusters is proven theoretically and shown by numerical simulations. The relationship between the optimum number of clusters and the various system parameters are investigated. A tradeoff between the performance and the total energy consumption is illustrated. The results show that the performance is greatly improved by adopting the multi-cluster structure of the sensor network.
The one type of routing in ad hoc and sensor networks that currently appears to be most amenable to algorithmic analysis is geographic routing. This paper contains an introduction to the problem field of geographic routing, presents a specific routing algorithm based on a synthesis of the greedy forwarding and face routing approaches, and provides an algorithmic analysis of the presented algorithm from both a worst-case and an average-case perspective.
Research on Wireless Sensor Networks has often assumed homogeneous nodes. In reality, homogeneous nodes have different capabilities like different levels of initial energy and drain rate. This leads to the research on heterogeneous networks where two or more types of nodes are considered within the network and the more powerful sensor nodes act as cluster heads. In this paper, we have analyzed a heterogeneous network with three types of nodes having different initial energy levels. A single hop clustering topology has been assumed and analyzed the network performance in terms of lifetime. Simulation results show that the network lifetime is much better in proposed protocol than the existing protocols.
It is well known that a packet loss in 802.11 can happen either due to collision or an insufficiently strong signal. However, discerning the exact cause of a packet loss, once it occurs, is known to be quite difficult. In this paper we take a fresh look at this problem of wireless packet loss diagnosis for 802.11-based communication and propose a promising technique called COLLIE. COLLIE performs loss diagnosis by using newly designed metrics that examine error patterns within a physical-layer symbol in order to expose statistical differences between collision and weak signal based losses. We implement COLLIE through custom driver-level modifications in Linux and evaluate its performance experimentally. Our results demonstrate that it has an accuracy ranging between 60-95% while allowing a false positive rate of up to 2%. We also demonstrate the use of COLLIE in subsequent link adaptations in both static and mobile wireless usage scenarios through measurements on regular laptops and the Netgear SPH101 Voice-over-WiFi phone. In these experiments, COLLIE led to throughput improvements of 20- 60% and reduced retransmission related costs by 40% depending upon the channel conditions.
There has been a growing interest in the applications of sensor networks. Since sensors are generally constrained in on-board energy supply, efficient management of the network is crucial in extending the life of the sensor. We present a novel approach for energy-aware and context-aware routing of sensor data. The approach calls for network clustering and assigns a less-energy-constrained gateway node that acts as a centralized network 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. Simulation results demonstrate that our approach can achieve substantial energy saving.
Sensor webs consisting of nodes with limited battery power and wireless communications are deployed to collect useful information from the field. Gathering sensed information in an energy efficient manner is critical to operate the sensor network for a long period of time. In W. Heinzelman et al. (Proc. Hawaii Conf. on System Sci., 2000), a data collection problem is defined where, in a round of communication, each sensor node has a packet to be sent to the distant base station. If each node transmits its sensed data directly to the base station then it will deplete its power quickly. The LEACH protocol presented by W. Heinzelman et al. is an elegant solution where clusters are formed to fuse data before transmitting to the base station. By randomizing the cluster heads chosen to transmit to the base station, LEACH achieves a factor of 8 improvement compared to direct transmissions, as measured in terms of when nodes die. In this paper, we propose PEGASIS (power-efficient gathering in sensor information systems), a near optimal chain-based protocol that is an improvement over LEACH. In PEGASIS, each node communicates only with a close neighbor and takes turns transmitting to the base station, thus reducing the amount of energy spent per round. Simulation results show that PEGASIS performs better than LEACH by about 100 to 300% when 1%, 20%, 50%, and 100% of nodes die for different network sizes and topologies.
The recent interest in sensor networks has led to a number of routing schemes that use the limited resources available at sensor nodes more efficiently. These schemes typically try to find the minimum energy path to optimize energy usage at a node. In this paper we take the view that always using lowest energy paths may not be optimal from the point of view of network lifetime and long-term connectivity. To optimize these measures, we propose a new scheme called energy aware routing that uses sub-optimal paths occasionally to provide substantial gains. Simulation results are also presented that show increase in network lifetimes of up to 40% over comparable schemes like directed diffusion routing. Nodes also burn energy in a more equitable way across the network ensuring a more graceful degradation of service with time.
