Information-Based Control of Decentralised Sensor Networks
5. Discussion and Conclusions
Decentralised sensor networks are expected to be a cornerstone of future defence and security systems. They will need to operate over large areas, for long periods of time, with minimal human supervision. Some of the sensors will be stationary and placed at fixed locations in the area of interest; other sensors will be mobile and can visit multiple locations. The sensors may communicate, but the network topology is unlikely to be fixed or known, and the communication bandwidth will be limited. The operational modes of the sensors, their trajectories through the environment, and the information they exchange, are all control variables that may self-adapt to the local goals of individual sensors or to the global goal of the system
Figure 7. 3-D map used by the RoboCup Rescue simulator
at large. This is a control problem and it was described how formal measures of information provide a meaningful control basis in decentralised sensor networks.
The multi-agent systems methodology provides a framework and associated tools and techniques for enabling decentralised IBC in sensor networks. While statistics and sensor fusion are equipped with methods to manage uncertainty in these systems, and simple IBC methods can be used to control separate sensors, neither is able to promote the large-scale coordination that is required to maximise the performance of the full decentralised sensor network. However, multi-agent systems methods can usefully fill this gap and help design systems that must consider complex trade-offs in their decision-making. These methods are typically decentralised and deal with dynamism as well as a multiplicity of objectives, further increasing their appeal in the military and security domain.
This exciting field of research needs to develop in several ways. Theoreti- cally, it would be useful to develop a system-level understanding and analysis of cooperative feedback between networked sensor nodes. This would identify the key characteristics of networked sensing problems that benefit from cooperative solutions as well as quantifying the degree of cooperation that is required. Al- gorithmically, the focus should be on developing practical algorithms that are flexible and scalable in domains where there is dynamism, uncertainty of various forms, and stringent physical resource constraints. Finally, in terms of applica- tions, agent-based optimisation methods may offer novel perspectives on many other long-standing problems in networked sensor fusion systems, including sensor registration, data association, routing topologies for information products, rumour propagation, and decentralised situation assessment.
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Acknowledgment
The funding sources and research partner institutions referenced in Section 1.1 are acknowledged. The following colleagues have made significant contributions to the work described here: Peter Bladon, Chris Lloyd and Antony Waldock (BAE Systems); Salah Sukkarieh and David Cole (University of Sydney); Steve Reece (University of Oxford).
David Nicholson BAE SYSTEMS
Advanced Technology Centre Sowerby Building, PO Box 5 Filton, Bristol BS34 7QW United Kingdom
e-mail:[email protected] Sarvapali D. Ramchurn and Alex Rogers Electronics and Computer Science University of Southampton Highfield, Southampton, SO17 1BJ United Kingdom