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Issue No.01 - Jan. (2013 vol.24)
pp: 72-84
Kyle Chard , University of Chicago and Argonne National Laboratory, Chicago
Kris Bubendorfer , Victoria University of Wellington, Wellington
ABSTRACT
Utility computing models have long been the focus of academic research, and with the recent success of commercial cloud providers, computation and storage is finally being realized as the fifth utility. Computational economies are often proposed as an efficient means of resource allocation, however adoption has been limited due to a lack of performance and high overheads. In this paper, we address the performance limitations of existing economic allocation models by defining strategies to reduce the failure and reallocation rate, increase occupancy and thereby increase the obtainable utilization of the system. The high-performance resource utilization strategies presented can be used by market participants without requiring dramatic changes to the allocation protocol. The strategies considered include overbooking, advanced reservation, just-in-time bidding, and using substitute providers for service delivery. The proposed strategies have been implemented in a distributed metascheduler and evaluated with respect to Grid and cloud deployments. Several diverse synthetic workloads have been used to quantity both the performance benefits and economic implications of these strategies.
INDEX TERMS
Resource management, Economics, Contracts, Biological system modeling, Computer architecture, Protocols, Pricing, Grid computing, Economic resource allocation, utility computing, cloud computing
CITATION
Kyle Chard, Kris Bubendorfer, "High Performance Resource Allocation Strategies for Computational Economies", IEEE Transactions on Parallel & Distributed Systems, vol.24, no. 1, pp. 72-84, Jan. 2013, doi:10.1109/TPDS.2012.102
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