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Developing and Analysing Dynamic Resource Management Algorithms with a Generic Framework

Distributed systems need to share tasks efficiently to exploit their performance. A combination of process migration and dynamic resource management algorithms can enable this. We investigate one such migration technique and five algorithms in order to create a generic resource management framework for distributed systems. We use openMosix’s transparent process migration under Linux for experimentation. Experiments that were run on 4-, 8and 12-node clusters showed that performance depends heavily upon process migration, and less so on the algorithms. Some algorithms also monitor multiple resources to improve performance. Scalability of the framework is an important consideration, and we found that even with distributed control a completely connected network would soon become unmanageable as the number of nodes is increased. We find that the opportunity cost algorithms are the most consistent but upon consideration of scalability suggest that simpler algorithms, such as the distributed MINIX load balancer, are desirable.