Testing and evaluating recommendation algorithms in internet of things

Technological revolution in communication and embedded computing has led to the Internet of Things (IoT) where all objects are connected together to provide users with services. Nowadays, many third party service providers are providing a large number of IoT services. Suggesting suitable services to IoT users based on objects they own has not been tackled yet. In this paper, we investigate the possibilities of leveraging recommendation algorithms, especially graph-based, to IoT. We propose a graph-based model for IoT systems and conduct experiment in which analyze and explore correlations between performances of different algorithms. We show that the graph-based recommendation algorithm can be used to develop an effective recommender system for the IoT. Moreover, we show that some algorithms perform reasonably well and produce high quality results.