Recently, research interest has increased in the design, development, and deployment of mobile agent systems for high-level inference and surveillance in a wireless sensor network (WSN). Mobile agent systems employ migrating codes to facilitate flexible application re-tasking, local processing, and collaborative signal and information processing. This provides extra flexibility, as well as new capabilities to WSNs in contrast to the conventional WSN operations based on the client-server computing model. In this article we survey the potential applications of mobile agents in WSNs and discuss the key design issues for such applications. We decompose the agent design functionality into four components, that is, architecture, itinerary planning, middleware system design, and agent cooperation. This taxonomy covers low-level to high-level design issues and facilitates the creation of a component-based and efficient mobile agent system for a wide range of applications. With a different realization for each design component, it is expected that flexible trade-offs (e.g., between energy and delay) can be achieved according to specific application requirements.
Wireless sensor networks that operate on batteries have limited network lifetime. There have been extensive recent research efforts on how to design protocols and algorithms to prolong network lifetime. However, due to energy constraint, even under the most efficient protocols and algorithms, the network lifetime may still be unable to meet the mission's requirements. In this paper, we consider the energy provisioning (EP) problem for a two-tiered wireless sensor network. In addition to provisioning additional energy on the existing nodes, we also consider deploying relay nodes (RNs) into the network to mitigate network geometric deficiencies and prolong network lifetime. We formulate the joint problem of EP and RN placement (EP-RNP) into a mixed-integer nonlinear programming (MINLP) problem. Since an MINLP problem is NP-hard in general, and even state-of-the-art software and techniques are unable to offer satisfactory solutions, we develop a heuristic algorithm, called Smart Pairing and INtelligent Disc Search (SPINDS), to address this problem. We show a number of novel algorithmic design techniques in the design of SPINDS that effectively transform a complex MINLP problem into a linear programming (LP) problem without losing critical points in its search space. Through numerical results, we show that SPINDS offers a very attractive solution and some important insights to the EP-RNP problem.
We define and study capacity regions for wireless ad hoc networks with an arbitrary number of nodes and topology. These regions describe the set of achievable rate combinations between all source-destination pairs in the network under various transmission strategies, such as variable-rate transmission, single-hop or multihop routing, power control, and successive interference cancellation (SIC). Multihop cellular networks and networks with energy constraints are studied as special cases. With slight modifications, the developed formulation can handle node mobility and time-varying flat-fading channels. Numerical results indicate that multihop routing, the ability for concurrent transmissions, and SIC significantly increase the capacity of ad hoc and multihop cellular networks. On the other hand, gains from power control are significant only when variable-rate transmission is not used. Also, time-varying flat-fading and node mobility actually improve the capacity. Finally, multihop routing greatly improves the performance of energy-constraint networks.
The one type of routing in ad hoc and sensor networks that currently appears to be most amenable to algorithmic analysis is geographic routing. This paper contains an introduction to the problem field of geographic routing, presents a specific routing algorithm based on a synthesis of the greedy forwarding and face routing approaches, and provides an algorithmic analysis of the presented algorithm from both a worst-case and an average-case perspective.
We describe a distributed position-based network protocol
optimized for minimum energy consumption in mobile wireless networks
that support peer-to-peer communications. Given any number of randomly
deployed nodes over an area, we illustrate that a simple local
optimization scheme executed at each node guarantees strong connectivity
of the entire network and attains the global minimum energy solution for
stationary networks. Due to its localized nature, this protocol proves
to be self-reconfiguring and stays close to the minimum energy solution
when applied to mobile networks. Simulation results are used to verify
the performance of the protocol
Wireless sensor networks could advance many scientific pursuits while providing a vehicle for enhancing various forms of productivity, including manufacturing, agriculture, construction, and transportation.
This paper presents the expected transmission count metric (ETX), which finds high-throughput paths on multi-hop wireless networks. ETX minimizes the expected total number of packet transmissions (including retransmissions) required to successfully deliver a packet to the ultimate destination. The ETX metric incorporates the effects of link loss ratios, asymmetry in the loss ratios between the two directions of each link, and interference among the successive links of a path. In contrast, the minimum hop-count metric chooses arbitrarily among the different paths of the same minimum length, regardless of the often large differences in throughput among those paths, and ignoring the possibility that a longer path might offer higher throughput.
Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specification: Higher Speed Physical Layer (PHY) Extension in the 2.4 GHz Band
IEEE Standard 802.11, "Wireless LAN Medium
Access Control (MAC) and Physical Layer
(PHY) Specification: Higher Speed Physical
Layer (PHY) Extension in the 2.4 GHz Band,"
IEEE Standard for Information Technology-Telecommunications and Information Exchange
between Systems-Local and Metropolitan Area
Networks-Specific Requirements-Part 11, 1999.
A Two-Tier Data Dissemination Model for Large-Scale Wireless Sensor Networks
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