Balancing electricity bill and performance in server farms with setup costs

High electricity consumption, associated with running Internet scale server farms, not only reflects on the data center’s greenhouse gas emissions, but also increases the cost of running the data center itself. In this paper, we consider the problem of maximizing the revenues of service providers running large scale data centers subject to setup cost by reducing their electricity bill, while considering the fact that clients consuming the offered services have finite non-deterministic patience. As a solution, we present and evaluate the performance of allocation policies which, in the context of both one and two-tiered systems, dynamically switch servers on and off according to changes in user demand. The algorithms we present aim at maximizing the users’ experience while minimizing the amount of electricity required to run the IT infrastructure in spite of non-stationary traffic which cannot be predicted with the absolute accuracy. The results of several experiments are presented, showing that the proposed schemes perform well under different traffic conditions.

► We propose a set of allocation policies.
► They aim at delivering performance while minimizing the number of required servers.
► The computational cost of the decision making is extremely low.
► Our algorithms can be used online as a part of a dynamic allocation scheme.
► Experiments show that our policies perform well under different traffic conditions.