Shuffled Frog Leaping Algorithm based Unequal Clustering Strategy for Wireless Sensor Networks

In energy-limited WSNs, coverage and connectivity are two of the most fundamental QoS issues, which have a great impact on the performance of WSNs for minimizing the node energy consumption and maximizing the network coverage lifetime. Due to the node distribution, the energy consumption among nodes is more imbalanced in cluster-based WSNs. Based on this problem, this paper proposes Sink Mobility based Energy Balancing Unequal Clustering protocol (SMEBUC) for WSNs with node distribution, which chooses the nodes with more energy as cluster heads and divides all nodes into clusters of different size through the improved Shuffled Frog Leaping Algorithm (SFLA). To reduce the cluster head replacement frequency, cluster head serves continuously to determine the cluster head exchange time and nodes weight. The greedy algorithm is adopted to select the optimal relay node between cluster head and Sink. To further reduce the energy consumption, mobile Sink routing is put forward to avoid the hot-spots. We evaluate and compare the performance of SMEBUC with LEACH and EBUCP, and the results show that SMEBUC achieves more energy savings, and energy balance.