DocumentCode :
687493
Title :
A Multi-Objective Genetic Algorithm for constructing load-balanced virtual backbones in probabilistic Wireless Sensor Networks
Author :
Jing He ; Shouling Ji ; Beyah, Raheem ; Yingshu Li
Author_Institution :
Dept. of Comput. Sci., Kennesaw State Univ., Kennesaw, GA, USA
fYear :
2013
fDate :
9-13 Dec. 2013
Firstpage :
261
Lastpage :
266
Abstract :
A Connected Dominating Set (CDS) is used as a Virtual Backbone (VB) for efficient routing and broadcasting in Wireless Sensor Networks (WSNs). Currently, almost all existing works focus on constructing Minimum-sized CDS under the Deterministic Network Model (DNM). However, due to the existence of many probabilistic lossy links in WSNs, it is more practical to obtain a VB under the realistic Probabilistic Network Model (PNM). Moreover, load-balance factor cannot be neglected when constructing a VB to prolong network lifetime. Hence, in this paper, we propose a Multi-Objective Genetic Algorithm (MOGA) to construct a Load-Balanced Virtual Backbone under PNM (LBVBP). Through simulations, we demonstrate that our proposed methods extend network lifetime by 65% on average compared with the existing state-of-the-art approaches.
Keywords :
deterministic algorithms; genetic algorithms; probability; resource allocation; wireless sensor networks; connected dominating set; deterministic network model; load balanced virtual backbones; multiobjective genetic algorithm; probabilistic network model; probabilistic wireless sensor networks; Biological cells; Educational institutions; Wireless sensor networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Global Communications Conference (GLOBECOM), 2013 IEEE
Conference_Location :
Atlanta, GA
Type :
conf
DOI :
10.1109/GLOCOM.2013.6831081
Filename :
6831081
Link To Document :
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