SRA: A Sensing Radius Adaptation Mechanism for Maximizing Network Lifetime in WSNs

Coverage is an important issue that has been widely discussed in wireless sensor networks (WSNs). However, it is still a big challenge to achieve both purposes of full coverage and energy balance. This paper considers the area coverage problem for a WSN in which each sensor has a variable sensing radius. To prolong the network lifetime, a weighted Voronoi diagram (WVD) is proposed as a tool for determining the responsible sensing region of each sensor according to the remaining energy in a distributed manner. The proposed mechanism, which is called sensing radius adaptation (SRA), mainly consists of three phases. In the first phase, each sensor and its neighboring nodes cooperatively construct the WVD to identify the responsible monitoring area. In the second phase, each sensor adjusts its sensing radius to reduce the overlapping sensing region such that the purpose of energy conservation can be achieved. In the last phase, the sensor with the least remaining energy further adjusts its sensing radius with its neighbor for to maximize the network lifetime. Performance evaluation and analysis reveal that the proposed SRA mechanism outperforms the existing studies in terms of the network lifetime and the degree of energy balance.

[1]  Ossama Younis,et al.  ROC: Resilient Online Coverage for Surveillance Applications , 2011, IEEE/ACM Transactions on Networking.

[2]  Thomas F. La Porta,et al.  Sensor activation and radius adaptation (SARA) in heterogeneous sensor networks , 2012, TOSN.

[3]  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 .

[4]  Sirisha Medidi,et al.  Energy-Efficient k-Coverage for Wireless Sensor Networks with Variable Sensing Radii , 2009, GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference.

[5]  Erik Frisk,et al.  Sensor Placement for Fault Diagnosis , 2008, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[6]  Ai Chen,et al.  Designing localized algorithms for barrier coverage , 2007, MobiCom '07.

[7]  Minglu Li,et al.  Reliable Anchor-Based Sensor Localization in Irregular Areas , 2010, IEEE Transactions on Mobile Computing.

[8]  Wei Wang,et al.  Coverage for target localization in wireless sensor networks , 2006, 2006 5th International Conference on Information Processing in Sensor Networks.

[9]  Peter Desnoyers,et al.  Exact distributed Voronoi cell computation in sensor networks , 2007, IPSN.

[10]  Jiming Chen,et al.  Energy-Efficient Probabilistic Area Coverage in Wireless Sensor Networks , 2015, IEEE Transactions on Vehicular Technology.

[11]  Chih-Yung Chang,et al.  An energy-balanced swept-coverage mechanism for mobile WSNs , 2013, Wirel. Networks.

[12]  Raj Jain,et al.  A Quantitative Measure Of Fairness And Discrimination For Resource Allocation In Shared Computer Systems , 1998, ArXiv.

[13]  Weijia Jia,et al.  Optimal Deployment Patterns for Full Coverage and $k$-Connectivity $(k \leq 6)$ Wireless Sensor Networks , 2010, IEEE/ACM Transactions on Networking.

[14]  Hewijin Christine Jiau,et al.  Localization with mobile anchor points in wireless sensor networks , 2005, IEEE Transactions on Vehicular Technology.

[15]  Weili Wu,et al.  Energy-efficient target coverage in wireless sensor networks , 2005, Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies..

[16]  Yingshu Li,et al.  Delaunay-triangulation based complete coverage in wireless sensor networks , 2009, 2009 IEEE International Conference on Pervasive Computing and Communications.

[17]  Chih-Yung Chang,et al.  Patrolling Mechanisms for Disconnected Targets in Wireless Mobile Data Mules Networks , 2011, 2011 International Conference on Parallel Processing.

[18]  Chih-Yung Chang,et al.  The k-barrier coverage mechanism in Wireless Visual Sensor Networks , 2012, 2012 IEEE Wireless Communications and Networking Conference (WCNC).

[19]  Sirisha Medidi,et al.  Energy Efficient Coverage with Variable Sensing Radii in Wireless Sensor Networks , 2007, Third IEEE International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob 2007).

[20]  Jang-Ping Sheu,et al.  Distributed Localization Scheme for Mobile Sensor Networks , 2010, IEEE Transactions on Mobile Computing.

[21]  Miao Pan,et al.  Maximum Lifetime Scheduling for Target Coverage and Data Collection in Wireless Sensor Networks , 2015, IEEE Transactions on Vehicular Technology.

[22]  Jie Wu,et al.  Maximum network lifetime in wireless sensor networks with adjustable sensing ranges , 2005, WiMob'2005), IEEE International Conference on Wireless And Mobile Computing, Networking And Communications, 2005..

[23]  Shuigeng Zhou,et al.  Distributed Localization Using a Moving Beacon in Wireless Sensor Networks , 2008, IEEE Transactions on Parallel and Distributed Systems.

[24]  Yunhao Liu,et al.  Sweep coverage with mobile sensors , 2008, 2008 IEEE International Symposium on Parallel and Distributed Processing.

[25]  Xiang-Yang Li,et al.  Minimum-energy broadcast routing in static ad hoc wireless networks , 2001, Proceedings IEEE INFOCOM 2001. Conference on Computer Communications. Twentieth Annual Joint Conference of the IEEE Computer and Communications Society (Cat. No.01CH37213).

[26]  Bhaskar Krishnamachari,et al.  Energy-Quality Tradeoffs for Target Tracking in Wireless Sensor Networks , 2003, IPSN.