Auction Protocols for Decentralized Scheduling

Scheduling is the problem of allocating resources to alternate possible uses over designated periods of time. Several have proposed (and some have tried) market-based approaches to decentralized versions of the problem, where the competing uses are represented by autonomous agents. Market mechanisms use prices derived through distributed bidding protocols to determine an allocation, and thus solve the scheduling problem. To analyze the behavior of market schemes, we formalize decentralized scheduling as a discrete resource allocation problem, and bring to bear some relevant economic concepts. Drawing on results from the literature, we discuss the existence of equilibrium prices for some general classes of scheduling problems, and the quality of equilibrium solutions. To remedy the potential nonexistence of price equilibria due to complementarities in preference, we introduce additional markets in combinations of basic goods. We present some auction mechanisms and bidding protocols corresponding to the two market structures, and analyze their computational and economic properties. Finally, we consider direct revelation mechanisms, and compare to the market-based approach.

[1]  Dimitri P. Bertsekas,et al.  Auction algorithms for network flow problems: A tutorial introduction , 1992, Comput. Optim. Appl..

[2]  A. D. Baker Metaphor or reality: a case study where agents BID with actual costs to schedule a factory , 1996 .

[3]  David C. Parkes,et al.  iBundle: an efficient ascending price bundle auction , 1999, EC '99.

[4]  J. Banks,et al.  Allocating uncertain and unresponsive resources: an experimental approach. , 1989, The Rand journal of economics.

[5]  Martin Shubik,et al.  The Assignment Game , 1971 .

[6]  Michael P. Wellman,et al.  Market-oriented programming: some early lessons , 1996 .

[7]  Michael P. Wellman,et al.  The Michigan Internet AuctionBot: a configurable auction server for human and software agents , 1998, AGENTS '98.

[8]  S. Bikhchandani,et al.  Competitive Equilibrium in an Exchange Economy with Indivisibilities , 1997 .

[9]  S. David Wu,et al.  On combinatorial auction and Lagrangean relaxation for distributed resource scheduling , 1999 .

[10]  Richard E. Neapolitan,et al.  Foundations of Algorithms , 1996 .

[11]  Michael Stonebraker,et al.  Mariposa: a wide-area distributed database system , 1996, The VLDB Journal.

[12]  R. Myerson Incentive Compatibility and the Bargaining Problem , 1979 .

[13]  Michael P. Wellman,et al.  Efficiency and Equilibrium in Task Allocation Economies with Hierarchical Dependencies , 1999, IJCAI.

[14]  Michael P. Wellman,et al.  A Parametrization of the Auction Design Space , 2001, Games Econ. Behav..

[15]  Jianxiu Hao,et al.  On algorithms for network flow problems , 1989 .

[16]  T. Ishida,et al.  A Trading Agent Competition for the Research Community , 1999 .

[17]  Ronald M. Harstad,et al.  Computationally Manageable Combinational Auctions , 1998 .

[18]  Pablo Noriega,et al.  Competitive scenarios for heterogeneous trading agents , 1998, AGENTS '98.

[19]  H. Leonard Elicitation of Honest Preferences for the Assignment of Individuals to Positions , 1983, Journal of Political Economy.

[20]  Michael P. Wellman,et al.  Distributed quiescence detection in multiagent negotiation , 2000, Proceedings Fourth International Conference on MultiAgent Systems.

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

[22]  Bernardo A. Huberman,et al.  The ecology of computation , 1988, Digest of Papers. COMPCON Spring 89. Thirty-Fourth IEEE Computer Society International Conference: Intellectual Leverage.

[23]  S. Rassenti,et al.  A Combinatorial Auction Mechanism for Airport Time Slot Allocation , 1982 .

[24]  Jerry R. Green,et al.  Incentives in public decision-making , 1979 .

[25]  L. Shapley,et al.  The assignment game I: The core , 1971 .

