An Equilibratory Market-Based Approach for Distributed Resource Allocation and Its Applications to Communication Network Control

Kuwabara, Kazuhiro; Ishida, Toru; Nishibe, Yoshiyasu; Suda, Takafumi

doi:10.1142/9789814261371_0003

Cited by 29 publications

(28 citation statements)

References 10 publications

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“…Kuwabara et al [34] propose an application of a posted-offer market to decentralised computational systems, observing the quantities provided at the equilibria at which the markets arrive. No central component, such as an auctioneer or specialist is used; prices are determined privately by the sellers and then posted via a broadcast mechanism.…”

Section: Decentralised Market Mechanismsmentioning

confidence: 99%

“…As in human retail markets, key to the efficiency of the posted-offer market in Kuwabara et al [34] is the assumption of iterated transactions. For example, where a large number of buyers arrive over a period of time, each seller is able to adapt its price such that the payoff from its transactions is maximised.…”

Section: Adaptive and Evolutionary Pricingmentioning

confidence: 99%

“…Critically however, though the sellers in Kuwabara et al's [34] system are non-cooperative, they are not self-interested, since they do not consider their payoff when determining their price. Instead, a seller node's previous usage is encoded directly as the seller's next price.…”

Section: Adaptive and Evolutionary Pricingmentioning

confidence: 99%

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Resource allocation in decentralised computational systems: an evolutionary market-based approach

Lewis

Marrow

Yao

2009

Auton Agent Multi-Agent Syst

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We present a novel market-based method, inspired by retail markets, for resource allocation in fully decentralised systems where agents are self-interested. Our market mechanism requires no coordinating node or complex negotiation. The stability of outcome allocations, those at equilibrium, is analysed and compared for three buyer behaviour models. In order to capture the interaction between self-interested agents, we propose the use of competitive coevolution. Our approach is both highly scalable and may be tuned to achieve specified outcome resource allocations. We demonstrate the behaviour of our approach in simulation, where evolutionary market agents act on behalf of service providing nodes to adaptively price their resources over time, in response to market conditions. We show that this leads the system to the predicted outcome resource allocation. Furthermore, the system remains stable in the presence of small changes in price, when buyers' decision functions degrade gracefully.

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Section: Decentralised Market Mechanismsmentioning

confidence: 99%

Section: Adaptive and Evolutionary Pricingmentioning

confidence: 99%

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Resource allocation in decentralised computational systems: an evolutionary market-based approach

Lewis

Marrow

Yao

2009

Auton Agent Multi-Agent Syst

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“…Market-oriented algorithms have been applied successfully towards solving complex resource allocation problems such as distributed multi-commodity flow in the trucking industry (Wellman 1993(Wellman , 1996, query processing and data migration in a distributed database (Stonebraker et al 1994), task scheduling in a distributed operating system (Huberman 1995, Malone et al 1988, Miller and Drexler 1988, network and file system resource allocation (Ferguson et al 1988, Gagliano and Mitchem 1996, Kurose and Simha 1989, Kuwabara et al 1996, Miller et al 1996, and Yemini 1981, allocating tradeable pollution permits (Marron and Bartels 1996), task allocation in discrete manufacturing systems (Baker 1996, Tilley 1996, and load balancing in distributed systems (Ferguson et al 1996). Most of the current research has focused on developing one of two types of economic models.…”

Section: Market Applicationsmentioning

confidence: 99%

Approximating the 0–1 Multiple Knapsack Problem with Agent Decomposition and Market Negotiation

Smolinski

2000

Intelligent Problem Solving. Methodologies and Approaches

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The 0-1 multiple knapsack problem appears in many domains from financial portfolio management to cargo ship stowing. Methods for solving it range from approximate algorithms, such as greedy algorithms, to exact algorithms, such as branch and bound. Approximate algorithms have no bounds on how poorly they perform and exact algorithms can suffer from exponential time and space complexities with large data sets. This paper introduces a market model based on agent decomposition and market auctions for approximating the 0-1 multiple knapsack problem, and an algorithm that implements the model (M(x)). M(x) traverses the solution space rather than getting caught in a local maximum, overcoming an inherent problem of many greedy algorithms. The use of agents ensures that infeasible solutions are not considered while traversing the solution space and that traversal of the solution space is not just random, but is also directed. M(x) is compared to a bound and bound algorithm (BB) and a simple greedy algorithm with a random shuffle (G(x)). The results suggest that M(x) is a good algorithm for approximating the 0-1 Multiple Knapsack problem. M(x) almost always found solutions that were close to optimal in a fraction of the time it took BB to run and with much less memory on large test data sets. M(x) usually performed better than G(x) on hard problems with correlated data.

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“…Furthermore, the research is more focused on efficiently distributing the control of network resources, than on automating the potential of selling Telecom services through the use virtual market-places. Kubawara, et al developed a market model for multi-agent resource allocation [7]. In their market, Activity-Agents (the buyers) and Resource-Agents (the sellers) of the network resources trade bandwidth on physical ATM links, i.e., ATM channels.…”

Section: Introductionmentioning

confidence: 99%

Market-Skilled Agents for Automating the Bandwidth Commerce

Calisti

Faltings

Mazziotta

2000

Trends in Distributed Systems: Towards a Universal Service Market

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Abstract. In the current deregulated Telecom scenario the number of network operators and service providers is rapidly increasing. The resulting competition generates the need for a flexible resource management. In parallel, the fast growth of electronic commerce opens a new market where operators can offer network bandwidth commodities. In this dynamic context, the traditional architecture of Telecom networks needs to be evolved. The integration of economic principles with software technology is a strategic contribution to this evolution. In particular, market-skilled software agents seem to be one of the most promising paradigms. In this paper we describe an agent-based system for the e-commerce of "IP bandwidth", and we discuss how the integration of this system within a network management platform would automate the advertisement of Telecom goods, the monitoring of market trends, the pricing and the configuration of network resources.

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An Equilibratory Market-Based Approach for Distributed Resource Allocation and Its Applications to Communication Network Control

Cited by 29 publications

References 10 publications

Resource allocation in decentralised computational systems: an evolutionary market-based approach

Resource allocation in decentralised computational systems: an evolutionary market-based approach

Approximating the 0–1 Multiple Knapsack Problem with Agent Decomposition and Market Negotiation

Market-Skilled Agents for Automating the Bandwidth Commerce

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