A Research of Time Cost Balance Simulated Annealing Ant Colony Algorithm for Task Allocation in Cloud Computing

Aiming at solving the problem of task allocation in cloud computing, this paper proposes a restraint function of Time Cost Balance Simulated Annealing Ant Colony Algorithm (TCBSA-ACO). The TCBSA-ACO, combined with features of task allocation in cloud computing, improves information elements updating and inspiring factors creatively by establishing a time cost restraint function and a load standard deviation function, and achieves global optimization of all the answers by adopting the simulated annealing algorithm. Some simulation experiments are done by the tool CloudSim, and the results are compared with those of the standard ant colony algorithms BACO and the latest ant colony algorithm DSFACO. The comparison shows that this TCBSA-ACO algorithm is more efficient than the other two algorithms both in reducing time and cost of task execution and in keeping load balance, thus improves resource utilization in the system.