Scheduling of near-future workload in distributed computing systems

A major issue in distributed computing systems is the choice of an adequate load balancing policy. ´Traditional´ load balancing policies assign independent tasks to servers, while scheduling policies assume complete knowledge of task dependencies and treat the assignment problem as a large search problem. However, both approaches are based on assumptions that do not hold in distributed computing systems: the job context of tasks exists and thus dependencies between tasks, but they cannot be predicted a long time in advance. In this paper, a dynamic decentralized load balancing policy is introduced that utilizes neat-future workload predictions based on knowledge about the job context. A performance evaluation by simulation and a comparison to widely used load balancing policies is presented.<>