In this paper, we consider the self-organisation of sensors within a network deployed for wide area surveillance. We present a decentralised coordination algorithm based upon the max-sum algorithm and demonstrate how self-organisation can be achieved within a setting where sensors are deployed with no a priori information regarding their local environment. These energy-constrained sensors first learn how their actions interact with those of neighbouring sensors, and then use the max-sum algorithm to coordinate their sense/sleep schedules in order to maximise the effectiveness of the sensor network as a whole. In a simulation we show that this approach yields a 30% reduction in the number of vehicles that the sensor network fails to detect (compared to an uncoordinated network), and this performance is close to that achieved by a benchmark centralised optimisation algorithm (simulated annealing)

Self-organising Sensors for Wide Area Surveillance Using the Max-sum Algorithm

FARINELLI, Alessandro;
2010-01-01

Abstract

In this paper, we consider the self-organisation of sensors within a network deployed for wide area surveillance. We present a decentralised coordination algorithm based upon the max-sum algorithm and demonstrate how self-organisation can be achieved within a setting where sensors are deployed with no a priori information regarding their local environment. These energy-constrained sensors first learn how their actions interact with those of neighbouring sensors, and then use the max-sum algorithm to coordinate their sense/sleep schedules in order to maximise the effectiveness of the sensor network as a whole. In a simulation we show that this approach yields a 30% reduction in the number of vehicles that the sensor network fails to detect (compared to an uncoordinated network), and this performance is close to that achieved by a benchmark centralised optimisation algorithm (simulated annealing)
978-364214411-0
Decentralised Coordination; Self-Organising Sensors; Multi-agent Systems
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11562/346582
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