Online algorithms for geographical load balancing

TLDR

Internet energy costs can be lowered by shifting workloads to data centers in regions with low energy prices, allowing lightly loaded centers to shut surplus servers, a strategy often implemented with receding‑horizon control. The study develops online algorithms to decide how many servers to keep active in each data center and applies them to assess the environmental benefits of geographical load balancing. The algorithms evaluate the feasibility of powering a continent‑wide network of data centers primarily with renewable energy and identify the most effective renewable portfolio. RHC works well in homogeneous environments but fails when propagation delays, server counts, and electricity prices vary, prompting the authors to propose robust RHC variants that maintain performance under heterogeneity.

Abstract

It has recently been proposed that Internet energy costs, both monetary and environmental, can be reduced by exploiting temporal variations and shifting processing to data centers located in regions where energy currently has low cost. Lightly loaded data centers can then turn off surplus servers. This paper studies online algorithms for determining the number of servers to leave on in each data center, and then uses these algorithms to study the environmental potential of geographical load balancing (GLB). A commonly suggested algorithm for this setting is "receding horizon control" (RHC), which computes the provisioning for the current time by optimizing over a window of predicted future loads. We show that RHC performs well in a homogeneous setting, in which all servers can serve all jobs equally well; however, we also prove that differences in propagation delays, servers, and electricity prices can cause RHC perform badly, So, we introduce variants of RHC that are guaranteed to perform as well in the face of such heterogeneity. These algorithms are then used to study the feasibility of powering a continent-wide set of data centers mostly by renewable sources, and to understand what portfolio of renewable energy is most effective.