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Abstract
This work consider finding the best sink(s) location using different approaches to boost the network performance. It has three main directions. The first direction addresses the problem of deploying one sink node in homogenous WSNs. For small size problems, we propose a mixed Integer linear programing (MILP) formulation to find the best sink node location. For, large-scale size problems, we followed the genetic algorithms (GA) approach to be able to find a near optimal solution. We have considered using two objective functions, namely, minimizing the total number of hops and maximizing the link reliability. Experimental results shows that GA can find the optimal solution with a probability of 80% to 100%. The second direction addresses the problem of deploying multiple sink nodes in homogenous WSNs. Experimental results shows that GA can find the optimal solution with a probability of 60% to 100%. Finally, we consider the problem of deploying multiple sink nodes in heterogeneous WSNs. In heterogeneous WSNs, we have implemented two level hierarchy algorithm to deploy the sink nodes. In the first level: Modifications to a clustering algorithm called 2leader follower algorithm3 have been made and this new algorithm 2modified leader follower algorithm3 is used to cluster the network based on the difference in the characteristics of the sensor node. In the second level: The sink nodes are deployed such that the nodes{u2019} locations minimize the total number of hops. Results are compared to deploying random sink nodes with and without clustering