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Distributed Aggregation Algorithms with Load-Balancing for Scalable Grid Resource Monitoring

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2 Author(s)
Min Cai ; Dept. of Comput. Sci., Univ. of Southern California, Los Angeles, CA ; Kai Hwang

Scalable resource monitoring and discovery are essential to the planet-scale infrastructures such as grids and PlanetLab. This paper proposes a scalable grid monitoring architecture that builds distributed aggregation trees (DAT) on a structured P2P network like Chord. By leveraging Chord topology and routing mechanisms, the DAT trees are implicitly constructed from native Chord routing paths without membership maintenance. To balance the DAT trees, we propose a balanced routing algorithm on Chord that dynamically selects the parent of a node from its finger nodes by its distance to the root. This paper shows that this balanced routing algorithm enables the construction of almost completely balanced DATs, when nodes are evenly distributed in the Chord identifier space. We have evaluated the performance and scalability of a DAT prototype implementation with up to 8192 nodes. Our experimental results show that the balanced DAT scheme scales well to a large number of nodes and corresponding aggregation trees. Without maintaining explicit parent-child membership, it has very low overhead during node arrival and departure. We demonstrate that the DAT scheme performs well in grid resource monitoring.

Published in:

Parallel and Distributed Processing Symposium, 2007. IPDPS 2007. IEEE International

Date of Conference:

26-30 March 2007