Optimized Energy Scheduling Algorithm for Energy Efficient Wireless Sensor Networks

Authors: S. Arun Rajan, S. Bhavani

Abstract:

Wireless sensor networks can be tiny, low cost, intelligent sensors connected with advanced communication systems. WSNs have pulled in significant consideration as a matter of fact that, industrial as well as medical solicitations employ these in monitoring targets, conservational observation, obstacle exposure, movement regulator etc. In these applications, sensor hubs are thickly sent in the unattended environment with little non-rechargeable batteries. This constraint requires energy-efficient systems to drag out the system lifetime. There are redundancies in data sent over the network. To overcome this, multiple virtual spine scheduling has been presented. Such networks problems are called Maximum Lifetime Backbone Scheduling (MLBS) problems. Though this sleep wake cycle reduces radio usage, improvement can be made in the path in which the group heads stay selected. Cluster head selection with emphasis on geometrical relation of the system will enhance the load sharing among the nodes. Also the data are analyzed to reduce redundant transmission. Multi-hop communication will facilitate lighter loads on the network.

Keywords: WSN, wireless sensor networks, MLBS, maximum lifetime backbone scheduling.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1129129

References:

[1] C.-T. Cheng, C. K. Tse, and F. C. Lau, "A clustering algorithm for wireless sensor networks based on social insect colonies," Sensors Journal, IEEE, vol. 11, pp. 711-721, 2011.
[2] Y. Liao, H. Qi, and W. Li, "Load-balanced clustering algorithm with distributed self-organization for wireless sensor networks," Sensors Journal, IEEE, vol. 13, pp. 1498-1506, 2013.
[3] T. Ankit and K. Ketan, "Cluster Head Election for Energy and Delay Constraint Applications of Wireless Sensor Network," IEEE Sensors Journal, vol. 14, pp. 2658 - 2664, Aug. 2014
[4] P. Yaxiong Zhao, “On Maximizing the Lifetime of Wireless Sensor Network Using Virtual Backbone Scheduling,” IEEE Trans . Parallel Distributed Systems, vol. 23, no. 8, pp.567-650, Aug 2012.
[5] R. Cohen and B. Kapchits, “An Optimal Wake-Up Scheduling Algorithm for Minimizing Energy Consumption while Limiting Maximum Delay in a Mesh Sensor Network,” IEEE/ACM Trans. Networking, vol. 17,no.2,pp. 570-581,Apr. 2009.
[6] Vuran, Mehmet C.; Akyildiz, I.F. "XLP: A Cross-Layer Protocol for Efficient Communication in Wireless Sensor Networks", Mobile Computing, IEEE Transactions on, on page(s): 1578 - 1591 Volume: 9, Issue: 11, Nov. 2010.
[7] Ozgovde, A.; Ersoy, C. "WCOT: A Realistic Lifetime Metric for the Performance Evaluation of Wireless Sensor Networks", Personal, Indoor and Mobile Radio Communications, 2007. PIMRC 2007. IEEE 18th International Symposium on, on page(s): 1 – 5.