Energy optimization in WSNs using Successive Addition and Successive Reduction Methods

Power optimization is an important issue in wireless sensor networks, the objective of this research is to design and implement algorithms to optimize the power consumption for the network. Two methods have been proposed in this study. The first method is the Successive Addition Method, SAM, where the algorithm tries to build the operational sensor sets by incrementally adding sensors. The second is the Successive Reduction Method, SRM, where the algorithm removes sensors that have the largest overlap with other sensors in the set. The results of simulation showed that the two algorithms are able to choose the optimum sets and achieve the required levels of area coverage for the optimum total time. It is observed that the SAM outperforms the SRM at lower target coverage. However, the SRM's performance improves when the target coverage is higher.