Broadcasting in dynamic radio networks

Clementi, Andrea E. F.; Monti, Angelo; Pasquale, Francesco; Silvestri, Riccardo

doi:10.1016/j.jcss.2008.10.004

Cited by 38 publications

(53 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The time required for global broadcast has been studied in a probabilistic version of the edge-dynamic graph model, where edges are independently formed and removed according to simple Markov processes [10,11,12]. Similar edge-dynamic graphs have also been considered in control theory literature, e.g.…”

Section: Related Workmentioning

confidence: 99%

“…In [12] the authors also consider a worst-case dynamic graph model which is similar to ours, except that the graph is not always connected and collisions are modelled explicitly. This lower-level model does not admit a deterministic algorithm for global broadcast; however, [12] gives a randomized algorithm that succeeds with high probability.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Distributed computation in dynamic networks

Kühn

Lynch

Oshman

2010

Proceedings of the Forty-Second ACM Symposium on Theory of Computing

317

569

View full text Add to dashboard Cite

In this paper we investigate distributed computation in dynamic networks in which the network topology changes from round to round. We consider a worst-case model in which the communication links for each round are chosen by an adversary, and nodes do not know who their neighbors for the current round are before they broadcast their messages. The model captures mobile networks and wireless networks, in which mobility and interference render communication unpredictable. In contrast to much of the existing work on dynamic networks, we do not assume that the network eventually stops changing; we require correctness and termination even in networks that change continually. We introduce a stability property called T -interval connectivity (for T ≥ 1), which stipulates that for every T consecutive rounds there exists a stable connected spanning subgraph. For T = 1 this means that the graph is connected in every round, but changes arbitrarily between rounds.We show that in 1-interval connected graphs it is possible for nodes to determine the size of the network and compute any computable function of their initial inputs in O(n 2 ) rounds using messages of size O(log n + d), where d is the size of the input to a single node. Further, if the graph is T -interval connected for T > 1, the computation can be sped up by a factor of T , and any function can be computed in O(n + n 2 /T ) rounds using messages of size O(log n + d). We also give two lower bounds on the token dissemination problem, which requires the nodes to disseminate k pieces of information to all the nodes in the network.The T-interval connected dynamic graph model is a novel model, which we believe opens new avenues for research in the theory of distributed computing in wireless, mobile and dynamic networks.

show abstract

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Distributed computation in dynamic networks

Kühn

Lynch

Oshman

2010

Proceedings of the Forty-Second ACM Symposium on Theory of Computing

317

569

View full text Add to dashboard Cite

show abstract

“…For global broadcast, some papers assume restrictions on the changes made in each round. For example, [8] consider graph changes that are random. They also consider the worst-case adversary, as do the studies in [29,35].…”

Section: Related Workmentioning

confidence: 99%

Bounded-Contention Coding for the additive network model

Censor-Hillel

Haeupler²,

Lynch³

et al. 2015

Distrib. Comput.

View full text Add to dashboard Cite

Efficient communication in wireless networks is typically challenged by the possibility of interference among several transmitting nodes. Much important research has been invested in decreasing the number of collisions in order to obtain faster algorithms for communication in such networks.This paper proposes a novel approach for wireless communication, which embraces collisions rather than avoiding them, over an additive channel. It introduces a coding technique called Bounded-Contention Coding (BCC) that allows collisions to be successfully decoded by the receiving nodes into the original transmissions and whose complexity depends on a bound on the contention among the transmitters.BCC enables deterministic local broadcast in a network with n nodes and at most a transmitters with information of bits each within O(a log n + a ) bits of communication with full-duplex radios, and O((a log n + a )(log n)) bits, with high probability, with half-duplex radios. When combined with random linear network coding, BCC gives global broadcast within O((D + a + log n)(a log n + )) bits, with high probability. This also holds in dynamic networks that can change arbitrarily over time by a worst-case adversary. When no bound on the contention is given, it is shown how to probabilistically estimate it and obtain global broadcast that is adaptive to the true contention in the network.

show abstract

“…The dynamic model studied in this paper, by contrast, assumes concurrent communication yields collisions-making it wellsuited for describing radio networks. The exception is the work of Clementi et al [6], which studies a dynamic network model that preserves the standard radio network collision rules. In this model, they show a tight bound of Θ(n 2 / log n) rounds for solving broadcast with a strong adversary constrained only to keep the graph connected in a useful manner in each round.…”

Section: Related Workmentioning

confidence: 99%

The cost of radio network broadcast for different models of unreliable links

Ghaffari

Lynch

Newport

2013

Proceedings of the 2013 ACM Symposium on Principles of Distributed Computing

View full text Add to dashboard Cite

We study upper and lower bounds for the global and local broadcast problems in the dual graph model combined with different strength adversaries. The dual graph model is a generalization of the standard graph-based radio network model that includes unreliable links controlled by an adversary. It is motivated by the ubiquity of unreliable links in real wireless networks. Existing results in this model [11,12,3,8] assume an offline adaptive adversary-the strongest type of adversary considered in standard randomized analysis. In this paper, we study the two other standard types of adversaries: online adaptive and oblivious. Our goal is to find a model that captures the unpredictable behavior of real networks while still allowing for efficient broadcast solutions.For the online adaptive dual graph model, we prove a lower bound that shows the existence of constant-diameter graphs in which both types of broadcast require Ω(n/ log n) rounds, for network size n. This result is within log-factors of the (near) tight upper bound for the offline adaptive setting. For the oblivious dual graph model, we describe a global broadcast algorithm that solves the problem in O(D log n + log 2 n) rounds for network diameter D, but prove a lower bound of Ω( √ n/ log n) rounds for local broadcast in this same setting. Finally, under the assumption of geographic constraints on the network graph, we describe a local broadcast algorithm that requires only O(log 2 n log ∆) rounds in the oblivious model, for maximum degree ∆. In addition to the theoretical interest of these results, we argue that the oblivious model (with geographic constraints) captures enough behavior of real networks to render our efficient algorithms useful for real deployments.

show abstract

Broadcasting in dynamic radio networks

Cited by 38 publications

References 22 publications

Distributed computation in dynamic networks

Distributed computation in dynamic networks

Bounded-Contention Coding for the additive network model

The cost of radio network broadcast for different models of unreliable links

Contact Info

Product

Resources

About