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A K-Clique Based Clustering Protocol for Resource Discovery in P2P Network

Publication Type : Conference Paper

Publisher : 2018 International Conference on Advances in Computing, Communications and Informatics (ICACCI)

Source : 2018 International Conference on Advances in Computing, Communications and Informatics (ICACCI), p. pp. 2475-2480 (2018)

Url : https://ieeexplore.ieee.org/document/8554723

Keywords : clique based model, Cloud computing, cloud systems, Clustering, Clustering algorithms, Data transfer, distributed databases, Internet of things, k-clique, k-clique based clustering protocol, k-clique based overlay network formation, meta data, metadata type, multikey-single value pair mapping mechanism, Nickel, Overlay networks, P2P network, pattern clustering, Peer to Peer Network, peer-to-peer computing, Protocols, resource discovery, routing, Semantics

Campus : Amritapuri

School : Department of Computer Science and Engineering, School of Engineering

Department : Computer Science

Verified : No

Year : 2018

Abstract : Data transfer amongst peers in a network without a central authority to regulate traffic, is on the ascendancy in the recent years. In this paper, we propose a k-clique based overlay network formation using multi key-single value pair mapping mechanism within a peer to peer network. This clique based model aims to discover resources of the same metadata type within a cluster of subnet with a minimum of hops as possible subject to the nodes having certain properties. The discovery of a subset of resources sharing similar characteristics is essential in the context of requirements being dynamic, in fields related to Internet of Things and Cloud systems. The simulated experiment validates our approach as it discovers resources in very less number of hops.

Cite this Research Publication : Krishna Prasad T. R., Jayakumar P., and Dr. Sajeev G. P., “A K-Clique Based Clustering Protocol for Resource Discovery in P2P Network”, 2018 International Conference on Advances in Computing, Communications and Informatics (ICACCI). IEEE. pp. 2475-2480, 2018. doi: 10.1109/icacci.2018.8554723.

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