Emergent Mind

Abstract

Consider a single-hop, multi-channel, synchronous radio network in which a source node needs to disseminate a message to all other $n-1$ nodes. An adversary called Eve, which captures environmental noise and potentially malicious interference, aims to disrupt this process via jamming. Assume sending, listening, or jamming on one channel for one time slot costs unit energy. The question is, if Eve spends $T$ units of energy on jamming, can we devise broadcast algorithms in which each node's cost is $o(T)$? Previous results show such resource competitive algorithms do exist in the single-channel setting: each node can receive the message within $\tilde{O}(T+n)$ time slots while spending only $\tilde{O}(\sqrt{T/n}+1)$ energy. In this paper, we show that when Eve is oblivious, the existence of multiple channels allows even faster message dissemination, while preserving resource competitiveness. Specifically, we have identified an efficient "epidemic broadcast" scheme in the multi-channel setting that is robust again jamming. Extending this scheme leads to a randomized algorithm called MultiCast which uses $n/2$ channels, and accomplishes broadcast in $\tilde{O}(T/n+1)$ time slots while costing each node only $\tilde{O}(\sqrt{T/n}+1)$ energy. When the value of $n$ is unknown, we further propose MultiCastAdv, in which each node's running time is $\tilde{O}(T/(n{1-2\alpha})+n{2\alpha})$, and each node's cost is $\tilde{O}(\sqrt{T/(n{1-2\alpha})}+n{2\alpha})$. Here, $0<\alpha<1/4$ is a tunable parameter affecting the constant hiding behind the big-$O$ notation. To handle the issue of limited channel availability, we have also devised variants for both MultiCast and MultiCastAdv that can work in networks in which only $C$ channels are available, for any $C\geq 1$. These variants remain to be resource competitive, and have (near) optimal time complexity in many cases.

We're not able to analyze this paper right now due to high demand.

Please check back later (sorry!).

Generate a summary of this paper on our Pro plan:

We ran into a problem analyzing this paper.

Newsletter

Get summaries of trending comp sci papers delivered straight to your inbox:

Unsubscribe anytime.