Approximate-Centroid Election In Large-Scale Distributed Embedded Systems
Résumé
Many distributed algorithms require a specific role to be played by a leader, a single node in the system. The choice of this node often has a direct impact on the performance. In particular, selecting a central node as the leader can significantly improve algorithm efficiency. Classical distributed algorithms require global information about the connectivity network to elect a centroid node. Thus, they are not suitable for large-scale distributed embedded systems with scarce computation, memory and energy resources. We present \algoNameNoSpace, an Effective and Efficient Approximate-Centroid Election algorithm that uses $O(1)$ memory space per node, $O(d)$ time and $O(mn^2)$ messages of size $O(1)$, where $n$ is the number of nodes, $m$ the number of connections and $d$ the diameter of the system. We evaluate our algorithm on the Blinky Blocks system using simulations. Experimental results show that \algoName scales well in terms of accuracy, execution time and number of messages. We show that \algoName is more accurate than the only existing algorithm with similar complexity results.