Sensor Clustering and Base Station Mobilizing in Wireless Sensor Networks Using Genetic Algorithms

Wireless Sensor Networks (WSNs) are a set of nodes which are spatially distributed in an environment to fulfill some goals and collect their task related essential data in the surrounding area, store and process them and make them ready for a final cast. Regards to the fact that the size and the weight of these sensors are limited, the research for an optimal energy consumption pattern in these networks is indispensable. The proposed solution in this paper tries to quell the power hunger of the sensors, by clustering them, and finding the best position of the base station (BS) using the genetic algorithms. Notwithstanding the fact that, choosing the best cluster-heads and the best position of the BS has been always around as a big challenge; the dynamic nature of the problem as a consequence of the sequential changes in the coordinates of the cluster-heads in each iteration has also made the problem even more complicated, making it strongly impossible to implement with classic mathematical approaches. The simulation results in this paper, show that our strategy enhances the lifetime of the network in comparison with the immobile BS or non-clustering methods.