ID3 and k-means Based Methodology for Internet of Things Device Classification
Joan Nolla Suarez, Ante Salcedo · 2017
The Internet of Things (IoT) brings the issue of connecting an immense amount of diverse devices. This vast diversity will present a challenge for communications, since it is not expected that all devices will follow the same rules and standards to communicate back and forth, due to the difficulty and inefficiency of developing a unique set rules and standards for each device. A classification of devices is needed, so rules and protocols of communications could be established among the different device categories, to deal with the diversity of the things to be interconnected. In this paper, a classification methodology using a clustering algorithm like k-means is proposed; as well as, a way to establish rules of classification using a decision tree implemented with the ID3 algorithm.