Cluster Oriented Sensor Selection for Context-Aware Internet of Things Applications

Abstract

Internet of Things (IoT) paradigm has important role in sensor sensing, searching and related analytics. Now IoT is broadly used in different application domains based on user needs to support intelligent computing. These applications need context aware information for their particular requirement. But widely deployed sensors gives immense amount of data from which searching and finding required information is a cumbersome task. In context aware computing, searching and selection of most related and optimal sensors is crucial, because each user needs and usage is different. In this paper an approach for optimal selection of IoT sensors based on cluster and cluster head formation is proposed for faster and effective retrieval. The experimental evaluation shows that the proposed approach produces better result than traditional random clustering.