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DOI: 10.14569/IJACSA.2016.070315
PDF

Energy Efficient Routing Protocol for Maximizing the Lifetime in Wsns Using Ant Colony Algorithm and Artificial Immune System

Author 1: Safaa Khudair Leabi
Author 2: Turki Younis Abdalla

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 7 Issue 3, 2016.

  • Abstract and Keywords
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Abstract: Energy limitations have become fundamental challenge for designing wireless sensor networks. Network lifetime represent the most important and interested metric. Several attempts have been made for efficient utilization of energy in routing techniques. This paper proposes an energy efficient routing technique for maximizing the networks lifetime called swarm intelligence routing. This is achieved by using ant colony algorithm (ACO) and artificial immune system (AIS). AIS is used for solving packet LOOP problem and to control route direction. While ACO algorithm is used for determining optimum route for sending data packets. The proposed routing technique seeks for determining the optimum route from nodes towards base station so that energy exhaustion is balanced and lifetime is maximized. Proposed routing technique is compared with Dijkstra routing method. Results show significant increase in network lifetime of about 1.2567.

Keywords: ant colony algorithm; artificial immune system; adaptive routing; network lifetime; wireless sensor networks

Safaa Khudair Leabi and Turki Younis Abdalla, “Energy Efficient Routing Protocol for Maximizing the Lifetime in Wsns Using Ant Colony Algorithm and Artificial Immune System” International Journal of Advanced Computer Science and Applications(IJACSA), 7(3), 2016. http://dx.doi.org/10.14569/IJACSA.2016.070315

@article{Leabi2016,
title = {Energy Efficient Routing Protocol for Maximizing the Lifetime in Wsns Using Ant Colony Algorithm and Artificial Immune System},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.070315},
url = {http://dx.doi.org/10.14569/IJACSA.2016.070315},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {3},
author = {Safaa Khudair Leabi and Turki Younis Abdalla}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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