Tasks mapping in grid computing environment based on ACO algorithm
基于蚁群优化算法的网格任务映射策略

In order to optimize the tasks mapping in grid, a grid tasks mapping algorithm based on Ant Colony Optimization (named ACO-GTM) was proposed. The algorithm generated initial solutions through these artificial ants traversed on the construction graph and optimized these initial solutions by using the Best-improvement 2-opt local search algorithm. It combined the global and local pheromone updates. The experiments show that the proposed algorithm for the mapping problem has better performance than other algorithms on optimum makespan and load-balancing.