Actors: a model of concurrent computation in distributed systems
Actors: a model of concurrent computation in distributed systems
Design of dynamic load-balancing tools for parallel applications
Proceedings of the 14th international conference on Supercomputing
MACE3J: fast flexible distributed simulation of large, large-grain multi-agent systems
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 2
On Load Balancing for Distributed Multiagent Computing
IEEE Transactions on Parallel and Distributed Systems
A Bytecode Translator for Distributed Execution of ``Legacy'' Java Software
ECOOP '01 Proceedings of the 15th European Conference on Object-Oriented Programming
J-Orchestra: Automatic Java Application Partitioning
ECOOP '02 Proceedings of the 16th European Conference on Object-Oriented Programming
Adapting to Load on Workstation Clusters
FRONTIERS '99 Proceedings of the The 7th Symposium on the Frontiers of Massively Parallel Computation
A Load Balancing Framework for Adaptive and Asynchronous Applications
IEEE Transactions on Parallel and Distributed Systems
Load Balancing of Autonomous Actors over Dynamic Networks
HICSS '04 Proceedings of the Proceedings of the 37th Annual Hawaii International Conference on System Sciences (HICSS'04) - Track 9 - Volume 9
ATSpace: A Middle Agent to Support Application Oriented Matchmaking and Brokering Services
IAT '04 Proceedings of the IEEE/WIC/ACM International Conference on Intelligent Agent Technology
Parallel simulation of a stochastic agent/environment interaction model
Integrated Computer-Aided Engineering
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Although distributed computing is necessary to execute massively multi-agent applications, the distribution of agents is challenging especially when the communication patterns among agents are continuously changing. This paper proposes two adaptive agent allocation mechanisms for massively multi-agent applications: one mechanism aims at minimizing agent communication cost, while the other mechanism attempts to prevent overloaded computer nodes from negatively affecting overall performance. We synthesize these two mechanisms in a multi-agent framework called Adaptive Actor Architecture (AAA). In AAA, each agent platform monitors the workload of its computer node and the communication patterns of agents executing on it. An agent platform periodically reallocates agents according to their communication localities. When an agent platform is overloaded, the platform migrates a set of agents, which have more intra-group communication than inter-group or inter-node communication, to a lightly loaded agent platform. These adaptive agent allocation mechanisms are developed as fully distributed algorithms, and they move the selected agents as a group. In order to evaluate these mechanisms, preliminary experimental results with large-scale micro UAV (Unmanned Aerial Vehicle) simulations are described.