Balanced Multicast Routing Performance in Autonomous Sensor Networks
Advances in Networks
Volume 4, Issue 2, November 2016, Pages: 21-33
Received: Oct. 11, 2016; Accepted: Nov. 2, 2016; Published: Dec. 21, 2016
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Authors
Abdelrahman S. Halawa, Systems and Computers Department, Faculty of Engineering, Al-Azhar University, Cairo, Egypt
Salah M. Abdel-Mageid, Systems and Computers Department, Faculty of Engineering, Al-Azhar University, Cairo, Egypt
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Abstract
Wireless sensor networks (WSNs) are almost autonomous and dynamic network consisting of a number of wireless nodes with limited energy. Accordingly, multicast routing protocols for WSNs encounter many challenges such as energy limitation, limited bandwidth, and self-configuration when producing multi-hop routes. Most existing multicast routing protocols are designed for ad hoc networks which maximize network throughput regardless energy consumption. However, multicast routing protocols for WSNs must consider the trade-off between minimizing energy consumption and maximizing network throughput. In this paper, balancing multicast routing metrics is considered for WSNs in which the route selection is based on nodes’ remaining energy and hop count metrics. In addition, the advisor node of a multicast group is periodically changed every predefined time interval to achieve more energy balancing., The performance of the proposed scheme is evaluated and compared with the existing multicast routing protocols using NS2 in terms of network lifetime, network throughput, packet delivery ratio, end-to-end delay and network control overhead which the impact of traffic load, node density, noise level, and mobility models are taken into account. The results show that the performance of the proposed scheme is better than the performance of existing schemes.
Keywords
Wireless Sensor Networks, Multicast Routing, Balanced Metrics, Node Energy, Hop Count, Network Lifetime
To cite this article
Abdelrahman S. Halawa, Salah M. Abdel-Mageid, Balanced Multicast Routing Performance in Autonomous Sensor Networks, Advances in Networks. Vol. 4, No. 2, 2016, pp. 21-33. doi: 10.11648/j.net.20160402.12
Copyright
Copyright © 2016 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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