A modify ant colony optimization for the grid jobs scheduling problem with QoS requirements
Xun Pu, Lu Xianliang · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2011
Job scheduling with customers' quality of service (QoS) requirement is challenging in grid environment. In this paper, we present a modify Ant colony optimization (MACO) for the Job scheduling problem in grid. Instead of using the conventional construction approach to construct feasible schedules, the proposed algorithm employs a decomposition method to satisfy the customer's deadline and cost requirements. Besides, a new mechanism of service instances state updating is embedded to improve the convergence of MACO. Experiments demonstrate the effectiveness of the proposed algorithm.