Energy conservation via domatic partitions

• Authors: Sriram V. Pemmaraju;Imran A. Pirwani
• Venue: Proceedings of the 7th ACM international symposium on Mobile ad hoc networking and computing
• Year: 2006

Using a dominating set as a coordinator in wireless networks has been proposed in many papers as an energy conservation technique. Since the nodes in a dominating set have the extra burden of coordination, energy resources in such nodes will drain out more quickly than in other nodes. To maximize the lifetime of nodes in the network,it has been proposed that the role of coordinators be rotated among the nodes in the network. One abstraction that has been considered for the problem of picking a collection of coordinators and cycling through them, is the domatic partition problem. This is the problem of partitioning the set of the nodes of the network into dominating sets with the aim of maximizing the number of dominating sets. In this paper,we consider the k -domatic partition problem. A k -dominating set is a subset D of nodes such that every node in the network is at distance at most k from D. The k-domatic partition problem seeks to partition the network into maximum number of k-dominating sets.We point out that from the point of view of saving energy,it may be better to construct a k-domatic partition for k 1.We present three deterministic, distributed algorithms for finding large k-domatic partitions for k 1. Each of our algorithms constructs a k-domatic partition of size at least a constant fraction of the largest possible (k 1)-domatic partition. Our first algorithm runs in constant time on unit ball graphs (UBGs) in Euclidean space assuming that all nodes know their positions in a global coordinate system. Our second algorithm drops knowledge of global coordinates and instead assumes that pairwise distances between neighboring nodes are known. This algorithm runs in O(log* n ) time on UBGs in a metric space with constant doubling dimension. Our third algorithm drops all reliance on geometric information, using connectivity information only. This algorithm runs in O(log Δ · log *n) time on growth-bounded graphs. Euclidean UBGs, UBGs in metric spaces with constant doubling dimension, and growth-bounded graphs are successively more general models of wireless networks and all three models include the well-known, but somewhat simplistic wireless network models such as unit disk graphs.