Unequal clustering and scheduling in Wireless Sensor Network using Advance Genetic Algorithm

Duo to limited energy of the sensor nodes which forming the wireless sensor network (WSN), and almost deployed in harsh environment, therefore it is very important to minimize the consumption of the sensor node's energy. For this reasons designing an energy efficient clustering and scheduling of sensor nodes considered the most efficient methods for extending the WSN's lifetime. In this paper, we have proposed Genetic algorithm based methods for clustering and scheduling. The proposed methods have two stages; in the first stage GA is used for cluster formation where the chromosome is represented by using the sensor node's position. While in the second stage GA is used for selecting a minimum number of nodes while maintaining the full coverage and the connectivity of the selected nodes. The simulation result shows that the proposed algorithm (AGA) is more efficient than the existent algorithms in terms of number of first node die per round, number of a live nodes, and energy consumption.