K-means clustering-based WSN protocol for energy efficiency improvement

Abstract

Since it is very difficult to replace or recharge the batteries of the sensor nodes in the wireless sensor network (WSN), efficient use of the batteries of the sensor nodes is a very important issue. This has a deep relationship with the lifetime of the network. If the node's energy is exhausted, the node is no longer available. If a certain number of nodes (50% or 80%) in a network consumes energy completely, the whole network will not work. Therefore, various protocols have been proposed to maintain the network for a long time by minimizing energy consumption. In recent years, a protocol using a K-means clustering algorithm, one of machine learning techniques, has been proposed. A KCED protocol is proposed in consideration of residual energy of a node, a cluster center, and a distance to a base station in order to improve a problem of a protocol using K-average gung zipper algorithm such as cluster center consideration.