CCAJS: A Novel Connect Coverage Algorithm Based on Joint Sensing Model for Wireless Sensor Networks

This paper discusses how to effectively guarantee the coverage and connectivity quality of wireless sensor networks when joint perception model is used for the nodes whose communication ranges are multi-level adjustable in the absence of position information. A Connect Coverage Algorithm Based on Joint Sensing model (CCAJS) is proposed, with which least working nodes are chosen based on probability model ensuring the coverage quality of the network. The algorithm can balance the position distribution of selected working nodes as far as possible, as well as reduce the overall energy consumption of the whole network. The simulation results show that, less working nodes are needed to ensure the coverage quality of networks using joint perception model than using the binary perception model. CCAJS can not only satisfy expected coverage quality and connectivity, but also decrease the energy consumption, thereby prolonging the network lifetime.

[1]  Yan Jin,et al.  ECCRA: An energy-efficient coverage and connectivity preserving routing algorithm under border effects in wireless sensor networks , 2008, Comput. Commun..

[2]  Zeyu Sun,et al.  A novel coverage algorithm based on event-probability-driven mechanism in wireless sensor network , 2014, EURASIP J. Wirel. Commun. Netw..

[3]  Sajal K. Das,et al.  Coverage and connectivity issues in wireless sensor networks: A survey , 2008, Pervasive Mob. Comput..

[4]  Songwu Lu,et al.  PEAS: a robust energy conserving protocol for long-lived sensor networks , 2002, 10th IEEE International Conference on Network Protocols, 2002. Proceedings..

[5]  Yu-Chee Tseng,et al.  $k$-Angle Object Coverage Problem in a Wireless Sensor Network , 2012, IEEE Sensors Journal.

[6]  Hai Liu,et al.  Maximal lifetime scheduling in sensor surveillance networks , 2005, Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies..

[7]  Ding-Zhu Du,et al.  Improving Wireless Sensor Network Lifetime through Power Aware Organization , 2005, Wirel. Networks.

[8]  Sajal K. Das,et al.  Centralized and Clustered k-Coverage Protocols for Wireless Sensor Networks , 2012, IEEE Transactions on Computers.

[9]  Siba K. Udgata,et al.  Sensor Deployment and Scheduling for Target Coverage Problem in Wireless Sensor Networks , 2014, IEEE Sensors Journal.

[10]  Di Tian,et al.  A coverage-preserving node scheduling scheme for large wireless sensor networks , 2002, WSNA '02.

[11]  Hui Liu,et al.  Maximizing the Lifetime of $k$-Discrete Barrier Coverage Using Mobile Sensors , 2013, IEEE Sensors Journal.

[12]  Himanshu Gupta,et al.  Connected sensor cover: self-organization of sensor networks for efficient query execution , 2003, IEEE/ACM Transactions on Networking.

[13]  Yang Xiao,et al.  Lightweight Deployment-Aware Scheduling for Wireless Sensor Networks , 2005, Mob. Networks Appl..

[14]  Yang Xiao,et al.  IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, PAPER ID: TPDS-0307-0605.R1 1 Random Coverage with Guaranteed Connectivity: Joint Scheduling for Wireless Sensor Networks , 2022 .

[15]  Dharma P. Agrawal,et al.  Coverage and Lifetime Optimization of Wireless Sensor Networks with Gaussian Distribution , 2008, IEEE Transactions on Mobile Computing.

[16]  Yunhao Liu,et al.  CitySee: not only a wireless sensor network , 2013, IEEE Network.

[17]  Li Zengzhi.  Useful Lifetime Maximization for Partial Coverage Conserve in Wireless Sensor Networks , 2009 .

[18]  Panayiotis Kotzanikolaou,et al.  Solving coverage problems in wireless sensor networks using cover sets , 2010, Ad Hoc Networks.

[19]  Ju-Jang Lee,et al.  A Bipopulation-Based Evolutionary Algorithm for Solving Full Area Coverage Problems , 2013, IEEE Sensors Journal.

[20]  Li Xiao,et al.  An Adaptive Partitioning Scheme for Sleep Scheduling and Topology Control in Wireless Sensor Networks , 2009, IEEE Transactions on Parallel and Distributed Systems.

[21]  Qun Zhao,et al.  Lifetime Maximization for Connected Target Coverage in Wireless Sensor Networks , 2008, IEEE/ACM Transactions on Networking.

[22]  Krishnendu Chakrabarty,et al.  A distributed coverage- and connectivity-centric technique for selecting active nodes in wireless sensor networks , 2005, IEEE Transactions on Computers.

[23]  Yunhao Liu,et al.  Does Wireless Sensor Network Scale? A Measurement Study on GreenOrbs , 2011, IEEE Transactions on Parallel and Distributed Systems.

[24]  Abdelhamid Mellouk,et al.  An Evidence-Based Sensor Coverage Model , 2012, IEEE Communications Letters.

[25]  Zeyu Sun,et al.  Research on Localization Algorithm Based on Improved Bayesian Filtering Model , 2015 .

[26]  Jie Li,et al.  Collaborative Target Tracking in Wireless Sensor Networks , 2014, Ad Hoc Sens. Wirel. Networks.

[27]  Jie Li,et al.  Polytype target coverage scheme for heterogeneous wireless sensor networks using linear programming , 2014, Wirel. Commun. Mob. Comput..

[28]  Lui Sha,et al.  Design and analysis of an MST-based topology control algorithm , 2003, IEEE Transactions on Wireless Communications.