Towards green cloud computing: Demand allocation and pricing policies for cloud service brokerage

Chenxi Qiu, Haiying Shen, Liuhua Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Scopus citations

Abstract

Functioning as an intermediary between tenants and cloud providers, cloud service brokerages (CSBs) can bring about great benefits to the cloud market. CSBs buy the cloud resources, i.e., servers, with lower prices from cloud providers and sell the resources to the tenants with higher prices. To maximize its own profit, a CSB may distribute tenants' requests to the clouds that waste energy resources. However, as energy costs of cloud computing have been increasing rapidly, there is a need for cloud providers to optimize energy efficiency while maintain high service level performance to tenants, not only for their own benefit but also for social welfares (e.g., protecting environment). Thus, for green cloud companies, two questions have arisen: 1) under what pricing policies from the cloud providers to the CSB, a profit-driven CSB is willing to minimize the total cloud energy cost while satisfy tenant demands and 2) how should a CSB distribute tenants' demands to achieve this objective? To address question 1), we find a pricing policy for cloud providers such that maximizing CSB's profit is equivalent to minimizing cloud providers' energy cost. To address question 2), we first devise a greedy solution, and then propose an approximation algorithm with a constant approximation ratio. Both simulation and real-world Amazon EC2 experimental results demonstrate the effectiveness of our pricing policy to incentivize CSBs to save energy for cloud providers and the superior performance of our algorithms in energy efficiency and resource utilizations in comparison with the previous algorithms.

Original languageEnglish (US)
Title of host publicationProceedings - 2015 IEEE International Conference on Big Data, IEEE Big Data 2015
EditorsFeng Luo, Kemafor Ogan, Mohammed J. Zaki, Laura Haas, Beng Chin Ooi, Vipin Kumar, Sudarsan Rachuri, Saumyadipta Pyne, Howard Ho, Xiaohua Hu, Shipeng Yu, Morris Hui-I Hsiao, Jian Li
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages203-212
Number of pages10
ISBN (Electronic)9781479999255
DOIs
StatePublished - Dec 22 2015
Externally publishedYes
Event3rd IEEE International Conference on Big Data, IEEE Big Data 2015 - Santa Clara, United States
Duration: Oct 29 2015Nov 1 2015

Publication series

NameProceedings - 2015 IEEE International Conference on Big Data, IEEE Big Data 2015

Conference

Conference3rd IEEE International Conference on Big Data, IEEE Big Data 2015
Country/TerritoryUnited States
CitySanta Clara
Period10/29/1511/1/15

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems
  • Software

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