Heuristic Model for Task Allocation in a Heterogeneous Distributed Computing System

In heterogeneous distributed computing systems, partitioning of the application software into modules and the proper allocation of these modules among dissimilar processors are important factors which determine the efficient utilization of resources. This paper presents a new heuristic model, the HMLM/SA, which performs static allocation of such program modules in a heterogeneous distributed computing system in a manner that is designed to minimize the application program's parallel execution time. The new methodology augments the Maximally Linked Module concept by using stochastic techniques and by adding constructs which take into account the limited and uneven distribution of hardware resources often associated with heterogeneous systems. The execution time of the resulting HMLM/SA algorithm and the quality of the allocations produced are shown to be superior to that of the base HMLM algorithm, pure simulated annealing and the randomized algorithm when they were applied to randomly-generated systems and synthetic structures which were derived from real-world problems.