A Data Dissemination Algorithm for Opportunistic Networks

Opportunistic networks are an evolution of MANETs, where highly mobile nodes that have no physical route connecting them might need to communicate. In this case routes are built dynamically, as nodes act according to a store-carry-and-forward paradigm. A natural continuation of forwarding in opportunistic networks is data dissemination, which is usually performed using the publish/subscribe model. In this paper, we propose a socially-based data dissemination technique for opportunistic networks called Social Dissemination. The solution assumes that nodes are grouped into communities, where nodes in the same community meet often, while at the same time certain nodes may have relationships with nodes from other communities. When two nodes meet, they exchange information about the data they store, and select data objects from the other node according to a utility function. We define such a utility function and experimentally compare its results with previously proposed state-of-the-art dissemination techniques.