Sensor Network Gossiping or How to Break the Broadcast Lower Bound

Farach-Colton, Martı́n; Mosteiro, Miguel A.

doi:10.1007/978-3-540-77120-3_22

Cited by 16 publications

(23 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Formally, the payoff functions of the players are defined by . Moreover, the probability that the number of exactly-once-sampled d's will be smaller than m 2e is exponentially small in m (see , e.g., [3], Lemma 4). So, with probability that is exponentially close to 1, in the resulting uniform distribution at least one player may increase it's payoff by at least -correlated equilibrium with exponentially small (in m) probability.…”

Section: < M Actions)mentioning

confidence: 99%

Simple approximate equilibria in large games

Babichenko

Barman

Peretz

2014

Proceedings of the Fifteenth ACM Conference on Economics and Computation

View full text Add to dashboard Cite

We show that in an n-player m-action strategic form game, we can obtain an approximate equilibrium by sampling any mixed-action equilibrium a small number of times. We study three notions of equilibrium: Nash, correlated and coarse correlated. For each one of them we obtain upper and lower bounds on the asymptotic (where max(m, n) → ∞) worst-case number of samples required for the empirical frequency of the sampled action profiles to form an approximate equilibrium with probability close to one.These bounds imply that using a small number of samples we can test whether or not players are playing according to an approximate equilibrium, even in games where n and m are large. In addition, our results include a substantial improvement over the previously known upper bounds on the existence of a small-support approximate equilibrium in games with many players. For all three notions of equilibrium, we show the existence of approximate equilibrium with support size polylogarithmic in n and m, whereas the best previously known results were polynomial in n [8,6,7].

show abstract

Section: < M Actions)mentioning

confidence: 99%

Simple approximate equilibria in large games

Babichenko

Barman

Peretz

2014

Proceedings of the Fifteenth ACM Conference on Economics and Computation

View full text Add to dashboard Cite

show abstract

“…The following lemma establishes formally the efficiency of these phases. Further details can be found in [6]- [8] and the references therein. …”

Section: A Preprocessing and Maintenancementioning

confidence: 99%

“…Additionally, a second phase establishes schedules of transmissions so that each group delegate-slugs can communicate without colliding with neighboring groups. The first and second preprocessing phases can be implemented as in [8]. Further details can be found in the full version of this paper [11].…”

Section: A Preprocessing and Maintenancementioning

confidence: 99%

An Early-Stopping Protocol for Computing Aggregate Functions in Sensor Networks

Anta

Mosteiro

Thraves

2009

2009 15th IEEE Pacific Rim International Symposium on Dependable Computing

Self Cite

View full text Add to dashboard Cite

In this paper, we study algebraic aggregate computations in Sensor Networks. The main contribution is the presentation of an early-stopping protocol that computes the average function under a harsh model of the conditions under which sensor nodes operate. This protocol is shown to be time-optimal in presence of unfrequent failures. The approach followed saves time and energy by relying the computation on a small network of delegate nodes that can be rebuilt fast in case of node failures and communicate using a collisionfree schedule. Delegate nodes run simultaneously two protocols, namely, a collection/dissemination tree-based algorithm, which is shown to be optimal, and a mass-distribution algorithm. Both algorithms are analyzed under a model where the frequency of failures is a parameter. Other aggregate computation algorithms can be easily derived from this protocol. To the best of our knowledge, this is the first optimal early-stopping algorithm for aggregate computations in Sensor Networks.

show abstract

“…When some number 1 ≤ k ≤ n of active nodes hold an information that must be disseminated to all nodes in the network, the problem is called k-Selection [32] or Many-to-all [11]. If k = 1 the problem is called Broadcast [5,36], whereas if k = n the problem is known as Gossiping [9,19]. Upper bounds for these problems in mobile networks may be used for dissemination, and even those for static networks may apply if the movement of nodes does not preclude the algorithm from completing the task (e.g., round-robin).…”

Section: Previous Workmentioning

confidence: 99%

Opportunistic information dissemination in mobile ad-hoc networks: the profit of global synchrony

et al. 2012

Self Cite

View full text Add to dashboard Cite

The topic of this paper is the study of information dissemination in mobile ad-hoc networks by means of deterministic protocols. We assume a weak set of restrictions on the mobility of nodes, parameterized by α, the disconnection time, and β, the link stability time, such that the mobile ad-hoc networks considered are connected enough for dissemination. Such a connectivity model generalizes previous models in that we assume much less connectivity, or make explicit the assumptions in previous papers. The protocols studied are classified into three classes: oblivious (the transmission schedule of a node is only a function of its ID), quasi-oblivious (the transmission schedule may also depend on a global time), and adaptive. The main contribution of this work concerns negative results. Contrasting the lower and upper bounds derived, interesting complexity gaps among protocol-classes are observed. These results show that the gap in time complexity between oblivious and quasi-oblivious A preliminary version of this work is included in [21].

show abstract

Sensor Network Gossiping or How to Break the Broadcast Lower Bound

Cited by 16 publications

References 17 publications

Simple approximate equilibria in large games

Simple approximate equilibria in large games

An Early-Stopping Protocol for Computing Aggregate Functions in Sensor Networks

Opportunistic information dissemination in mobile ad-hoc networks: the profit of global synchrony

Contact Info

Product

Resources

About