Turtles, termites, and traffic jams: explorations in massively parallel microworlds
Turtles, termites, and traffic jams: explorations in massively parallel microworlds
Anthill: A Framework for the Development of Agent-Based Peer-to-Peer Systems
ICDCS '02 Proceedings of the 22 nd International Conference on Distributed Computing Systems (ICDCS'02)
Coalition Formation for Large-Scale Electronic Markets
ICMAS '00 Proceedings of the Fourth International Conference on MultiAgent Systems (ICMAS-2000)
Agent-Based Load Balancing on Homogeneous Minigrids: Macroscopic Modeling and Characterization
IEEE Transactions on Parallel and Distributed Systems
Operating system multilevel load balancing
Proceedings of the 2006 ACM symposium on Applied computing
A peer-to-peer meta-scheduler for service-oriented grid environments
Proceedings of the first international conference on Networks for grid applications
A Space-Based Generic Pattern for Self-Initiative Load Balancing Agents
ESAW '09 Proceedings of the 10th International Workshop on Engineering Societies in the Agents World X
Characterizing autonomic task distribution and handling in grids
Engineering Applications of Artificial Intelligence
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We present a dynamic model of agent-based load balancing on grids. Our goal is to explore the effects of agents' strategies on the quality of load balancing. We show that under certain conditions, the model exhibits a known phenomenon that the load is perfectly balanced. This result is in agreement with recent experimental results on load balancing through Anthill. On the other hand, under general conditions, our model predicts unexpected phenomena that all the load balancing states tend to a unique steady state, where the load is not absolutely even balanced. The quality of load balancing, e.g., whether or not the load can be perfectly balanced, depends on agents' strategies. To measure the quality of load balancing, we define a total utility gain and further discuss the optimization of total utility gains.