Prediction Based Efficient Online Bandwidth Allocation Method

Abstract

In this letter, we propose an efficient online bandwidth allocation method based on Gaussian process regression (GPR) in order to guarantee given quality of service (QoS) requirement and to prevent a waste of resources. To this end, we analyze large-buffer asymptotics for Gaussian queues including non-stationary input processes, and derive the necessary bandwidth to meet the requirement. Our experimental results demonstrate the proposed method satisfies the QoS requirement for both synthetic traffic and real-world traffic. We also show that the proposed algorithm performs better than the existing algorithm in terms of resource efficiency.