Semantic clustering in wireless sensor networks

Abstract

Wireless Sensor Networks have critical resource constraints and minimizing resources usage is crucial to extend the network lifetime. Energy saving in WSNs can be achieved through several techniques, such as topology control and clustering, to provide a longer lifetime and scalability to the network. In this paper we propose a semantic clustering model based on a fuzzy inference system to find out the semantic neighborhood relationships in the network. As a case study we describe the structural health monitoring domain application which has been used to illustrate and verify the proposed model.