Performance Characterization of Decentralized Algorithms for Replica Selection in Distributed Object Systems
Kevin L. Mills, C Tan
Designers of distributed software systems often rely on server replicas for increased robustness, scalability, and performance. Replicated server architectures require some technique to select a target replica for each client transaction. In this paper, we survey key concepts related to replica selection and we use simulation to characterize performance (response time, server latency, selection error, probability of server overload) for four common replica-selection algorithms (random, greedy, partitioned, weighted) when applied in a decentralized form to client queries in a distributed object system deployed on a local network. We introduce two new replica-selection algorithms (balanced and balanced-partitioned) that give improved performance over the more common algorithms. We find the weighted algorithm performs best among the common algorithms and the balanced algorithm performs best among all those we considered. Our findings should help designers of distributed object systems to make informed decisions when choosing among available replica-selection algorithms.
Proceedings of the International Workshop on Software Performance 2005
and Tan, C.
Performance Characterization of Decentralized Algorithms for Replica Selection in Distributed Object Systems, Proceedings of the International Workshop on Software Performance 2005, -1, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=150111
(Accessed February 26, 2024)