Performance evaluation of distributed self-stabilizing dominating set algorithms in wireless sensor networks

Finding a minimal dominating set (MDS) is a popular problem in wireless sensor networks (WSNs) to provide routing and backbone formation. A self-stabilizing system can tolerate topological changes such as node and edge joining/leaving thus they are very suitable for fault-tolerant and reliable WSNs. In this paper, we provide an extensive performance evaluation of self-stabilizing MDS algorithms for WSNs. To the best of our knowledge, this is the first experimental evaluation study of self-stabilizing MDS algorithms applied in WSN domain. We implemented the algorithms on various node counts and densities, and compared the average energy consumption, wall- clock time, move count and dominator count of the algorithms. The comprehensive simulation results show that the Goddard's algorithm finds the MDS with about 8.8% lower move and 5.8% lower dominator node count while its theoretical move count bound is higher than Chiu's algorithm. Despite of lower move count, the simulation results shows that the energy consumption of Goddard's algorithm is up to 1.5 times higher than Turau's and 2.8 times higher than Chiu's algorithms. The wallclock time, move count and detected dominator count of Turau's algorithm are respectively 84%, 88% and 12% higher than Goddard's algorithm in the networks with 1500 nodes which confirms its 9n move count bound. These measurements reveal that Goddard's algorithm outperforms other algorithms in terms of dominator count and Chiu's algorithm has a better performance for other metrics.