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 fin 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.
['Ruben Stranders', 'Alexander Carl Rogers', 'Nicholas R. Jennings']
A decentralised coordination algorithm for minimising conflict and maximising coverage in sensor networks