Time-constrained workflow scheduling in cloud environment using simulation annealing algorithm

Abstract

In cloud environment, it is necessary to find the efficient algorithms to optimize time-cost of cloud-oriented workflow scheduling. In this paper, a Simulated Annealing algorithm based heuristic is put forward in order to solve the timeconstrained scheduling problem. Time-cost of scheduling is consisted of tasks execution and data transmission. The simulation testing results demonstrates that, the time-cost of scheduling using this algorithm can cost less time compared with particle swarm optimization algorithm, SA-based scheduling can also balance the load on resources, and SA with good convergence can find global optimal solution faster. © 2013 Kavala Institute of Technology.