Maximal independent sets in multichannel radio networks

Daum, Sebastian; Ghaffari, Mohsen; Gilbert, Seth; Kühn, Fabian; Newport, Calvin

doi:10.1145/2484239.2484257

Cited by 23 publications

(57 citation statements)

References 30 publications

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“…Multiple channels have been found to yield linear speedups in graph-based models, such as for broadcast [9], minimum dominating sets [7], leader election [5] and maximal independent sets [4]. In contrast, essentially the only work on multiple channels in the signal-to-interference-and-noise ratio (SINR) model is [37], which attained a sub-linear speedup for local information exchange, but holds only for a restricted number of channels when each message can carry multiple packets.…”

Section: Can We Speed Distributed Wireless Algorithms Up Linearly Witmentioning

confidence: 99%

“…In particular, aggregation can be achieved in optimal O(D + log n) time [2,14], but this uses O(K log 2 n) time for precomputation and also relies heavily on arbitrary power control. In multi-channel networks, the multiple-message broadcast algorithm given in [4] can be adapted to solve the data aggregation problem in a graph-based interference model in O(D+∆+ log 2 n F +log n log log n) rounds with high probability, but it restricts the number of channels to at most log n. An algorithm for the related broadcast problem was given in [9] for a similar setting but also allowing disruptions on channels. The work closest to ours is a recent treatment of the local information exchange problem in multi-channel SINR networks [37], where Yu et al gave a distributed algorithm attaining a sub-linear speedup.…”

Section: Related Workmentioning

confidence: 99%

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Leveraging multiple channels in ad hoc networks

Halldórsson

Wang

2018

Distrib. Comput.

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We examine the utility of multiple channels of communication in wireless networks under the SINR model of interference. The central question is whether the use of multiple channels can result in linear speedup, up to some fundamental limit. We answer this question affirmatively for the data aggregation problem, perhaps the most fundamental problem in sensor networks. To achieve this, we form a hierarchical structure of independent interest, and illustrate its versatility by obtaining a new algorithm with linear speedup for the node coloring problem.

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Section: Can We Speed Distributed Wireless Algorithms Up Linearly Witmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Leveraging multiple channels in ad hoc networks

Halldórsson

Wang

2018

Distrib. Comput.

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“…With the assumption that nodes can listen to and receive messages from multiple channels concurrently, Shi et al [21] gave an O(log k log log k) time randomized information exchange algorithm using Θ(n) channels. Furthermore, in a very recent paper [8], Daum et al gave a randomized protocol with time complexity O(k log n + log 2 n F + log n log log n) when there are F available channels. In contrast, very few works addressed unrestricted information exchange on multiple channels.…”

Section: Related Workmentioning

confidence: 99%

“…In contrast, very few works addressed unrestricted information exchange on multiple channels. To the best of our knowledge, there is only one result, which is given in [8]. Their proposed randomized algorithm can accomplish information exchange in O(k + log 2 n F + log n log log n) timeslots with high probability.…”

Section: Related Workmentioning

confidence: 99%

Information exchange with collision detection on multiple channels

Wang

et al. 2014

J Comb Optim

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Abstract. Information exchange is a fundamental communication primitive in radio networks. We study this problem in multi-channel singlehop networks. In particular, given k pieces of information, initially stored in k nodes respectively, the task is to broadcast these information pieces to the entire network via a set of F channels. We develop efficient distributed algorithms for this task for the scenario where both the identities and the number k of the initial information holders are unknown to the participating nodes. Assuming nodes with collision detection, we present an efficient randomized algorithm for unrestricted information exchange, where multiple information items can be combined into a single message. The algorithm disseminates all the information items within O( k F + F log 2 n) timeslots with high probability. To the best of our knowledge, this is the first algorithm that breaks the Ω(k) lower bound for unrestricted information exchange if only a single channel is available. This result establishes the superiority of multiple channels for the task of unrestricted information exchange. Moreover, for restricted information exchange, where each message can carry only one information item, we devise a randomized algorithm that completes the task in O(k + log 2 n F + log n) timeslots. When k is large, both algorithms are asymptotically optimal, as they can reach the trivial lower bounds of Ω( k F ) and Ω(k) for unrestricted and restricted information exchange, respectively.

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“…Ad-hoc multi-hop multi-channel networks were studied by Alonso et al [2], Daum et al [20] and [22], Dolev et al [31], and So and Vaidya [47].…”

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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Maximal independent sets in multichannel radio networks

Cited by 23 publications

References 30 publications

Leveraging multiple channels in ad hoc networks

Leveraging multiple channels in ad hoc networks

Information exchange with collision detection on multiple channels

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

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