Energy-aware clustering method for cluster head selection to increasing lifetime in wireless sensor network

Energy-aware clustering method for cluster head selection to increasing lifetime in wireless sensor network

연구 분야: Infrastructure

학회: The Journal of Supercomputing

Wireless sensor network consists of many tiny sensors that can be a powerful tool for data collection in various environments. The optimal scenario for sensor networks is for all nodes to reach the end of their energy, together or through regular scheduling, to maximize the lifetime of network. Studies have shown that clustering helps conserve the limited energy resources of sensors. In this paper, an ink drop spread is used for clustering. Initially, ink drops are spread using the ink drop spread operator with a weight proportional to the energy of each node, and clustering as well as routing is performed based on it. Clustering is performed dynamically; in each round, clustering is redone, cluster heads are selected, and nodes with very low energy are marked as dead. Our proposed algorithm, EACM, is compared with the popular algorithms LEACH, PEGASIS, LEACH_EX, and the latest algorithms EECPK-means, RaCH, and C3HA. The proposed algorithm demonstrates an improvement in clustering quality, a reduction in node energy consumption, and an overall increase in the lifetime of network. On average, the proposed algorithm results in more active nodes within the network, with the remaining energy being at least 17% higher than that of the best existing algorithms.