Profile Data Deploying Strategy for Efficient Cooperative Reasoning on Ontology

Abstract

This paper introduces the profile data management scheme such as data structuring, interchanging and data deployment. An overwhelming amount of multimedia data is generated by surveillance devices such as smart cameras. Profile data contained in them if properly structured and is integrated, can induce a useful context information. This work builds a hierarchical profile data deploy structure and import related multimedia data to annotate rich data arriving from multiple sensor streams, in this case smart cameras. The annotation process provides an impetus to the improvement of knowledge over time. Proactive deploying provides the main concepts and properties to model a hierarchical area data structure which can span a university campus or an apartment or a city. We also define management policies to compare their performance for the wide area surveillance specifically. The popularity of smart cameras providing many intelligent functions grows with the advance of electronic technologies and Internet applications. It explores the convergence of the caching and streaming technologies for multimedia data. For the surveillance of the large area, agents built in networked RFID sensors, CCTVs and smart cameras should collaborate through integration of profile data. Profile data includes audio, video, recognized feature data, ontology data and others. Most such transfers would take place with the streaming data passing through one or more of the agents caching the streaming data as it passes through. Effective caching techniques will be critical for the successful deployment of streaming multimedia data over the surveillance network. This should be obvious, because of the huge latencies involved, and the requirements of real time play out. This paper describes a framework for the working of such a distributed caching and streaming system. Distributed agents receiving heterogeneous data from various sources have autonomy, collaborate with each other, and do ontology reasoning based on distributed knowledge bases. A framework for the integration of profile data supplied by a set of agents is designed. The agents are interconnected through a peer network. And non-leaf administrative agents in a geographic area hierarchy or in an administration hierarchy build a hierarchical structure according to their right hierarchy. This framework guarantees the consistency and expressivity of the ontology used in the data integration process. In the process of reasoning each agent may process the consolidated data for the distributed and autonomous reasoning, which is scalable and efficient(1), helps security persons by giving appropriate decision or prediction based on huge ontology data about situation it gathers. The distribution of demands for profile data items is often skewed, and the surveillance devices have different capabilities and data formats. These can lead to poor data communication and dropped messages. In this paper, we propose a proactive caching scheme for efficiency and