Probabilistic load scheduling with priorities in distributed computing systems

Abstract

Scheduling of processing loads play an important role in the performance of a distributed computing system/network. This is more important when the distributed computing system consists of many heterogeneous processors, with different processing capabilities. The scheduling strategies should also take into account the priorities given to the loads, when there is more than one type of jobs utilizing the system. A methodology is presented to obtain optimal load scheduling strategies, when there are two type of loads in a heterogeneous distributed computing system. In this paper a distributed computing system/network in which two type of loads (or jobs) namely local loads and global loads arrive is considered. The local loads originate at the individual processors/nodes in the network and have to be processed at the same processors. The global loads originate at the central scheduler and have to be distributed among the processors in the system. The individual processors in the system assign different priorities to local and global loads. A priority queuing optimization model of this situation is formulated as a nonlinear programming problem and a solution methodology is presented. The arrival rate of the global and local loads are assumed to follow Poisson distribution and the service time of the global and local loads at the processors follow a general or exponential service time distribution. Both the situations are analyzed. The objective of this study is to minimize the response time of the global loads in the network.