A Context-Aware M2M-Based Middleware for Service Selection in Mobile Ad-Hoc Networks

This paper proposes a novel middleware for service selection in mobile ad-hoc networks with a particular focus on scenarios immediately and subsequently afterwards an emergency. The proposed middleware, operating on a mobile user's hand-held device and collecting the user's contexts through machine-to-machine connectivity, has three major contributions as compared to the current literature. The middleware, based on the collected contexts, firstly classifies a service request, e.g., safety-related or comfort service. Then, it initiates the required network connectivity for service discovery, i.e., the ad-hoc connectivity when an infrastructure-based network is inaccessible. Finally, the middleware selects the service based on a method specifically proposed for that service category, including pre-defined realistic user contexts, to access it. The simulation results show that the middleware achieves up to 12 percent higher success rate compared to the minimum hop count service selection method. Compared with the same method, it has a response time up to 50 percent lower for the safety-related but 80 percent higher for the comfort services. Yet, the middleware attains up to 96 percent user satisfaction rate for both service classes.