Hetrogeneous Multi-Deployment Strategy Effect on Maximizing the Lifetime Routing in Wireless Sensor Network

In the last few years, a significant increasing interest in the Wireless Sensor Networks (WSN) is noticed. A great challenge in WSN is the limitation of power in sensor nodes batteries, hence developing energy efficient solutions is a key issue for prolonging the lifetime of these networks. CMAX and OML are power efficient routing heuristics that have been proposed to maximize sensor networks lifetime. All the researches that evaluate these two heuristics, agreed on the superiority of OML over CMAX heuristic. In this work, in order to better represent real life terrains, four different types of single distributions were studied. In three-dimensional (3D) space, those distributions (Uniform, Poisson, Normal and Chi-square) were used to generate a Directed Acyclic Graph (DAG) to simulate the connectivity of random deployed WSN. For simulating Heterogeneous environments, 2-Hetroand 4-Hetro-Distributions were implemented. Results of 2-Hetro-Distributions revealed the superiority of OML over CMAX heuristic in most of the cases. But unlike previous researches, slight improvement was shown by CMAX over OML when Chi-square_Normal (CN) distribution is used, with improvement ratio more than 7%. Also, improvement in the average lifetime equals to 38.63% is provided by CMAX when sensor nodes were deployed in a Chi-square_Poisson (CP) terrain. In 4-Hetro-Distributions, the best case for applying OML heuristic is noticed at the Normal_Poisson_Chi-square_Uniform distribution (NPCU) with improvement ratio up to 99.82% over CMAX. Results of Chi-square_Poisson_Normal_Uniform (CPNU) distribution pointed out that CMAX heuristic is providing better average lifetime than OML heuristic, with unexpected improvement ratio up to 65.48%. As evident by the results of this work, it is proven that Heterogeneity of real life terrains (i.e. multi-tone terrain changes) has a major effect on the lifetime routing in Wireless Sensor Networks (WSN).