The paper presents a technique called as Mobility-Enabled Multi Level Optimization (MeMLO) that addressing the existing problem of clustering in wireless sensor net-work (WSN). The technique enables selection of aggregator… Click to show full abstract
The paper presents a technique called as Mobility-Enabled Multi Level Optimization (MeMLO) that addressing the existing problem of clustering in wireless sensor net-work (WSN). The technique enables selection of aggregator node based on multiple optimization attribute which gives better decision capability to the clustering mechanism by choosing the best aggregator node. The outcome of the study shows MeMLO is highly capable of minimizing the halt time of mobile node that significantly lowers the transmit power of aggregator node. The simulation outcome shows negligible computational complexity, faster response time, and highly energy efficient for large scale WSN for longer simulation rounds as compared to conventional LEACH algorithm.
               
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