Simulative performance analysis of gossip failure detection for scalable distributed systems

  • Authors:

  • Mark W. Burns;Alan D. George;Bradley A. Wallace

  • Affiliations:

  • High-performance Computing and Simulation (HCS) Research Laboratory, Department of Electrical and Computer Engineering, University of Florida, P.O. Box 116200, Gainesville, FL 32611-6200, USA;High-performance Computing and Simulation (HCS) Research Laboratory, Department of Electrical and Computer Engineering, University of Florida, P.O. Box 116200, Gainesville, FL 32611-6200, USA;High-performance Computing and Simulation (HCS) Research Laboratory, Department of Electrical and Computer Engineering, University of Florida, P.O. Box 116200, Gainesville, FL 32611-6200, USA

  • Venue:
  • Cluster Computing
  • Year:
  • 1999

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Abstract

Three protocols for gossip-based failure detection services in large-scale heterogeneous clusters are analyzed and compared. The basic gossip protocol provides a means by which failures can be detected in large distributed systems in an asynchronous manner without the limits associated with reliable multicasting for group communications. The hierarchical protocol leverages the underlying network topology to achieve faster failure detection. In addition to studying the effectiveness and efficiency of these two agreement protocols, we propose a third protocol that extends the hierarchical approach by piggybacking gossip information on application-generated messages. The protocols are simulated and evaluated with a fault-injection model for scalable distributed systems comprised of clusters of workstations connected by high-performance networks, such as the CPlant system at Sandia National Laboratories. The model supports permanent and transient node and link failures, with rates specified at simulation time, for processors functioning in a fail-silent fashion. Through high-fidelity, CAD-based modeling and simulation, we demonstrate the strengths and weaknesses of each approach in terms of agreement time, number of gossips, and overall scalability.