Energy Constrained Routing Algorithm for Wireless Networks

K. Kaushik¹ , B. Bhushan² , R. Sharma³

Section:Research Paper, Product Type: Isroset-Journal
Vol.5 , Issue.2 , pp.33-35, Apr-2017

Online published on Apr 30, 2017

Copyright © K. Kaushik, B. Bhushan, R. Sharma . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

View this paper at   Google Scholar | DPI Digital Library

XML View     PDF Download

How to Cite this Paper

Abstract :
The aim of following paper is to introduce an Energy Constrained Routing algorithm for wireless network to enhance the performance of network. The following schemes PECE there are two stages cluster formation and stable data transfer. In stage one we used an energy saving clustering routing algorithm based on degree of the nodes, left energy and relative distance between nodes. Whereas in stage two where we used BCO (Bee Colony Optimization). On these basis of considering a precise definition of the route from source node to sink node. This algorithm helps in reducing energy consumption and increases the survival time.

Key-Words / Index Term :
Wireless Network, SI, Algorithm, Agents

References :
[1] DG Zhang, “Design and implementation of embedded un-interruptible power supply system (EUPSS) for web based mobile application”, Enterprise Information System, Vol.6, Issue.4, pp.473–489, 2012.
[2] D. Zhang, K. Zheng, T. Zhang, X. Wang, “A novel multicast routing method with minimum transmission for WSN of cloud computing service”, Soft Computing, Vol.19, Issue.7, pp.1817–1827, 2015.
[3] GQ Zheng., “The research process of MAC protocol of WSN”. Acta Automatic Sinica, Vol.4, Issue.3, pp. 305–316, 2008.
[4] A. Rana, M. Bala, Varsha , “Review Paper on MSEEC: Energy Efficient Clustering Protocol in HWSN”, International Journal of Computer Sciences and Engineering, Vol.4, Issue.5, pp.71-75, 2016.
[5] J Kennedy, “Particle swarm optimization”, Proceeding of IEEE International Conference Neural Networks, Vol.4, Issue.1, pp.1942–1947, 1995.
[6] GG Llinas, “Network and QoS-based selection of complementary services”, IEEE Transcation Services Computer, Vol.8, Issue.1, pp.79–91, 2015.
[7] DG Zhang, “A new approach and system for attentive mobile learning based on seamless migration”, Applied Intelligence, Vol.36, Issue.1, pp.75–89, 2012.
[8] S. Stanislava, “Cluster head election techniques for coverage preservation in wireless sensor networks”, Ad-Hoc Network, Vol.5, Issue.7, pp.955–972, 2009
[9] H. javedan, G. Shahmohammadi, “Presenting a Method for Efficient Energy Consumption in Wireless Sensor Networks Using the Topology control and Fuzzy Systems”, International Journal of Computer Sciences and Engineering, Vol.4, Issue.2, pp.1-12, 2016.
[10] DG Zhang, “Novel Quick Start (QS) Method for Optimization of TCP”, Wireless Networks, Vol.22, Issue.1, pp 211–222, 2016.
[11] Uruj Fatma Siddiqui, Raj Gaurang Tiwari and Pankaj Kumar, “A Review of Improvement on LEACH Protocol in Wireless Sensor Network”, International Journal of Computer Sciences and Engineering, Vol.3, Issue.8, pp.26-31, 2015.
[12] S Lindsey, “PEGASIS: power efficient gathering in sensor information systems”, IEEE Aerospace Conference, China, pp.1152–1130, 2002.