Hierarchical neighbor graphs: A fully distributed topology for data collection in wireless sensor networks

We introduce hierarchical neighbor graphs, a new topology control mechanism for wireless sensor networks. This mechanism is a randomized one that takes a single parameter, 0 < p < 1, and uses it to build a structure that has the flavor of hierarchical clustering and is fully distributed in the sense that it requires only local knowledge at each node to be formed and repaired, and moreover requires minimal computation in this process. Hierarchical neighbor graphs naturally account for differences in the battery power of nodes and are able to use energy efficiently by reorganizing dynamically–without any global coordination or communication–when the battery power of heavily utilized nodes decreases. In this paper we study the lifetime and delay of hierarchical neighbor graphs, giving analytical characterizations of both. We perform simulations to demonstrate the sensitivity of the lifetime and delay to the number of nodes in the network and the parameter p, also studying the tradeoff between these two quantities and the effects of application-specific data aggregation policies. Through extensive simulations we compare hierarchical neighbor graphs against other leading proposals for data collection in wireless sensor networks and demonstrate that in general our structure provides better lifetime values than most other structures, and, importantly, is able to deal with heterogeneous distributions of initial battery power much better than previous proposals.