Market-based control: a paradigm for distributed resource allocation
Market-based control: a paradigm for distributed resource allocation
Server load balancing
Cactus Tools for Grid Applications
Cluster Computing
Condor-G: A Computation Management Agent for Multi-Institutional Grids
Cluster Computing
On Load Balancing for Distributed Multiagent Computing
IEEE Transactions on Parallel and Distributed Systems
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IEEE Transactions on Software Engineering
Resource allocation games with changing resource capacities
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Combining state and model-based approaches for mobile agent load balancing
Proceedings of the 2003 ACM symposium on Applied computing
Analyzing Market-Based Resource Allocation Strategies for the Computational Grid
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AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
An Agent-based Resource Allocation Model for computational grids
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NSDI'05 Proceedings of the 2nd conference on Symposium on Networked Systems Design & Implementation - Volume 2
Adaptive load balancing: a study in multi-agent learning
Journal of Artificial Intelligence Research
Decentralized Co-allocation of Interrelated Resources in Dynamic Environments
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 02
An adaptive bidding strategy for combinatorial auction-based resource allocation in dynamic markets
PRICAI'10 Proceedings of the 11th Pacific Rim international conference on Trends in artificial intelligence
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ACM Transactions on Autonomous and Adaptive Systems (TAAS) - Special section on formal methods in pervasive computing, pervasive adaptation, and self-adaptive systems: Models and algorithms
Improving self-organized resource allocation with effective communication
AP2PC'08 Proceedings of the 7th international conference on Agents and Peer-to-Peer Computing
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Distributed applications require distributed techniques for efficient resource allocation. These techniques need to take into account the heterogeneity and potential unreliability of resources and resource consumers in a distributed environments. In this paper we propose a distributed algorithm that solves the resource allocation problem in distributed multi-agent systems. Our solution is based on the self-organisation of agents, which does not require any facilitator or management layer. The resource allocation in the system is a purely emergent effect. We present results of the proposed resource allocation mechanism in the simulated static and dynamic multi-server environment.