Paper Title
Efficient Cooperative Inference Infrastructure For Reasoning Agents In Surveillance Networks

In this paper an efficient and scalable inference infrastructure for surveillance networks providing systematic collection and analysis of social security data based on distributed cooperative ontology framework is proposed. Upon cooperative inference system, each reasoning agent can build and process ontology cooperatively. They share context data for cooperative combined inference. In the process of reasoning agents not only can utilize their own ontologies from a region server but also can form and generate a P2P(peer-to-peer) network to provide ontologies with knowledge data and services to each other in wider bandwidth. For efficient ontology integration the data weighting and similarity measure is incorporated for better caching in information concentric P2P network and shows better performance. Key words- agent, context ontology, data weighting, surveillance networks, information centric peer-to-peer network