An Efficient Topology-Adaptive Membership Protocol for Large-Scale Cluster-Based Services

  • Authors:
  • Jingyu Zhou;Lingkun Chu;Tao Yang

  • Affiliations:
  • Ask Jeeves Inc., Piscataway, NJ/ University of California at Santa Barbara;Ask Jeeves Inc., Piscataway, NJ;Ask Jeeves Inc., Piscataway, NJ/ University of California at Santa Barbara

  • Venue:
  • IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Papers - Volume 01
  • Year:
  • 2005

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Abstract

A highly available large-scale service cluster often requires the system to discover new nodes and identify failed nodes quickly in order to handle a high volume of traffic. Determining node membership promptly in such an environment is critical to location-transparent service invocation, load balancing, and failure shielding. In this paper, we present a topology-adaptive hierarchical membership service which dynamically divides the entire cluster into membership groups based on the network topology among nodes so that the liveness of a node within each group is published to others in a highly efficient manner. The proposed approach has been compared with two alternatives: an allto-all multicast approach and a gossip based approach. The results show that the proposed approach is scalable and effective in terms of high membership accuracy, short view convergence time, and low communication cost.