Algorithms for Energy Conservation in Heterogeneous Data Centers
Susanne Albers, Jens Quedenfeld · Lecture notes in computer science · 2021
Abstract Power consumption is the major cost factor in data centers. It can be reduced by dynamically right-sizing the data center according to the currently arriving jobs. If there is a long period with low load, servers can be powered down to save energy. For identical machines, the problem has already been solved optimally by [25] and [1]. In this paper, we study how a data-center with heterogeneous servers can dynamically be right-sized to minimize the energy consumption. There areddifferent server types with various operating and switching costs. We present a deterministic online algorithm that achieves a competitive ratio of 2das well as a randomized version that is 1.58d-competitive. Furthermore, we show that there is no deterministic online algorithm that attains a competitive ratio smaller than 2d. Hence our deterministic algorithm is optimal. In contrast to related problems like convex body chasing and convex function chasing [17, 30], we investigate the discrete setting where the number of active servers must be an integral, so we gain truly feasible solutions.