Reconfigurable Parallel Processing System Based on A Modified Ant Colony Algorithm

Abstract

Ant colony optimization is an evolutionary approach where a number of ants search for good solutions. Ant Algorithms often show good optimization results. This paper, discusses number of algorithms built using modified ant colony algorithm which are used to solve the problem of assigning each task in a given task graph to a processor in a reconfigurable multi processor architecture so as to minimize the total overall execution time of the tasks. Each group of ants is working collectively to find the interconnection architecture best suited for the task graph and the best scheduling of that task graph on the chosen interconnection architecture. The total execution time is computed according to the knowledge of individual run times of tasks and the communication requirements among tasks. The inter task communication time is dependent on the interconnection processor architecture. The results of using modified ant colony algorithm in reconfigurable parallel processor system are compared with that of using genetic algorithm for solving the same problem.