Cost‐minimizing online algorithm for internet green data centers on multi‐source energy

Abstract

Huge energy consumption of large-scale cloud data centers damages environments with excessive carbon emission. More and more data center operators are seeking to reduce carbon footprint via various types of renewable energy. However, the intermittent availability of renewable energy sources makes it quite challenging to cooperate with dynamically arriving workload.Meanwhile, the different natures (eg, price and carbon emission) of multiple energy sources also bring more challenges to achieve an optimal trade-off among carbon emission, power cost, and service level agreement (SLA). In this paper, we study the problem of reducing the long-term energy cost for geo-distributed cloud centers, where multiple sources of renewable energy are considered and SLA requirement and carbon budget are satisfied. To tackle the randomness of workload arrival, varying electricity price, and intermittent supply of renewable energy, we first formulate the cost minimization problem as a constraint stochastic optimization problem. Second, based on Lyapunov optimization technique, we propose an online control algorithm to solve it and provide the rigorous theory analysis to demonstrate its performance. By converting the long-term optimization problem to a mixed integer linear programming problem in each time slot, we analyze its inherent structure and propose an efficient algorithm to solve it based on Brenner's method.Our proposed algorithm makes online decisions rely only on the current system state and achieve [O( 1 ∕V), O(V)] cost emission trade-off. Finally, the effectiveness of our algorithm is evaluated by extensive simulations based on real-world data traces. KEYWORDS geo-distributed cloud center, green-aware, Lyapunov optimization, renewable energy INTRODUCTIONDriven by the exploding demand of enterprises and personal computation, the scale of cloud data centers has become increasingly large. As stated in the latest report, 1 some leading IT enterprises (eg, Facebook, Amazon, and Google) own their inter-continental data centers in different regions that contain thousands of servers. Thus, accompanied with the corresponding electricity cost is up to millions dollars per year. Meanwhile, large electricity consumption from "brown energy" (produce from oil or coal) brings a large amount of greenhouse gases (GHG) emissions which cause great damages to the fragile environment. Recent studies have shown that Information and Communications Technology (ICT) sector is responsible for 2% of global carbon emission, which places it on par with the aviation industry, and this is set to be doubled by 2020. 2,3 Therefore, it is significant for the large-scale data centers to reduce the net carbon footprint and power cost.Recently, reducing power consumption to make data centers green with renewable energy has received a lot of attention both in industry. 4 and academia. 5,6 Compared to brown energy, renewable energy (such as wind energy and solar energy) is more environmentally friendly with low carbon footprint. Google, Microsoft, and Faceboo...

Foreword to the Special Section on Parallel and Distributed Computing, Applications and Technologies

“…In the third paper, the authors proposed a new finer‐grained model that can evaluate online the trade‐off between energy cost and carbon emission for operating large‐scale data centers on heterogeneous energy sources. They formulated this problem as a constraint stochastic optimization problem and proposed the Green‐Aware Online control Algorithm (GAOA), which makes an online decision relying only on the current system state and an efficient solution to achieve long‐term optimization by solving a mixed‐integer linear programming problem in each time slot.…”