Title: A self-adaptive resource index and discovery system in distributed computing environments

Authors: Wu-Chun Chung; Yi-Hsiang Lin; Kuan-Chou Lai; Kuan-Ching Li; Yeh-Ching Chung

Addresses: Department of Computer Science, National Tsing Hua University, Hsinchu 300, Taiwan ' Institute of Information Systems and Applications, National Tsing Hua University, Hsinchu 300, Taiwan ' Department of Computer and Information Science, National Taichung University, Taichung 403, Taiwan ' Department of Computer Science and Information Engineering, Providence University, Taichung 433, Taiwan ' Department of Computer Science, National Tsing Hua University, Hsinchu 300, Taiwan

Abstract: Resource-sharing systems apply the Peer-to-Peer (P2P) technique to provide scalable multi-attribute range queries. However, due to the heterogeneity of resources and the variation of sharing policies from different providers, current P2P-based resource discovery systems may suffer the load imbalance problem in large-scale distributed systems. In this paper, a self-adaptive resource index and discovery system, NAMED SARIDS, is proposed to achieve load balancing in distributed computing environments, by adopting a two-tier architecture based on structured P2P overlay. Experimental results show that SARIDS is scalable yet efficient for load balancing even in non-uniform peer range environments.

Keywords: distributed computing; self-adaptive resource discovery; multi-attribute queries; range queries; load balancing; peer-to-peer; P2P overlays; self-adaptive resource index.

DOI: 10.1504/IJAHUC.2012.048259

International Journal of Ad Hoc and Ubiquitous Computing, 2012 Vol.10 No.2, pp.74 - 83

Published online: 30 Jul 2012 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article