Profit Maximization for Geographical Dispersed Green Data Centers

TL;DR

This paper develops an optimization framework for maximizing profit in geographically dispersed green data centers by considering workload distribution, energy sources, SLAs, and electricity markets, validated through simulations.

Contribution

It introduces a convex optimization model that effectively balances green and brown workloads across regions, accounting for diverse energy markets and SLAs.

Findings

Convexity of the optimization problem is proven.

Workload distribution strategy improves profit in simulations.

Effective integration of green energy and market factors enhances data center efficiency.

Abstract

This paper aims at maximizing the profit associated with running geographically dispersed green data centers, which offer multiple classes of service. To this end, we formulate an optimization framework which relies on the accuracy of the G/D/1 queue in characterizing the workload distribution, and taps on the merits of the workload decomposition into green and brown workload served by green and brown energy resources. Moreover, we take into account of not only the Service Level Agreements (SLAs) between the data centers and clients but also different deregulated electricity markets of data centers located at different regions. We prove the convexity of our optimization problem and the performance of the proposed workload distribution strategy is evaluated via simulations.