PODC '87 Proceedings of the sixth annual ACM Symposium on Principles of distributed computing
A lower bound for radio broadcast
Journal of Computer and System Sciences
An Ω(D log(N/D)) lower bound for broadcast in radio networks
PODC '93 Proceedings of the twelfth annual ACM symposium on Principles of distributed computing
Deterministic broadcasting in unknown radio networks
SODA '00 Proceedings of the eleventh annual ACM-SIAM symposium on Discrete algorithms
Faster broadcasting in unknown radio networks
Information Processing Letters
Broadcasting in radio networks
Handbook of wireless networks and mobile computing
Explicit constructions of selectors and related combinatorial structures, with applications
SODA '02 Proceedings of the thirteenth annual ACM-SIAM symposium on Discrete algorithms
Deterministic Broadcasting Time in Radio Networks of Unknown Topology
FOCS '02 Proceedings of the 43rd Symposium on Foundations of Computer Science
Deterministic Radio Broadcasting
ICALP '00 Proceedings of the 27th International Colloquium on Automata, Languages and Programming
Fast broadcasting and gossiping in radio networks
FOCS '00 Proceedings of the 41st Annual Symposium on Foundations of Computer Science
Distributed broadcast in radio networks of unknown topology
Theoretical Computer Science
Broadcasting Algorithms in Radio Networks with Unknown Topology
FOCS '03 Proceedings of the 44th Annual IEEE Symposium on Foundations of Computer Science
Faster Deterministic Broadcasting in Ad Hoc Radio Networks
SIAM Journal on Discrete Mathematics
Theoretical Computer Science - Foundations of software science and computation structures
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We consider the problem of broadcasting in an unknown radio network modeled as a directed graph $G=(V,E)$, where $|V|=n$. In unknown networks, every node knows only its own label, while it is unaware of any other parameter of the network, including its neighborhood and even any upper bound on the number of nodes. We show an $\mathcal{O}(n\log n\log\log n)$ upper bound on the time complexity of deterministic broadcasting. This is an improvement over the currently best upper bound $\mathcal{O}(n\log^2n)$ for arbitrary networks, thus shrinking exponentially the existing gap between the lower bound $\Omega(n\log n)$ and the upper bound from $\mathcal{O}(\log n)$ to $\mathcal{O}(\log\log n)$.