Decentralised coordination of low-power embedded devices using the max-sum algorithm
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2
Good error-correcting codes based on very sparse matrices
IEEE Transactions on Information Theory
On the optimality of solutions of the max-product belief-propagation algorithm in arbitrary graphs
IEEE Transactions on Information Theory
Max/min-sum distributed constraint optimization through value propagation on an alternating DAG
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
Agent-based decentralised coordination for sensor networks using the max-sum algorithm
Autonomous Agents and Multi-Agent Systems
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A key challenge for the successful deployment of systems consisting of multiple autonomous networked sensors is the development of decentralised mechanisms to coordinate the activities of these physically distributed devices in order to achieve good system-wide performance. Such mechanisms must act in the presence of local constraints (such as limited power, communication and computational resources) and dynamic environments (where the topology, constraints and utility of the sensor network may change at any time). We propose the use of message passing techniques based on the max-sum algorithm to address this challenge, and in this paper, we demonstrate its use in two different settings. We first present a software simulation where our max-sum decentralised coordination algorithm is used to coordinate sectored radar sensors tracking multiple moving targets (see the ARGUS II DARP project - http://www.ecs.soton.ac.uk/research/projects/ARGUS). We then present a hardware implementation of the same algorithm that performs decentralised graph colouring - an intermediate step towards deploying the algorithm to coordinate the sleep/sense cycles of a network of low-power embedded sensors (see the DIF DTC 'Adaptive Energy-Aware Sensor Network' project - http://www.ecs.soton.ac.uk/research/projects/AEASN).