A Microeconomic Approach to Optimal Resource Allocation in Distributed Computer Systems
IEEE Transactions on Computers
Dynamic load balancing in parallel and distributed networks by random matchings (extended abstract)
SPAA '94 Proceedings of the sixth annual ACM symposium on Parallel algorithms and architectures
A market approach to operating system memory allocation
Market-based control
The dynamics of reinforcement learning in cooperative multiagent systems
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Reinforcement learning for call admission control and routing in integrated service networks
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
A game-theoretic formulation of multi-agent resource allocation
AGENTS '00 Proceedings of the fourth international conference on Autonomous agents
Communication decisions in multi-agent cooperation: model and experiments
Proceedings of the fifth international conference on Autonomous agents
Layered Learning in Multiagent Systems: A Winning Approach to Robotic Soccer
Layered Learning in Multiagent Systems: A Winning Approach to Robotic Soccer
Learning sequences of actions in collectives of autonomous agents
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 1
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Scheduling and Load Balancing in Parallel and Distributed Systems
Scheduling and Load Balancing in Parallel and Distributed Systems
An Agent-Based Approach for Scheduling Multiple Machines
Applied Intelligence
Multiagent Systems: A Survey from a Machine Learning Perspective
Autonomous Robots
Dynamic file-access characteristics of a production parallel scientific workload
Proceedings of the 1994 ACM/IEEE conference on Supercomputing
Computational Markets to Regulate Mobile-Agent Systems
Autonomous Agents and Multi-Agent Systems
TPOT-RL Applied to Network Routing
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Collective Intelligence and Braess' Paradox
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Load Balancing across Near-Homogeneous Multi-Resource Servers
HCW '00 Proceedings of the 9th Heterogeneous Computing Workshop
Coordinated Learning to Support Resource Management in Computational Grids
P2P '02 Proceedings of the Second International Conference on Peer-to-Peer Computing
Grid performance and resource management using mobile agents
Performance analysis and grid computing
The Grid 2: Blueprint for a New Computing Infrastructure
The Grid 2: Blueprint for a New Computing Infrastructure
A Swarm Based Approach for Task Allocation in Dynamic Agents Organizations
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 3
Towards Adaptive Workflow Enactment Using Multiagent Systems
Information Technology and Management
Cost sharing in a job scheduling problem using the Shapley value
Proceedings of the 6th ACM conference on Electronic commerce
Handling Communication Restrictions and Team Formation in Congestion Games
Autonomous Agents and Multi-Agent Systems
Resource management and organization in CROWN grid
InfoScale '06 Proceedings of the 1st international conference on Scalable information systems
A comparison between mechanisms for sequential compute resource auctions
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Towards self-organization in multi-agent systems and Grid computing
Multiagent and Grid Systems
Distributed agent-based air traffic flow management
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Efficient evaluation functions for evolving coordination
Evolutionary Computation
Analyzing and visualizing multiagent rewards in dynamic and stochastic domains
Autonomous Agents and Multi-Agent Systems
R-FRTDP: A Real-Time DP Algorithm with Tight Bounds for a Stochastic Resource Allocation Problem
CAI '07 Proceedings of the 20th conference of the Canadian Society for Computational Studies of Intelligence on Advances in Artificial Intelligence
An Infrastructure for Dynamic Composition of Grid Services
GRID '06 Proceedings of the 7th IEEE/ACM International Conference on Grid Computing
Reinforcement learning: a survey
Journal of Artificial Intelligence Research
Choosing a load balancing scheme for agent-based digital libraries
ISPA'06 Proceedings of the 4th international conference on Parallel and Distributed Processing and Applications
Ant colony system: a cooperative learning approach to the traveling salesman problem
IEEE Transactions on Evolutionary Computation
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Efficient management of large-scale job processing systems is a challenging problem, particularly in the presence of multi-users and dynamically changing system conditions. In addition, many real world systems require the processing of multi-resource jobs where centralized coordination may be difficult. Most conventional algorithms, such as load balancing, are designed for centralized, single resource problems. Indeed, in such a case, load balancing is known to provide optimal solutions. However, load balancing is not well suited to the more general, distributed, multi-resource allocation problem across heterogeneous networks that is frequently encountered in real world applications. Approaches based on heuristics can be designed to handle multi-resource allocation, but such approaches do not necessarily attempt to optimize directly a system-wide objective function. In this paper, we investigate a multiagent coordination approach to distributed, multi-resource job scheduling across heterogeneous servers. In this approach, agents at servers make local decisions to optimize an agent specific objective. The agent objectives though, are derived so that they are aligned with the overall efficiency of the system. We demonstrate that such a system outperforms (sometimes dramatically) more crudely constructed multiagent systems as well as a multi-resource version of load balancing.