Intelligent Bandwidth Reservation for Big Data Transfer in High-Performance Networks

Abstract

Many scientific applications are generating extremely large amounts of data at a high speed, which must be transferred to remote collaborating sites for storage and analysis. Such high- demanding data transfer has been increasingly supported by bandwidth reservation services in high-performance networks (HPNs). For each bandwidth reservation request (BRR), most existing scheduling algorithms return either the best-case reservation option or a reject message if the BRR cannot be satisfied. To perform intelligent scheduling, we provide two alternative reservation options in the latter case: schedule the BRR within the closest time intervals before and after the user-specified time interval. We consider two different types of BRRs and for each, we design a flexible bandwidth scheduling algorithm with a rigorous optimality proof to compute both the best and alternative reservation options. For comparison, we also design two heuristics adapted from existing bandwidth scheduling algorithms. Extensive simulations show that the proposed algorithms have superior performance to those in comparison.