Distributed Broadcast in Unknown Radio Networks

Marco, Gianluca De

doi:10.1137/080733826

Cited by 39 publications

(29 citation statements)

References 6 publications

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“…The first two of them are the same as in Algorithm Bound-Broadcast-Check from [6]: in the first stage all nodes learn an upper bound on n within a factor of 2, and in the second stage each node learns its distance from the source. The rest of the algorithm contains a crucial difference which permits us to improve the time O (nD) of Algorithm Bound-BroadcastCheck to the currently best known time of broadcasting without acknowledgement, which is the minimum of O (n log 2 D) [12] and O (n log n log log n) [13]. Instead of interleaving phases of broadcasting and phases of acknowledgement, as it was done in Algorithm Bound-BroadcastCheck and which was a time-consuming procedure, we first try to learn an approximate value of D and only then broadcast.…”

Section: Availability Of Collision Detectionmentioning

confidence: 99%

“…The aim of these papers was to construct broadcasting algorithms working as fast as possible in arbitrary (directed) radio networks without knowing their topology. The currently fastest deterministic broadcasting algorithms for such networks have running times O (n log 2 D) [12] and O (n log n log log n) [13]. On the other hand, in [11] an (n log D) lower bound on broadcasting time was proved for directed n-node networks with source eccentricity D. Randomized broadcasting algorithms in radio networks were studied in [2,12,26,24].…”

Section: Related Workmentioning

confidence: 99%

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Acknowledged broadcasting in ad hoc radio networks

Fusco

Pełc

2008

Information Processing Letters

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Section: Availability Of Collision Detectionmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Acknowledged broadcasting in ad hoc radio networks

Fusco

Pełc

2008

Information Processing Letters

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“…The aim of these papers was to construct broadcasting algorithms working as fast as possible in arbitrary (directed) radio networks without knowing their topology. The currently fastest deterministic broadcasting algorithms for such networks have running times O(n log 2 D) [10] and O(n log n log log n) [11]. On the other hand, in [9] an Ω(n log D) lower bound on broadcasting time was proved for directed n-node networks of diameter D.…”

Section: Related Workmentioning

confidence: 99%

Broadcasting in UDG radio networks with missing and inaccurate information

Fusco

Pełc

2010

Distrib. Comput.

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We study broadcasting time in radio networks, modeled as unit disk graphs (UDG). Network stations are represented by points in the plane and a station is connected to all stations at distance at most 1 from it. Stations are unaware of the network topology. Each station can send messages from the beginning of the broadcasting process, even before getting the source message. Emek et al. showed that broadcasting time depends on two parameters of the UDG network, namely, its diameter D (in hops) and its granularity g. The latter is the inverse of the density d of the network which is the minimum Euclidean distance between any two stations. They proved that the minimum broadcasting time is Θ(min {D + g 2, D log g}), assuming that each node knows the density of the network and knows exactly its own position in the plane. In many situations these assumptions are unrealistic. Does removing them influence broadcasting time? The aim of this paper is to answer this question, hence we assume that density is unknown and nodes perceive their position with some unknown error margin e. It turns out that this combination of missing and inaccurate information substantially changes the problem: the main new challenge becomes fast broadcasting in sparse networks (with constant density), when optimal time is O(D). Nevertheless, under our very weak scenario, we construct a broadcasting algorithm that maintains optimal time O (min {D + g 2, D log g}) for all networks with at least 2 nodes, of diameter D and granularity g (previously obtained with exact positions and known density), if each node perceives its position with error margin e=α, for any (unknown) constant α < 1/2. Rather surprisingly, the minimum time of an algorithm working correctly for all networks, and hence stopping if the source is alone, turns out to be Θ(D + g 2). Thus, the mere stopping requirement for the special case of the lonely source causes an exponential increase in broadcasting time, for networks of any density and any small diameter. Finally, if e ≥ d/2}, then broadcasting is impossible. © 2010 Springer-Verlag

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“…A broadcast from a synchronized start in a radio network was considered in [10,16,17,18,23,24,43]. The general problem of waking up a multi-hop radio network was studied in [11,12,15].…”

Section: Introductionmentioning

confidence: 99%

Scalable wake-up of multi-channel single-hop radio networks

Chlebus

Marco

Kowalski

2016

Theoretical Computer Science

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We consider single-hop radio networks with multiple channels as a model of wireless networks. There are n stations connected to b radio channels that do not provide collision detection. A station uses all the channels concurrently and independently. Some k stations may become active spontaneously at arbitrary times. The goal is to wake up the network, which occurs when all the stations hear a successful transmission on some channel. Duration of a waking-up execution is measured starting from the first spontaneous activation. We present a deterministic algorithm for the general problem that wakes up the network in O(k log 1/b k log n) time, where k is unknown. We give a deterministic scalable algorithm for the special case when b > d log log n, for some constant d > 1, which wakes up the network in O( k b log n log(b log n)) time, with k unknown. This algorithm misses time optimality by at most a factor of O(log n(log b+log log n)), because any deterministic algorithm requires Ω( k b log n k ) time. We give a randomized algorithm that wakes up the network within O(k 1/b ln 1 ǫ ) rounds with a probability that is at least 1 − ǫ, for any 0 < ǫ < 1, where k is known. We also consider a model of jamming, in which each channel in any round may be jammed to prevent a successful transmission, which happens with some known parameter probability p, independently across all channels and rounds. For this model, we give two deterministic algorithms for unknown k: one wakes up the network in time O(log −1 ( 1 p ) k log n log 1/b k), and the other in time O(log −1 ( 1 p ) k b log n log(b log n)) but assuming the inequality b > log(128b log n), both with a probability that is at least 1 − 1/poly(n).

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Distributed Broadcast in Unknown Radio Networks

Cited by 39 publications

References 6 publications

Acknowledged broadcasting in ad hoc radio networks

Acknowledged broadcasting in ad hoc radio networks

Broadcasting in UDG radio networks with missing and inaccurate information

Scalable wake-up of multi-channel single-hop radio networks

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