English

Minimum-energy broadcast in random-grid ad-hoc networks: approximation and distributed algorithms

Data Structures and Algorithms 2008-04-25 v1

Abstract

The Min Energy broadcast problem consists in assigning transmission ranges to the nodes of an ad-hoc network in order to guarantee a directed spanning tree from a given source node and, at the same time, to minimize the energy consumption (i.e. the energy cost) yielded by the range assignment. Min energy broadcast is known to be NP-hard. We consider random-grid networks where nodes are chosen independently at random from the nn points of a n×n\sqrt n \times \sqrt n square grid in the plane. The probability of the existence of a node at a given point of the grid does depend on that point, that is, the probability distribution can be non-uniform. By using information-theoretic arguments, we prove a lower bound (1ϵ)nπ(1-\epsilon) \frac n{\pi} on the energy cost of any feasible solution for this problem. Then, we provide an efficient solution of energy cost not larger than 1.1204nπ1.1204 \frac n{\pi}. Finally, we present a fully-distributed protocol that constructs a broadcast range assignment of energy cost not larger than 8n8n,thus still yielding constant approximation. The energy load is well balanced and, at the same time, the work complexity (i.e. the energy due to all message transmissions of the protocol) is asymptotically optimal. The completion time of the protocol is only an O(logn)O(\log n) factor slower than the optimum. The approximation quality of our distributed solution is also experimentally evaluated. All bounds hold with probability at least 11/nΘ(1)1-1/n^{\Theta(1)}.

Keywords

Cite

@article{arxiv.0804.3902,
  title  = {Minimum-energy broadcast in random-grid ad-hoc networks: approximation and distributed algorithms},
  author = {Tiziana Calamoneri and Andrea E. F. Clementi and Angelo Monti and Gianluca Rossi and Riccardo Silvestri},
  journal= {arXiv preprint arXiv:0804.3902},
  year   = {2008}
}

Comments

13 pages, 3 figures, 1 table

R2 v1 2026-06-21T10:34:14.848Z