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Constrained Bandwidth Allocation in Multi-Sensor Information Fusion: A Mechanism Design Approach

Constrained Bandwidth Allocation in Multi-Sensor Information Fusion: A Mechanism Design Approach
Constrained Bandwidth Allocation in Multi-Sensor Information Fusion: A Mechanism Design Approach
Sensor networks are increasingly seen as a solution for a large number of environmental, security and military monitoring tasks. Typically, in these networks, noisy data from a number of local sensors is fused to reduce the uncertainty in the global picture. A central issue in this information fusion is the decision of what data should be shared between sensors, in order to maximise the global gain in information, when the bandwidth of the communication network is limited. In this paper, we study the problem from a selfish agent perspective. We show how the uncertainty in the measurement of an event can be cast as a utility function derived from the Kalman filter. We then use the tools of mechanism design to engineer an incentivecompatible mechanism that allows rational selfish agents to individually maximise their own utility, whilst ensuring that the overall utility of the system is also maximised. We apply the mechanism to multi-sensor target detection and consider the complexity of finding an efficient solution with broadcast communication protocols.
Dash, Rajdeep
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Rogers, Alex
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Reece, Steve
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Roberts, Stephen
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Jennings, N. R.
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Dash, Rajdeep
6c83d6ec-5b7d-4fd9-ab62-0394a8181ff4
Rogers, Alex
f9130bc6-da32-474e-9fab-6c6cb8077fdc
Reece, Steve
9eecf0b5-3207-4067-9b72-6abcea5b54ab
Roberts, Stephen
fef5d01c-92bd-44cf-93f0-923ec24f8875
Jennings, N. R.
ab3d94cc-247c-4545-9d1e-65873d6cdb30

Dash, Rajdeep, Rogers, Alex, Reece, Steve, Roberts, Stephen and Jennings, N. R. (2005) Constrained Bandwidth Allocation in Multi-Sensor Information Fusion: A Mechanism Design Approach. The Eighth International Conference on Information Fusion (Fusion 2005), United States.

Record type: Conference or Workshop Item (Paper)

Abstract

Sensor networks are increasingly seen as a solution for a large number of environmental, security and military monitoring tasks. Typically, in these networks, noisy data from a number of local sensors is fused to reduce the uncertainty in the global picture. A central issue in this information fusion is the decision of what data should be shared between sensors, in order to maximise the global gain in information, when the bandwidth of the communication network is limited. In this paper, we study the problem from a selfish agent perspective. We show how the uncertainty in the measurement of an event can be cast as a utility function derived from the Kalman filter. We then use the tools of mechanism design to engineer an incentivecompatible mechanism that allows rational selfish agents to individually maximise their own utility, whilst ensuring that the overall utility of the system is also maximised. We apply the mechanism to multi-sensor target detection and consider the complexity of finding an efficient solution with broadcast communication protocols.

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More information

Published date: 2005
Additional Information: Event Dates: July 2005
Venue - Dates: The Eighth International Conference on Information Fusion (Fusion 2005), United States, 2005-07-01
Organisations: Agents, Interactions & Complexity

Identifiers

Local EPrints ID: 260866
URI: https://eprints.soton.ac.uk/id/eprint/260866
PURE UUID: 8e2ebac9-021a-43fa-8078-35e02248c4e4

Catalogue record

Date deposited: 14 May 2005
Last modified: 09 Sep 2019 18:55

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Contributors

Author: Rajdeep Dash
Author: Alex Rogers
Author: Steve Reece
Author: Stephen Roberts
Author: N. R. Jennings

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