A Decentralised Coordination Algorithm for Maximising Sensor Coverage in Large Sensor Networks

Stranders, Ruben, Rogers, Alex and Jennings, Nick (2010) A Decentralised Coordination Algorithm for Maximising Sensor Coverage in Large Sensor Networks. In, The Ninth International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2010), Toronto, Canada, 10 - 14 May 2010. , 1165-1172.


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In large wireless sensor networks, the problem of assigning radio frequencies to sensing agents such that no two connected sensors are assigned the same value (and will thus interfere with one another) is a major challenge. To tackle this problem, we develop a novel decentralised coordination algorithm that activates only a subset of the deployed agents, subject to the connectivity graph of this subset being provably 3-colourable in linear time, hence allowing the use of a simple decentralised graph colouring algorithm. Crucially, while doing this, our algorithm maximises the sensing coverage achieved by the selected sensing agents, which is given by an arbitrary non-decreasing submodular set function. We empirically evaluate our algorithm by benchmarking it against a centralised greedy algorithm and an optimal one, and show that the selected sensing agents manage to achieve 90% of the coverage provided by the optimal algorithm, and 85% of the coverage provided by activating all sensors. Moreover, we use a simple decentralised graph colouring algorithm to show the frequency assignment problem is easy in the resulting graphs; in all considered problem instances, this algorithm managed to ?nd a colouring in less than 5 iterations on average. We then show how the algorithm can be used in dynamic settings, in which sensors can fail or new sensors can be deployed. In this setting, our algorithm provides 250% more coverage over time compared to activating all available sensors simultaneously.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Event Dates: May 10-14, 2010
Divisions : Faculty of Physical Sciences and Engineering > Electronics and Computer Science > Agents, Interactions & Complexity
ePrint ID: 268465
Accepted Date and Publication Date:
Date Deposited: 03 Feb 2010 16:40
Last Modified: 31 Mar 2016 14:16
Further Information:Google Scholar
URI: http://eprints.soton.ac.uk/id/eprint/268465

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