Issue No.02 - July-December (2013 vol.1)
Sharrukh Zaman , Wayne State University, Detroit
Daniel Grosu , Wayne State University, Detroit
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TCC.2013.9
Cloud computing providers provision their resources into different types of virtual machine (VM) instances that are then allocated to the users for specific periods of time. The allocation of VM instances to users is usually determined through fixed-price allocation mechanisms that cannot guarantee an economically efficient allocation and the maximization of cloud provider's revenue. A better alternative would be to use combinatorial auction-based resource allocation mechanisms. This argument is supported by the economic theory; when the auction costs are low, as is the case in the context of cloud computing, auctions are especially efficient over the fixed-price markets because products are matched to customers having the highest valuation. The existing combinatorial auction-based VM allocation mechanisms do not take into account the user's demand when making provisioning decisions, that is, they assume that the VM instances are statically provisioned. We design an auction-based mechanism for dynamic VM provisioning and allocation that takes into account the user demand, when making provisioning decisions. We prove that our mechanism is truthful (i.e., a user maximizes its utility only by bidding its true valuation for the requested bundle of VMs). We evaluate the proposed mechanism by performing extensive simulation experiments using real workload traces. The experiments show that the proposed mechanism yields higher revenue for the cloud provider and improves the utilization of cloud resources.
Resource management, Dynamic scheduling, Cost accounting, Computational modeling, Virtual machining, Cloud computing,combinatorial auctions, Cloud computing, VM allocation, VM provisioning, dynamic resource configuration
Sharrukh Zaman, Daniel Grosu, "A Combinatorial Auction-Based Mechanism for Dynamic VM Provisioning and Allocation in Clouds", IEEE Transactions on Cloud Computing, vol.1, no. 2, pp. 129-141, July-December 2013, doi:10.1109/TCC.2013.9