Efficient Server Provisioning and Offloading Policies for Internet Data Centers with Dynamic Load-Demand

Abstract

In data centers, traffic demand varies in both large and small time scales. A data center with dynamic traffic often needs to over-provision active servers to meet the peak demand, which incurs significant energy cost. In this paper, our goal is to reduce energy cost of a set of distributed Internet data centers (IDCs) while maintaining the quality of service of the dynamic traffic. In particular, we consider the outage probability as the QoS metric, where outage is defined as service demand exceeding the capacity. We require the outage probability at each IDC to be smaller than a predefined threshold. Our goal is thus to minimize total energy cost over all IDCs, subject to the outage probability constraint. We achieve the goal by dynamically adjusting server capacity and performing load shifting in different time scales. We propose three different load-shifting and joint capacity allocation schemes with different complexity and performance. Our schemes leverage both stochastic multiplexing gain and electricity-price diversity. Thus, improving over prior work, our schemes reduce energy consumption/cost even when all IDCs have the same electricity price. We use both simulated load traces and real traffic traces to evaluate the performance of the proposed schemes. Results show that our proposed schemes are efficient in reducing energy cost, and robust in QoS provisioning.