Named Content Searching in Opportunistic Mobile Networks

In this letter, we study the adaptation of named data networking-based named content searching in opportunistic mobile networks (OMNs). Given the inherent uncertainty in OMNs, our goal is to replicate the content requests to a suitable set of nodes that can help improve users' experience in terms of requests satisfaction and latency. To this end, we propose a scheme, content searching as regret minimization (CHARM), based on the technique of random regret minimization. In CHARM, content interest replication and non-replication choices are expressed in terms of several measurable attributes. Regrets associated with the two choices indicate whether or not an interest should be replicated. Moreover, to reduce overhead, CHARM uses dynamic time-to-live adaptation, where the lifetime of a message is proactively scaled down. The results of performance evaluation based on real-life traces and synthetic mobility model indicate that CHARM can improve the number of interests satisfied and latency, respectively, by up to 1.6 and 1.4 times when compared with a contemporary scheme.

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