Market-based pricing in grids: On strategic manipulation and computational cost

Grid technologies and the related concepts of utility computing and cloud computing enable the dynamic sourcing of computer resources and services, thus allowing enterprises to cut down on hardware and software expenses and to focus on key competencies and processes. Resources are shared across administrative boundaries, e.g. between enterprises and/or business units. In this dynamic and inter-organizational setting, scheduling and pricing become key challenges. Market mechanisms show promise for enhancing resource allocation and pricing in grids. Current mechanisms, however, are not adequately able to handle large-scale settings with strategic users and providers who try to benefit from manipulating the mechanism. In this paper, a market-based heuristic for clearing large-scale grid settings is developed. The proposed heuristic and pricing schemes find an interesting match between scalability and strategic behavior.

[1]  Leigh Tesfatsion,et al.  Handbook of Computational Economics, Volume 2: Agent-Based Computational Economics (Handbook of Computational Economics) , 2006 .

[2]  Ami Marowka,et al.  What is the GRID? , 2002, Scalable Comput. Pract. Exp..

[3]  Philip H. Ramsey Exact Type 1 Error Rates for Robustness of Student's t Test with Unequal Variances , 1980 .

[4]  Dirk Neumann,et al.  Trading grid services - a multi-attribute combinatorial approach , 2008, Eur. J. Oper. Res..

[5]  D. Atkin OR scheduling algorithms. , 2000, Anesthesiology.

[6]  A. Mas-Colell,et al.  Microeconomic Theory , 1995 .

[7]  Sartaj Sahni,et al.  Approximate Algorithms for the 0/1 Knapsack Problem , 1975, JACM.

[8]  Leigh Tesfatsion,et al.  Agent-Based Computational Economics: Growing Economies From the Bottom Up , 2002, Artificial Life.

[9]  David E. Culler,et al.  Market-based Proportional Resource Sharing for Clusters , 2000 .

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

[11]  ParsonsSimon,et al.  Evolutionary mechanism design , 2010 .

[12]  Mor Harchol-Balter,et al.  Exploiting process lifetime distributions for dynamic load balancing , 1995, SIGMETRICS.

[13]  Stephen George Phelps,et al.  Evolutionary Mechanism Design , 2007 .

[14]  L. Hurwicz On informationally decentralized systems , 1977 .

[15]  Rudolf Müller,et al.  Decentralization and Mechanism Design for Online Machine Scheduling , 2006, SWAT.

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

[17]  David C. Parkes,et al.  Achieving Budget-Balance with Vickrey-Based Payment Schemes in Combinatorial Exchanges , 2001 .

[18]  Craig Boutilier,et al.  Bidding Languages for Combinatorial Auctions , 2001, IJCAI.

[19]  Jan Stallaert,et al.  A Market Design for Grid Computing , 2008, INFORMS J. Comput..

[20]  N. Carr The end of corporate computing , 2005 .

[21]  Lior Amar,et al.  The Power of Preemption in Economic Online Markets , 2008, GECON.

[22]  Jeffrey D. Ullman,et al.  Worst-Case Performance Bounds for Simple One-Dimensional Packing Algorithms , 1974, SIAM J. Comput..

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

[24]  Mark A. Satterthwaite,et al.  The Bayesian theory of the k-double auction: Santa Fe Institute Studies in the Sciences of Complexity , 2018 .

[25]  M. Satterthwaite,et al.  Efficient Mechanisms for Bilateral Trading , 1983 .

[26]  Sanjeev Khanna,et al.  A PTAS for the multiple knapsack problem , 2000, SODA '00.

[27]  D. J. Roberts,et al.  THE INCENTIVES FOR PRICE-TAKING BEHAVIOR IN LARGE EXCHANGE ECONOMIES , 1976 .

[28]  Dror G. Feitelson,et al.  Workload Modeling for Performance Evaluation , 2002, Performance.

[29]  David C. Parkes,et al.  Iterative combinatorial auctions: achieving economic and computational efficiency , 2001 .

[30]  Paolo Toth,et al.  Knapsack Problems: Algorithms and Computer Implementations , 1990 .

[31]  R. Blair,et al.  A more realistic look at the robustness and Type II error properties of the t test to departures from population normality. , 1992 .

[32]  Yoav Shoham,et al.  Combinatorial Auctions , 2005, Encyclopedia of Wireless Networks.

[33]  Amin Vahdat,et al.  Why Markets Could (But Don't Currently) Solve Resource Allocation Problems in Systems , 2005, HotOS.

[34]  M. Wellman,et al.  Automated Markets and Trading Agents , 2007 .

[35]  Dirk Neumann,et al.  Harnessing migrations in a market-based grid OS , 2008, 2008 9th IEEE/ACM International Conference on Grid Computing.

[36]  Kevin Lai,et al.  Markets are dead, long live markets , 2005, SECO.

[37]  Tad Hogg,et al.  Spawn: A Distributed Computational Economy , 1992, IEEE Trans. Software Eng..

[38]  Noam Nisan,et al.  The POPCORN market. Online markets for computational resources , 2000, Decis. Support Syst..

[39]  Noam Nisan,et al.  Towards a characterization of truthful combinatorial auctions , 2003, 44th Annual IEEE Symposium on Foundations of Computer Science, 2003. Proceedings..

[40]  Sanjeev Khanna,et al.  A Polynomial Time Approximation Scheme for the Multiple Knapsack Problem , 2005, SIAM J. Comput..

[41]  Li Zhang,et al.  Tycoon: An implementation of a distributed, market-based resource allocation system , 2004, Multiagent Grid Syst..

[42]  Amin Vahdat,et al.  Resource Allocation in Federated Distributed Computing Infrastructures , 2004 .

[43]  Sven de Vries,et al.  Combinatorial Auctions: A Survey , 2003, INFORMS J. Comput..

[44]  David Levine,et al.  CABOB: A Fast Optimal Algorithm for Winner Determination in Combinatorial Auctions , 2005, Manag. Sci..