Load balancing is a key issue in large-scale object-based storage systems. Many data replication and migration algorithms have been proposed for load balancing in distributed systems. However, the two operations, data replication and migration, are studied separately. An adaptive load balancing algorithm is presented in this paper, which combines replication and migration in a uniform model. Furthermore, this algorithm uses a hybrid load metric which reflects short-term and long-term load status. To solve the online problem with a changing workload, the algorithm employs an adaptive mechanism to keep track of the characteristics of workloads. The simulation results show that the algorithm with object replication and migration can markedly reduce the overall response time
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Machine Learning and Cybernetics, 2006 International Conference on
Date of Conference: 13-16 Aug. 2006