An overview on dynamic virtual machine provisioning using truthful greedy mechanisms in clouds

Cloud providers face so many decision problems when offering Infrastructure as a Service to their customers. A major challenging problem for cloud providers is scheming efficient mechanisms for virtual machine provisioning and allocation. Those mechanisms enable the cloud providers to effectively utilize their available resources and obtain higher profits. Freshly, cloud providers have introduced auction-based models for virtual machine provisioning and allocation which allow users to submit bids for their requested virtual machines. In this paper, dynamic virtual machine provisioning and allocation problem formulated for the auction-based model considering multiple types of resources. Then truthful greedy mechanisms designed for the problem such that the cloud provider provisions virtual machines based on the requests of the winning users and determines their payments. Proposed mechanisms are truthful, that is, the users do not have incentives to influence the system by lying about their requested bundles of virtual machine instances and their valuations. Proposed mechanisms will achieve promising results in terms of revenue for the cloud provider.

[1]  Xia Zhou,et al.  eBay in the Sky: strategy-proof wireless spectrum auctions , 2008, MobiCom '08.

[2]  Joseph Naor,et al.  A Truthful Mechanism for Value-Based Scheduling in Cloud Computing , 2013, Theory of Computing Systems.

[3]  Saswati Sarkar,et al.  Spectrum Auction Framework for Access Allocation in Cognitive Radio Networks , 2010, IEEE/ACM Transactions on Networking.

[4]  Barbara Panicucci,et al.  Generalized Nash Equilibria for the Service Provisioning Problem in Cloud Systems , 2013, IEEE Transactions on Services Computing.

[5]  Naixue Xiong,et al.  A game-theoretic method of fair resource allocation for cloud computing services , 2010, The Journal of Supercomputing.

[6]  Yoav Shoham,et al.  Truth revelation in approximately efficient combinatorial auctions , 2002, EC '99.

[7]  Athanasios V. Vasilakos,et al.  Heterogeneity playing key role: Modeling and analyzing the dynamics of incentive mechanisms in autonomous networks , 2012, TAAS.

[8]  Minyi Guo,et al.  Mechanism Design for Stochastic Virtual Resource Allocation in Non-cooperative Cloud Systems , 2011, 2011 IEEE 4th International Conference on Cloud Computing.

[9]  Daniel Grosu,et al.  Combinatorial Auction-Based Dynamic VM Provisioning and Allocation in Clouds , 2011, 2011 IEEE Third International Conference on Cloud Computing Technology and Science.

[10]  Xia Zhou,et al.  TRUST: A General Framework for Truthful Double Spectrum Auctions , 2009, IEEE INFOCOM 2009.

[11]  Valerio Di Valerio,et al.  Optimal Pricing and Service Provisioning Strategies in Cloud Systems: A Stackelberg Game Approach , 2013, 2013 IEEE Sixth International Conference on Cloud Computing.

[12]  Fan Wu,et al.  A Strategy-Proof Radio Spectrum Auction Mechanism in Noncooperative Wireless Networks , 2013, IEEE Transactions on Mobile Computing.

[13]  Daniel Grosu,et al.  Combinatorial Auction-Based Allocation of Virtual Machine Instances in Clouds , 2010, 2010 IEEE Second International Conference on Cloud Computing Technology and Science.

[14]  Noam Nisan,et al.  Truthful approximation mechanisms for restricted combinatorial auctions , 2008, Games Econ. Behav..

[15]  Mingyan Liu,et al.  Revenue generation for truthful spectrum auction in dynamic spectrum access , 2009, MobiHoc '09.

[16]  Tim Roughgarden,et al.  Algorithmic Game Theory , 2007 .