Bandwidth Scheduling for Energy Efficiency in High-Performance Networks

The transfer of big data in various applications across high-performance networks (HPNs) in a national or international scope consumes a significant amount of energy on a daily basis. However, most existing bandwidth scheduling algorithms only consider traditional objectives, such as data transfer time minimization, and very limited efforts have been devoted to energy efficiency in HPNs. In this paper, we consider two widely adopted power models, i.e., power-down and speed-scaling, and formulate two instant bandwidth scheduling problems to minimize energy consumption under data transfer deadline and reliability constraints. We prove the NP-completeness of both problems, and design a fully polynomial time approximation scheme for the problem using the power-down model. We also design an approximation algorithm and a heuristic approach that considers the tradeoff between objective optimality and time cost in practice for the problem using the speed-scaling model. The performance superiority of the proposed solutions is illustrated by extensive results based on both simulated and real-life networks in comparison with existing methods.