CWSC: Connected k-coverage working sets construction algorithm in wireless sensor networks

Yu, Jiguo; Deng, Xiu; Yu, Dongxiao; Wang, Guanghui; Gu, Xuemai

doi:10.1016/j.aeue.2013.05.004

Cited by 19 publications

(8 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Thus it is important to maintain a certain degree of redundancy in a CDS. The requirements of kcoverage take care of the fault-tolerance and robustness of dominatees, which ensure that every dominatee has atleast k adjacent dominator neighbors [7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Connected k-Coverage Topology Control for Area Monitoring in Wireless Sensor Networks

Ramalakshmi

Shanmugasundaram

2015

Wireless Pers Commun

View full text Add to dashboard Cite

One of the design challenges in Wireless sensor network (WSN) is to save limited energy resource to prolong the lifetime of the network without affecting their communication connectivity or sensing coverage. In dense WSN, the sensing areas of sensor node may overlap with each other. In general, the larger the overlap of the sensing range, the more redundant data will be generated with more energy consumption. In WSN, connected dominating set (CDS) has been used for energy efficient topology control, where a virtual backbone is formed, which allows communication between any arbitrary pair of nodes in the network. Nodes which are not in CDS can go to sleep state for energy conservation. Applications related to security and reliability require a certain amount of active nodes to ensure desired level of coverage at all time. These active nodes should be connected to reduce the delay during the communication. Therefore, it is necessary to construct a fault-tolerant CDS that continues to function during node or link failure, for both coverage and connectivity requirements of WSN. In this paper, we propose k-coverage connected dominating set (k-CCDS) for connected area coverage. We also propose a weight metric named weighted coverage cost (WCC), which consists of energy of sensing neighbors. The proposed protocol selects a CDS based on WCC to ensure that every nondominating node is connected with the CDS even if k À 1 dominating nodes are dead. This CDS is named k-CCDS, in which every non-dominating node is covered by atleast k dominating nodes. Simulation results show that it performs better when comparing with A3Cov in terms of CDS size, coverage, energy consumption and lifetime of the network.

show abstract

Section: Introductionmentioning

confidence: 99%

Connected k-Coverage Topology Control for Area Monitoring in Wireless Sensor Networks

Ramalakshmi

Shanmugasundaram

2015

Wireless Pers Commun

View full text Add to dashboard Cite

show abstract

“…Graph is widely used to model data in various applications [1][2][3][4][5][6][7]. With the rapid growth of emerging applications like social network analysis, semantic Web analysis, bioinformatics network analysis, and Internet of Things, it is urgent to require the processing capability on large scale graphs with billions of vertices [8][9][10][11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Optimal Representation of Large-Scale Graph Data Based on K2-Tree

Chang

Zeng

Wang

et al. 2017

Wireless Pers Commun

View full text Add to dashboard Cite

Graph is widely used to model data in various applications. With the rapid growth of many emerging applications such as Internet of Things, it is urgent to require the processing capability on large scale graphs with billions of vertices. Web graph is a typical case of graph data that is widely used for analyzing the structure, behavior and evolution of the World Wide Web. In this paper, we focus on optimal representation of large-scale Web graphs. Our work is motivated by the need of fit large-scale graphs into the main memory and carry out analyze on them. By analyzing the adjacency matrix of Web graphs, we find two characteristics on the distribution of 1s in the matrix. Firstly, only a very small proportion of elements in the matrix are 1s. Secondly, majority of 1s gather around the principal diagonal and form a few number of clusters in the matrix. Based on these characteristics, we first develop a clustering mechanism to locate the clusters of 1s in the adjacency matrix. Then, we combine this clustering mechanism with a structure named K 2 -tree and propose an approach for representing large-scale Web graphs compactly. Basic idea of the approach is trying to compress a large number of zeros as a single zero. Experimental results show that, our approach not only reduces the space for representing a Web graph, but also reduces the time consumption for operations such as retrieving neighbors of any nodes on the graph; compared with existing approaches, our approach achieves the best space/time tradeoff.

show abstract

“…The authors of [30] proposed a multiobjective hybrid optimization algorithm to solve the dynamic coverage and connectivity problem (DCCP) in flat WSNs. In [31], an algorithm based on Euclidean distance called CWSC is proposed to k-cover the sensing region while minimizing the number of working sensors. The goal of the research presented in [32] is addressing the network lifetime maximization problem with connectivity and coverage constraints by scheduling the activity of sensors.…”

Section: Related Workmentioning

confidence: 99%

Multiobjective Optimization for Topology and Coverage Control in Wireless Sensor Networks

Jameii

Faez

Dehghan

2015

International Journal of Distributed Sensor Networks

View full text Add to dashboard Cite

Coverage, connectivity, and network lifetime are important issues in wireless sensor networks (WSNs). Balancing the energy consumption in the network, reducing the transmission range of nodes, and density control of active nodes are approaches to extend the network lifetime. However, transmission range reduction and smaller number of active nodes can affect the network topology and may cause the network to be disconnected. So, there exist conflicts among lifetime, coverage, and connectivity. In this paper, these conflicting issues are considered and an evolutionary multiobjective optimization approach based on nondominated sorting genetic algorithm-II (NSGA-II) is proposed to optimize them. Simulation results demonstrate that the proposed algorithm can improve the network lifetime and coverage while maintaining the network connectivity.

show abstract

CWSC: Connected k-coverage working sets construction algorithm in wireless sensor networks

Cited by 19 publications

References 7 publications

Connected k-Coverage Topology Control for Area Monitoring in Wireless Sensor Networks

Connected k-Coverage Topology Control for Area Monitoring in Wireless Sensor Networks

Optimal Representation of Large-Scale Graph Data Based on K2-Tree

Multiobjective Optimization for Topology and Coverage Control in Wireless Sensor Networks

Contact Info

Product

Resources

About