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RCT: A Self-Adaptive Overlay for Efficient Computational Resource Discovery in Grid Systems

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4 Author(s)
Hailong Sun ; Beihang University, China ; Jinpeng Huai ; Gongwei Fu ; Yunhao Liu

Computational resource discovery is of great importance in grid environments. Existing approaches do not consider the characteristics of application resource requirements. We propose, Resource Category Tree (RCT), which organizes computational resources based on their characteristics represented by primary attributes (PA). RCT adopts a structure of AVL tree, with each node representing a specific range of PA values. Though RCT adopts a hierarchical structure, it does not require nodes in higher levels maintain more information than those in lower levels, which makes RCT highly scalable. RCT is featured by self-organization, load-aware self-adaptation and fault tolerance. Based on RCT, commonly used queries, such as range queries and multi-attribute queries, are well supported. We conduct performance evaluations through comprehensive simulations.

Published in:

e-Science and Grid Computing, 2006. e-Science '06. Second IEEE International Conference on

Date of Conference:

Dec. 2006

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