King's College London

Research portal

Resource allocation based on double auction for cloud computing system

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

Lei Xu, Jun Wang, A. Nallanathan, Yaping Li

Original languageEnglish
Title of host publicationProceedings - 18th IEEE International Conference on High Performance Computing and Communications, 14th IEEE International Conference on Smart City and 2nd IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1538-1543
Number of pages6
ISBN (Print)9781509042968
DOIs
Publication statusPublished - 20 Jan 2017
Event18th IEEE International Conference on High Performance Computing and Communications, 14th IEEE International Conference on Smart City and 2nd IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2016 - Sydney, Australia
Duration: 12 Dec 201614 Dec 2016

Conference

Conference18th IEEE International Conference on High Performance Computing and Communications, 14th IEEE International Conference on Smart City and 2nd IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2016
CountryAustralia
CitySydney
Period12/12/201614/12/2016

King's Authors

Abstract

Cloud computing is a new commercial model with distributed computing, utility computing, and grid computing. In many situations, both the cloud service providers (CSPs) and cloud service users maximize their earnings. Consequently, how to resolve the resource allocation and determine the transaction pricing between CSPs and users is a big challenge. In this paper, we propose a double auction-based cloud resource allocation and pricing model, which improves the auction efficiency. In this model, the profit of the middle auctioneer is taken into consideration, and a reliability mechanism is added to the model. The price for the CSPs is designed based on the resource price and the reliability index. Finally, a resource allocation algorithm is proposed. Simulation results demonstrate that the proposed algorithm reduces the number of auction rounds, and improves the auction efficiency very well.

View graph of relations

© 2018 King's College London | Strand | London WC2R 2LS | England | United Kingdom | Tel +44 (0)20 7836 5454