Efficient Distributed Communication in Ad-Hoc Radio Networks

Abstract

We present new distributed deterministic solutions to two communication problems in n-node ad-hoc radio networks: rumor gathering and multi-broadcast. In these problems, some or all nodes of the network initially contain input data called rumors, which have to be learned by other nodes. In rumor gathering, there are k rumors initially distributed arbitrarily among the nodes, and the goal is to collect all the rumors at one node. Our rumor gathering algorithm works in ${\mathcal O}((k+n)\log n)$ time and our multi-broadcast algorithm works in ${\mathcal O}(k\log^3 n+n\log^4 n)$ time, for any n-node networks and k rumors (with arbitrary k), which is a substantial improvement over the best previously known deterministic solutions to these problems.

As a consequence, we exponentially decrease the gap between upper and lower bounds on the deterministic time complexity of four communication problems: rumor gathering, multi-broadcast, gossiping and routing, in the important case when every node has initially at most one rumor (this is the scenario for gossiping and for the usual formulation of routing). Indeed, for $k={\mathcal O}(n)$, our results simultaneously decrease the complexity gaps for these four problems from polynomial to polylogarithmic in the size of the graph. Moreover, our deterministic gathering algorithm applied for $k={\mathcal O}(n)$ rumors, improves over the best previously known randomized algorithm of time ${\mathcal O}(k\log n+ n\log^2 n)$.

The first author is supported by the NSF Grant 1016847. The second author is supported by the Engineering and Physical Sciences Research Council [grant numbers EP/G023018/1, EP/H018816/1]. The third author is partially supported by a NSERC discovery grant and by the Research Chair in Distributed Computing at the Université du Québec en Outaouais.