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Scientific Programming
Volume 2016, Article ID 7609460, 13 pages
Research Article

A Dynamic Pricing Reverse Auction-Based Resource Allocation Mechanism in Cloud Workflow Systems

1School of Computer Science and Technology, Anhui University, Hefei, China
2School of Software and Electrical Engineering, Swinburne University of Technology, Melbourne, Australia
3School of Information Technology, Deakin University, Melbourne, Australia

Received 22 July 2016; Accepted 3 October 2016

Academic Editor: Wenbing Zhao

Copyright © 2016 Xuejun Li et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [4 citations]

The following is the list of published articles that have cited the current article.

  • M. Vishalatchi, N. Krishnamoorthy, and S. Sangeetha, “Optimised scheduling in cloud computing,” 2017 International Conference on Algorithms, Methodology, Models and Applications in Emerging Technologies (ICAMMAET), pp. 1–6, . View at Publisher · View at Google Scholar
  • Nima Jafari Navimipour, and Fereshteh Sheikholeslami, “Auction-based resource allocation mechanisms in the cloud environments: A review of the literature and reflection on future challenges,” Concurrency Computation , vol. 30, no. 16, 2018. View at Publisher · View at Google Scholar
  • Branka Mikavica, and Aleksandra Kostic-Ljubisavljevic, “Pricing and bidding strategies for cloud spot block instances,” 2018 41st International Convention on Information and Communication Technology, Electronics and Microelectronics, MIPRO 2018 - Proceedings, pp. 384–389, 2018. View at Publisher · View at Google Scholar
  • Gokulraj, and Geetha, “Integration of firefly optimization and Pearson service correlation for efficient cloud resource utilization,” International Journal of Communication Systems, vol. 31, no. 15, 2018. View at Publisher · View at Google Scholar