Data-Oriented Task Scheduling in Fixed- and Flexible-Grid Multilayer Inter-DC Optical Networks: A Comparison Study

Abstract

It is known that in multilayer interdatacenter optical networks (ML-IDCONs), network services can generate numerous data-oriented tasks (DoTs) that require not only inter-datacenter (DC) data transfers but also data processing in the DCs. In this paper, we perform a comparison study on the scheduling of DoTs (i.e., setting up lightpaths on fiber links for inter-DC data transfers and scheduling DoT buffering/processing in DCs) in fixed- and flexible-grid ML-IDCONs. We propose a DoT scheduling algorithm that can work well for both types of networks. Specifically, for each DoT, the algorithm first tries to serve it using the residual bandwidth in the IP layer. This is achieved by expanding the time-expanded network approach and transforming the store-and-forward assisted DoT scheduling problem into a minimum-cost maximum-flow (MCMF) problem. Then, by solving the MCMF problem, we find the way to maximize the data transfer throughput and minimize the total dc storage usage simultaneously. Next, if the obtained data transfer throughput is not sufficient for the DoT, the algorithm tries to build lightpath segments for it based on the branch and bound scenario. Extensive simulations are conducted to evaluate the proposed algorithm's performance in fixed- and flexible-grid ML-IDCONs, and also compare it with three benchmarks. Simulation results indicate that for DoT scheduling, the flexible-grid ML-IDCON can outperform fixed-grid ones in terms of the blocking probability, energy consumption of transponders, and usage of dc storage, and our algorithm achieves lower blocking probability than the benchmarks with comparable or higher time-efficiency.