Distributed Algorithms for Maximizing Lifetime of WSNs with Heterogeneity and Adjustable Sensing Range for Different Deployment Strategies

Focus of this paper is on energy heterogeneity and distributed algorithms for scheduling and adjustable range. The problem of lifetime enhancement of wireless sensor networks is dealt with the adjustment of transmission or sensing range of the sensor nodes and implementation of heterogeneous energy model. In this work, we deploy the sensor nodes in 2-D using triangular, square, and hexagonal tiles. The initial energies of the sensors and their positions along with the positions of targets are known. For this environment, we investigate the maximum achievable lifetime using heterogeneous deterministic energy efficient protocol with adjustable sensing range (HADEEPS) and heterogeneous load balancing protocol with adjustable sensing range (HALBPS). We observe that deploying the sensors in triangular tiles gives better lifetime.

[1]  Jie Wu,et al.  Improving network lifetime using sensors with adjustable sensing ranges , 2006, Int. J. Sens. Networks.

[2]  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..

[3]  Piotr Berman,et al.  Power efficient monitoring management in sensor networks , 2004, 2004 IEEE Wireless Communications and Networking Conference (IEEE Cat. No.04TH8733).

[4]  Yingshu Li,et al.  Maximum Lifetime of Sensor Networks with Adjustable Sensing Range , 2006, Seventh ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD'06).

[5]  Sushil K. Prasad,et al.  Distributed Algorithms for Lifetime of Wireless Sensor Networks Based on Dependencies Among Cover Sets , 2007, HiPC.

[6]  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..

[7]  Lili Zhang,et al.  An Effective Data Gathering Scheme in Heterogeneous Energy Wireless Sensor Networks , 2009, 2009 International Conference on Computational Science and Engineering.

[8]  Galen H. Sasaki,et al.  Wireless sensor placement for reliable and efficient data collection , 2003, 36th Annual Hawaii International Conference on System Sciences, 2003. Proceedings of the.

[9]  Sushil K. Prasad,et al.  A distributed algorithmic framework for coverage problems in Wireless Sensor Networks , 2008, IPDPS.

[10]  Jia-Shung Wang,et al.  Energy-efficient probabilistic target coverage in wireless sensor networks , 2011, 2011 17th IEEE International Conference on Networks.

[11]  Sushil K. Prasad,et al.  Distributed algorithms for maximizing the lifetime of wireless sensor networks , 2009 .

[12]  Alex Zelikovsky,et al.  DEEPS: Deterministic Energy-Efficient Protocol for Sensor networks , 2006, Seventh ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD'06).

[13]  Sushil K. Prasad,et al.  Energy efficient distributed algorithms for sensor target coverage based on properties of an optimal schedule , 2008, HiPC'08.

[14]  Jun Lu,et al.  Coverage-aware self-scheduling in sensor networks , 2003, 2002 14th International Conference on Ion Implantation Technology Proceedings (IEEE Cat. No.02EX505).

[15]  R. B. Patel,et al.  EEHC: Energy efficient heterogeneous clustered scheme for wireless sensor networks , 2009, Comput. Commun..

[16]  B. Bhargava,et al.  Energy-Efficient Routing Schemes for Wireless Sensor Networks , 2003 .

[17]  Dilip Kumar,et al.  EECHE: energy-efficient cluster head election protocol for heterogeneous wireless sensor networks , 2009, ICAC3 '09.

[18]  Bharat Bhargava,et al.  Energy-Efficient Routing Schemes for Sensor Networks , 2003 .