A Learning Automata Scheduler for the Parallel Distributed Computing Systems

抄録

In network computing system, load balance is a job distribution among multi-processors. Round Robin and random job allocation are the two simplest algorithms. The problem with these two approaches is they don't weight the loads when sending them out to the addresses. Therefore, for efficiently making use of the network, a job scheduling mechanism is required to make reasonable job assignment. This mechanism should be able to respond dynamically to the job transfer address and at the same time properly allocate jobs when the changes in traffic or in individual computer processing speed or in the length of wait-queue are not predictable.

In this paper, on the load distribution problem in parallel distribution computing system, learning automaton is introduced to the scheduling mechanism, which is able to dynamically respond to job addresses and make proper job assignment.