A Hybrid Ant Colony Tabu Search Algorithm for Solving Task Assignment Problem in Heterogeneous Processors

摘要

Assigning real-time tasks in a heterogeneous parallel and distributed computing environment is a challenging problem, in general, to be NP hard. This paper addresses the problem of finding a solution for real-time task assignment to heterogeneous processors without exceeding the processor capacity and fulfilling the deadline constraints. The proposed Hybrid Max-Min Ant System (HACO-TS) makes use of the merits of Max-Min ant system with Tabu search algorithm for assigning tasks efficiently than various metaheuristic approaches. The Tabu search is used to intensify the search by the MMAS method. The performance of the proposed HACO-TS algorithm has been tested on consistent and inconsistent heterogeneous multiprocessor systems. Experimental comparisons with existing Modified BPSO algorithms demonstrate the effectiveness of the proposed HACO-TS algorithm.