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DOI: 10.14569/IJARAI.2016.050505
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The Mobile Version of the Predicted Energy Efficient Bee-Inspired Routing (PEEBR)

Author 1: Imane M. A. Fahmy
Author 2: Hesham A. Hefny
Author 3: Laila Nassef

International Journal of Advanced Research in Artificial Intelligence(IJARAI), Volume 5 Issue 5, 2016.

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Abstract: In this paper, the previously proposed Predictive Energy Efficient Bee-inspired Routing (PEEBR) family of routing optimization algorithms based on the Artificial Bees Colony (ABC) Optimization model is extended from a random static mobility model, as employed by its first version (PEEBR-1), into a random mobility model in its second version (PEEBR-2). This random mobility model used by PEEBR-2 algorithm is proposed and described. Then, PEEBR-2’s was simulated in order to compare its performance relative to the first version (PEEBR-1) in terms of predicted optimal path energy consumption, nodes batteries residual power and fitness. The simulation results have shown that PEEBR-2’s optimal path is predicted to consume less energy and realizing higher fitness. On the other hand, PEEBR-1’s optimal paths nodes possess higher batteries residual power. At last, the impact of mobile nodes speeds was studied for PEEBR-2 in terms of optimal path’s predicted energy consumption and path nodes batteries residual power showing its performance stability relative to nodes mobility speed.

Keywords: PEEBR; PEEBR-1; PEEBR-2; Energy Efficient Routing; Bee-inspired; Artificial Bee Colony (ABC) optimization; Random Mobility Model

Imane M. A. Fahmy, Hesham A. Hefny and Laila Nassef, “The Mobile Version of the Predicted Energy Efficient Bee-Inspired Routing (PEEBR)” International Journal of Advanced Research in Artificial Intelligence(IJARAI), 5(5), 2016. http://dx.doi.org/10.14569/IJARAI.2016.050505

@article{Fahmy2016,
title = {The Mobile Version of the Predicted Energy Efficient Bee-Inspired Routing (PEEBR)},
journal = {International Journal of Advanced Research in Artificial Intelligence},
doi = {10.14569/IJARAI.2016.050505},
url = {http://dx.doi.org/10.14569/IJARAI.2016.050505},
year = {2016},
publisher = {The Science and Information Organization},
volume = {5},
number = {5},
author = {Imane M. A. Fahmy and Hesham A. Hefny and Laila Nassef}
}



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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