A Modified Ant Colony based optimization for managing Cloud resources in manufacturing sector

Resource scheduling and management is an important problem in Cloud Manufacturing. The concept of optimization for scheduling jobs is an important issue to be considered in scheduling of different resources among heterogeneous users. The resources are placed across diversified locations in cloud and the major task is to distribute the resources effectively such that the makespan and completion time is reduced. In this paper, a Modified Ant Colony based optimization technique is proposed to optimize the resources through distributed computation. ACO is used to choose one among the different alternative rules to determine the processing order of each resource. Rather than having a larger search space, this approach reduces the search space and gives better solution. This reduces the delay in allocating resources to the user by providing an adaptive and global search technique. This approach reduces the total completion time of jobs and also takes in to account the migration time of the process. A series of experiments were conducted and the results of the experiment are compared with other heuristic algorithms like PSO. The results have shown that this approach can produce optimal solutions quickly by reducing delays.