Combo-Pre: A Combination Link Prediction Method in Opportunistic Networks

Abstract

Opportunistic networks have emerged as prospective network architecture for smart mobile devices related applications. The main obstacle for designing routing protocol in opportunistic networks is their inherent dynamic nature. Unknown future link patterns lead to blind and inefficient packet forwarding behavior. Lots of efforts have focused on the future link prediction problem, but contact patterns among node pairs are too different to be predicted by one single method. To this end, we propose a combination link prediction method for opportunistic network routing named Combo-Pre. Combo-Pre applies periodic pattern mining methods to predict frequent and periodic contacts, decision tree method to predict frequent but non-periodic contacts and Adamic-Adar methods in complex networks to predict infrequent contacts. Experimental results show that Combo-Pre outperforms state-of-the-art link prediction methods in opportunistic networks. These results can be applied in routing protocol design to decrease routing cost and promote delivery rate.