With their proliferation and increasing capabilities, mobile devices with local wireless interfaces can be organized into opportunistic networks that exploit communication opportunities arising out of the movement of their users. Because the nodes are carried by people, these opportunistic networks can also be viewed as social networks. Unfortunately, existing routing algorithms for opportunistic networks rely on relatively simple mobility models that rarely consider these social network characteristics. In this paper, we propose PreS (Predict and Spread), an efficient routing algorithm for opportunistic networking that employs an adapted Markov chain to model a node's mobility pattern, and capture its social characteristics. A comparison with state-of-the-art algorithms suggests that PreS can yield better performance in terms of delivery ratio and delivery latency, and approaches the performance of the Epidemic algorithm with lower resource consumption.
['Jianwei Niu', 'Jinkai Guo', 'Qingsong Cai', 'Norman M. Sadeh', 'Shaohui Guo']
Predict and spread: An efficient routing algorithm for opportunistic networking