Workload characteristics for process migration and load balancing

Abstract

Is process migration useful for load balancing? We present experimental results indicating that the answer to this question depends largely on the characteristics of the applied workload. Experiments with our Shiva system, which supports remote execution and process migration, show that only those CPU bound workloads which were generated using an unrealistic exponential distribution for execution times show improvements for dynamic load balancing. (We use the term 'dynamic' to indicate remote execution determined at and not prior to run time. The latter is known as 'static' load balancing.) Using a more realistic workload distribution and adding a number of short lived tasks prevents dynamic algorithms from working. Migration is only useful with heterogeneous workloads. We find the migration of executing tasks to remote data to be effective for balancing I/O bound workloads, and indicate the region of 'workload variable space' for which this migrate-to-data approach is useful.