Cross Service Providers Workload Balancing for Data Centers in Deregulated Electricity Markets

Jun Sun, Shibo Chen, Georgios B. Giannakis, Qinmin Yang, Zaiyue Yang

Research output: Contribution to journalArticlepeer-review

Abstract

The emerging Internet of things (IoT) and 5G applications boost a skyrocketing demand for data processing, which results in an enormous energy consumption of data centers (DCs). Considering that existing distributed geographical load balancing is approaching the limit in reducing the energy cost of DCs, cloud service providers (SPs) is motivated to pursue a higher level cooperation. This paper investigates the optimal cross-SP workload balancing when it couples with the electricity markets. First we assume that there is a central operator (CO) coordinating the DCs owned by various SPs. A noncooperative game is formulated to model the interaction between utilities and CO which serves as a price maker. Under the centralized coordination of CO, an optimal solution is obtained with an iterative algorithm. Taking into account the computation and privacy issues, a decentralized algorithm is then proposed by utilizing techniques in state based potential game. Simulations using the Google workload trace show that the workload balancing among cross-SP DCs results in a lower DC operation cost than existing price-taker approach.

Original languageEnglish (US)
JournalIEEE Transactions on Control of Network Systems
DOIs
StateAccepted/In press - 2021

Bibliographical note

Publisher Copyright:
IEEE

Keywords

  • cloud service provider
  • decentralized coordination
  • electricity market
  • marker power

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