Abstract
The design and simulation of an agent processing platform suitable for distributed computing in heterogeneous sensor networks consisting of low-resource nodes is presented, providing a unique distributed programming model and enhanced robustness of the entire heterogeneous environment in the presence of node, sensor, link, data processing, and communication failures. In this work multi-agent systems with mobile activity-based agents are used for sensor data processing in unreliable mesh-like networks of nodes, consisting of a single microchip with limited low computational resources, which can be integrated into materials and technical structures. The agent behaviour, based on an activity-transition graph model, the interaction, and mobility can be efficiently integrated on the microchip using a configurable pipelined multi-process architecture based on the Petri-Net model and token-based processing. A new sub-state partitioning of activities simplifies and optimizes the processing platform significantly. Additionally, software implementations and simulation models with equal functional behaviour can be derived from the same program source. Hardware, software, and simulation platforms can be directly connected in heterogeneous networks. Agent interaction and communication is provided by a simple tuple-space database. A reconfiguration mechanism of the agent processing system offers activity graph changes at run-time. The suitability of the agent processing platform in large scale networks is demonstrated by using agent-based simulation of the platform architecture at process level with hundreds of nodes.
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Bosse, S. (2015). Design and Simulation of a Low-Resource Processing Platform for Mobile Multi-agent Systems in Distributed Heterogeneous Networks. In: Duval, B., van den Herik, J., Loiseau, S., Filipe, J. (eds) Agents and Artificial Intelligence. ICAART 2014. Lecture Notes in Computer Science(), vol 8946. Springer, Cham. https://doi.org/10.1007/978-3-319-25210-0_5
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DOI: https://doi.org/10.1007/978-3-319-25210-0_5
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