DocumentCode
2350739
Title
A Knowledge-Driven Architecture for Efficient Resource Discovery in P2P Networks
Author
Eftychiou, Athena ; Vrusias, Bogdan
Author_Institution
Dept. of Comput., Univ. of Surrey, Guildford, UK
fYear
2010
fDate
24-26 Nov. 2010
Firstpage
467
Lastpage
472
Abstract
As shared electronic data increases, it has become more difficult to manage it successfully and the demand for scalable and efficient mechanisms for managing and retrieving data effectively becomes essential. In this paper a more effective P2P architecture is presented, aiming to improve existing resource discovery processes. The proposed architecture is organised as a hierarchical super-peer structure, where super-peers of the network represent network´s knowledge that is formalised dynamically using its peers´ resources. The main focus of this paper is the creation of an adaptive hierarchical concept-based P2P topology using collective intelligence methods. In that process, unmanageable data is transformed into a structured knowledge based repository of semantic resources. Therefore, the network takes the form of an ontology of conceptually related entities of resource information, as provided by the peers. This knowledge driven approach has benefits over traditional load driven architectures, as the user query context is usually the main driver for managing the performance of the network, and in a way the network can be characterised as proactive rather than reactive. A number of experiments have been undertaken and results demonstrate the advantages of the proposed concept-based architecture over other popular architectures.
Keywords
data mining; ontologies (artificial intelligence); peer-to-peer computing; query processing; P2P network; collective intelligence method; hierarchical super peer structure; knowledge driven architecture; ontology; peer-to-peer network; resource discovery; user query; collective intelligence; distributed information retrieval; domain ontology; peer-to-peer (P2P) networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Networking and Collaborative Systems (INCOS), 2010 2nd International Conference on
Conference_Location
Thessaloniki
Print_ISBN
978-1-4244-8828-5
Electronic_ISBN
978-1-4244-4278-2
Type
conf
DOI
10.1109/INCOS.2010.71
Filename
5702144
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