Energy Efficient Differentiable Coverage Service Protocols for Wireless Sensor Networks

Sanli, H. Ozgur; Çam, Hasan

doi:10.1109/percomw.2005.31

Cited by 17 publications

(5 citation statements)

References 5 publications

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“…First, we propose a method of sensor node coverage by way of the coverage density. This method can lower the overlapping coverage [6] and solve the overlapping node located in nodes. Therefore, we research in the density of the sensor node scattering and also calculate the optimum number of sensor nodes.…”

Section: Coverage With Connectivity: Necessary and Sufficient Conditionsmentioning

confidence: 99%

A Coverage and Connectivity Method to Cluster Topology in Wireless Sensor Networks

Wang

2007

21st International Conference on Advanced Information Networking and Applications Workshops (AINAW'07)

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That is always an important topic to extend the whole lifetime in wireless network environment. How to make use of the consumption of the limited energy in the sensor nodes? How many sensor nodes can establish an optimum cluster? This paper proposes an optimum nodes number on clustering-based routing protocol called CCC (Coverage and Connectivity method to Cluster topology), which utilizes a node of its' optimum coverage and connectivity to transmit to another node and calculate the quantity of the nodes of an optimum cluster. In this article, the CCC, which is distributed the energy dissipation of sensor nodes and average energy savings. The performance of CCC is then compared to clustering-based schemes such as Low-Energy Adaptive Clustering Hierarchy (LEACH). Simulation results show that CCC improves network lifetime and reduces whole average of energy consumption.

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Section: Coverage With Connectivity: Necessary and Sufficient Conditionsmentioning

confidence: 99%

A Coverage and Connectivity Method to Cluster Topology in Wireless Sensor Networks

Wang

2007

21st International Conference on Advanced Information Networking and Applications Workshops (AINAW'07)

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“…Minimizing the battery and power expenditure and maximizing the network or sensor node lifetime has appeared as the primary and motivating concern in many developing architectures and transmission methods [6], [8], [11]- [14], [17], [18], [20], [21].…”

Section: Review Of Technical Literaturementioning

confidence: 99%

“…Research has also been done in managing bandwidth [2], [10], [ 13 ], [19] and network topology [ I 1], [20], [23 ]. One form of bandwidth control has been the scheduling of data aggregation events to minimize total power loss for each node.…”

Section: Review Of Technical Literaturementioning

confidence: 99%

A Comparison of Utility-Based Information Management Policies in Sensor Networks

Dhanani

Arseneau

Weatherton

et al. 2006

2006 IEEE Systems and Information Engineering Design Symposium

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We develop and compare the performance of two information management policies for wireless sensor networks. The first, sensor-centric utility-based (SCUB), is a distributed approach that instructs individual sensors to make their own decisions about what sensor information should be reported, based on a utility model for data. The second, resource manager (RM), is a consolidated approach that takes into account knowledge from all sensors before making decisions. We evaluate these policies through simulation in the context of dynamically deployed sensor networks in military scenarios. Our results show that both SCUB and RM yield longer lifetimes than cases where no policy is used. However, SCUB produces comparable lifetimes to RM while reporting significantly more data.

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“…Coverage is one of the most important issues in wireless sensor networks (WSNs), which is concerned with how well a specified area is monitored by sensors [Bai et al 2006;Cardei and zhu Du 2005;Dhillon et al 2002;Du and Lin 2005;Gallais et al 2007;Heo and Varshney 2004;Huang and Tseng 2005;Krishnamachari and Iyengar 2004;Kumar et al 2004Liu et al 2002;Lorincz and Welsh 2007;Megerian et al 2005;Sanli and Cam 2005;Sheu and Lin 2007;Sun et al 2005;Wan and Yi 2006;Zhang and Hou 2005a;Zou and Chakrabarty 2005]. Degree of coverage is often used as a measurement of the quality of service of WSNs.…”

Section: Introductionmentioning

confidence: 99%

Adaptive k -coverage contour evaluation and deployment in wireless sensor networks

Sheu

Chang

et al. 2013

ACM Trans. Sen. Netw.

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The problem of coverage is a fundamental issue in wireless sensor networks. In this article, we consider two subproblems: k-coverage contour evaluation and k-coverage rate deployment. The former aims to evaluate, up to k, the coverage level of any location inside a monitored area, while the latter aims to determine the locations of a given set of sensors to guarantee the maximum increment of k-coverage rate when they are deployed into the area. For the k-coverage contour evaluation problem, a nonuniform-grid-based approach is proposed. We prove that the computation cost of our approach is at most the square root of existing solutions. Based on our k-coverage contour evaluation scheme, a greedy k-coverage rate deployment scheme (k-CRD) is proposed, which is shown to be an order faster than existing studies for k-coverage rate deployment. The k-CRD can incorporate two different heuristics to further reduce its running time. Simulation results show that k-CRD with these heuristics can be significantly more time efficient without causing much degradation in the coverage rate of final deployment.

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Energy Efficient Differentiable Coverage Service Protocols for Wireless Sensor Networks

Cited by 17 publications

References 5 publications

A Coverage and Connectivity Method to Cluster Topology in Wireless Sensor Networks

A Coverage and Connectivity Method to Cluster Topology in Wireless Sensor Networks

A Comparison of Utility-Based Information Management Policies in Sensor Networks

Adaptive k -coverage contour evaluation and deployment in wireless sensor networks

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