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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 7 Issue 12, 2016.
Abstract: Wireless sensor network includes hundreds or thousands of nodes with limited energy. Since the lifetime of each sensor is as the battery life of the sensor, the energy issue is discussed as a fundamental challenge. In this article, parallel ant algorithm and exclusive territoriality algorithm have been used by providing the ability of nodes self-determination, in order to improve the parameters of energy consumption, extend the life and network coverage. For routing nodes also is used direct send method, sending by hierarchical clustering, along with carrier head cluster. This article is evaluated by focusing on network stability, based on two main factors: reduce energy consumption and extend the network life and increase network coverage. The simulated output in this paper represents an increase of energy consumption balance and network lifetime approach (the first death time) and network imperative life (the last death time), which represents network high-performance than latch, direct transmission and other methods. Therefore, also in this article the purpose is to provide a better way than previous methods based on developed ant algorithm to reduce energy consumption against hardware limitations.
Javad Mozaffari and Mehdi EffatParvar, “Reducing Energy Consumption in Wireless Sensor Networks using Ant Colony Algorithm and Autonomy Mechanisms” International Journal of Advanced Computer Science and Applications(IJACSA), 7(12), 2016. http://dx.doi.org/10.14569/IJACSA.2016.071214
@article{Mozaffari2016,
title = {Reducing Energy Consumption in Wireless Sensor Networks using Ant Colony Algorithm and Autonomy Mechanisms},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.071214},
url = {http://dx.doi.org/10.14569/IJACSA.2016.071214},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {12},
author = {Javad Mozaffari and Mehdi EffatParvar}
}
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.