[26]  Faruk Gul,et al.  WALRASIAN EQUILIBRIUM WITH GROSS SUBSTITUTES , 1999 .

[27]  Yoav Shoham,et al.  Taming the Computational Complexity of Combinatorial Auctions: Optimal and Approximate Approaches , 1999, IJCAI.

[28]  Tracy Mullen,et al.  Market-Based Negotiation for Digital Library Services , 1996 .

[29]  Fredrik Ygge,et al.  Market-Oriented Programming and its Application to Power Load Management , 1998 .

[30]  William Vickrey,et al.  Counterspeculation, Auctions, And Competitive Sealed Tenders , 1961 .

[31]  S. Clearwater Market-based control: a paradigm for distributed resource allocation , 1996 .

[32]  Jeffrey K. MacKie-Mason,et al.  Generalized Vickrey Auctions , 1994 .

[33]  Tuomas Sandholm,et al.  An algorithm for optimal winner determination in combinatorial auctions , 1999, IJCAI 1999.

[34]  Faruk Gul,et al.  Walrasian Equilibrium Without Complementarities , 1997 .

[35]  Peter R. Wurman,et al.  Market structure and multidimensional auction design for computational economies , 1999 .

[36]  Michael P. Wellman A Market-Oriented Programming Environment and its Application to Distributed Multicommodity Flow Problems , 1993, J. Artif. Intell. Res..

[37]  J. Jordan The competitive allocation process is informationally efficient uniquely , 1982 .

[38]  Michael P. Wellman,et al.  A Simple Computational Market for Network Information Services , 1995, ICMAS.

[39]  William E. Weihl,et al.  Lottery scheduling: flexible proportional-share resource management , 1994, OSDI '94.

[40]  R. McAfee,et al.  Auctions and Bidding , 1986 .

[41]  E. H. Clarke Multipart pricing of public goods , 1971 .

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

[43]  Theodore Groves,et al.  Incentives in Teams , 1973 .

[44]  Paul R. Milgrom,et al.  Putting Auction Theory to Work: The Simultaneous Ascending Auction , 1999, Journal of Political Economy.

[45]  J. Davenport Editor , 1960 .

[46]  Hans Akkermans,et al.  Decentralized Markets versus Central Control: A Comparative Study , 1999, J. Artif. Intell. Res..

[47]  T. Koopmans,et al.  Assignment Problems and the Location of Economic Activities , 1957 .

[48]  C. Plott,et al.  The Allocation Of Scarce Resources: Experimental Economics And The Problem Of Allocating Airport Slots , 1989 .

[49]  Michael P. Wellman A computational market model for distributed configuration design , 1994, Artificial Intelligence for Engineering Design, Analysis and Manufacturing.

[50]  J. Ledyard,et al.  A NEW AND IMPROVED DESIGN FOR MULTI-OBJECT ITERATIVE AUCTIONS , 1999 .

[51]  D. Gale,et al.  Multi-Item Auctions , 1986, Journal of Political Economy.

[52]  V. Crawford,et al.  Job Matching, Coalition Formation, and Gross Substitutes , 1982 .

[53]  C. Plott,et al.  A BINARY CONFLICT ASCENDING PRICE (BICAP) MECHANISM FOR THE DECENTRALIZED ALLOCATION OF THE RIGHT TO USE RAILROAD TRACKS. , 1996 .

[54]  Rahul Simha,et al.  A Microeconomic Approach to Optimal Resource Allocation in Distributed Computer Systems , 1989, IEEE Trans. Computers.

[55]  Michael P. Wellman,et al.  A market protocol for decentralized task allocation , 1998, Proceedings International Conference on Multi Agent Systems (Cat. No.98EX160).

[56]  R. McAfee,et al.  Analyzing the Airwaves Auction , 1996 .

[57]  Arne Andersson,et al.  Integer programming for combinatorial auction winner determination , 2000, Proceedings Fourth International Conference on MultiAgent Systems.

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