Predictive Feedback Scheduling for Resource-Constrained Networks with Flexible Workload

Resource-constrained networks usually run in an unpredictable open environment due to the workload variations. In this paper, a predictive feedback scheduler based on least squares support vector machines (LSSVM) is proposed in order to guarantee the stability of the system. It periodically monitors the network resources, predicates the next period of available bandwidth, and adopts interpolated method to calculate the next sampling period from predicative value. Consequently, the system's bandwidth is dynamically allocated by this feedback scheduling mechanism. Two different strategies, which are fixed bandwidth allocation and predictive feedback scheduling strategy based on LSSVM, are compared respectively. The results of simulation indicate that the proposed strategy can guarantee the stability of the system with flexible workload, and prove that the predictive feedback scheduling is an effective tradeoff method between quality of control and quality of service.