Regularity of movement based approach for M2M services discovery

In professional or home settings, the usage of Machine-to-Machine (M2M) technology is desired and often enforced for its ability to reduce the total cost and to expose ubiquitous networks services. However, due to the unpredictability of M2M network mobility, connection and disconnection, a lot of problems can attend services availability and cause path loss or change service selection parameters, making services discovery more difficult than ever. In this paper, we present an approach based on knowledge for ensuring discovery and invocation of available services. The approach firstly leverages semantic data from user regularity of movement by extracting knowledge jointly from the mobility data and underlying geographic domain information. Then, it analyzes those data in order to prepare a pre-planned list of available services ranked not only according to their relevance but also according to their degree of availability. To illustrate the feasibility of our approach, we adopt an illustrative scenario highlighting the importance of exploiting the daily life of a mobile user for service discovery enhancements.