Load balancing problems for multiclass jobs in distributed/parallel computer systems

Load balancing problems for multiclass jobs in distributed/parallel computer systems with general network configurations are considered. We construct a general model of such a distributed/parallel computer system. The system consists of heterogeneous host computers/processors (nodes) which are interconnected by a generally configured communication/interconnection network wherein there are several classes of jobs, each of which has its distinct delay function at each host and each communication link. This model is used to formulate the multiclass job load balancing problem as a nonlinear optimization problem in which the goal is to minimize the mean response time of a job. A number of simple and intuitive theoretical results on the solution of the optimization problem are derived. On the basis of these results, we propose an effective load balancing algorithm for balancing the load over an entire distributed/parallel system. The proposed algorithm has two attractive features. One is that the algorithm can be implemented in a decentralized fashion. Another feature is simple and straightforward structure. Models of nodes, communication networks, and a numerical example are illustrated. The proposed algorithm is compared with a well-known standard steepest-descent algorithm, the FD algorithm. By using numerical experiments, we show that the proposed algorithm has much faster convergence in terms of computational time than the FD algorithm.