A cognitive-based solution for semantic knowledge and content dissemination in opportunistic networks

Opportunistic networking is one of the key paradigms to support direct communication between devices in a mobile scenario. In this context, the high volatility and dynamicity of information and the fact that mobile nodes have to make decisions in condition of partial or incomplete knowledge, makes the development of effective and efficient data dissemination schemes very challenging. In this paper we present algorithms based on well-established models in cognitive sciences, in order to disseminate both data items, and semantic information associated with them. In our approach, semantic information represents both meta-data associated to data items (e.g., tags associated to them), and meta-data describing the interests of the users (e.g., topics for which they would like to receive data items). Our solution exploits dissemination of semantic data about the users' interests to guide the dissemination of the corresponding data items. Both dissemination processes are based on models coming from the cognitive sciences field, named cognitive heuristics, which describe how humans organise information in their memory and exchange it during interactions based on partial and incomplete information. We exploit a model describing how semantic data can be organised in each node in a semantic network, based on how humans organise information in their memory. Then, we define algorithms based on cognitive heuristics to disseminate both semantic data and data items between nodes upon encounters. Finally, we provide initial performance results about the diffusion of interests among users, and the corresponding diffusion of data items.