Services selection and composition in Opportunistic Networks

Opportunistic computing is an exciting evolution of opportunistic networks. The services provision in these networks suffer from the limitations of conventional MANETs such as non stable connections and limited distribution of knowledge between nodes. The introduction of services composition introduces new challenges for the definition of a system able to recognize the best alternative to choose from. The nodes in the network have heterogeneous physical characteristics, different mobility patterns and executes a variety of different services. During the connection, pairs of nodes may collaborate by exchanging information on the network status, such as characteristics of the encountered nodes and workload of their nodes. We propose a system which is capable of processing such information in order to offer the best alternative for a service request. The selection algorithms evaluate services composition by considering alternative paths. In this paper we analyze two types of knowledge distribution strategies to study sequential compositions in opportunistic networks. We propose an analytical model which is validated through a set of simulations, verifying the properties set.