Optimal gossip with direct addressing

Haeupler, Bernhard; Malkhi, Dahlia

doi:10.1145/2611462.2611489

Cited by 11 publications

(10 citation statements)

References 19 publications

(26 reference statements)

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“…Consider the problem of disseminating information in a large-scale distributed system: a source node in the network has some information that it wants to share/aggregate/reconcile with others. This fundamental problem has been widely studied under various names, e.g., information dissemination (e.g., [5]), rumor spreading (e.g., [8]), global broadcast (e.g., [20]), one-to-all multicast, information spreading (e.g., [6]), and gossip (e.g., [21]).…”

Section: Arxiv:161106343v3 [Csdc] 17 Dec 2018mentioning

confidence: 99%

“…For graphs modeling social networks Doerr et al [11,12] show a Θ(log n) time bound for solving broadcast. For the case of direct addressing, Haeupler and Malkhi [21] show that broadcast can be performed optimally in O(log log n) rounds. Information dissemination has been studied in random geometric graphs by Bradonjić et al [4], in wireless sensor networks networks by Boyd et al [3] and Farach-Colton et al [14], in mobile adhoc networks by Fernandez-Anta et al [13] and in dynamic graphs by Sarwate and Dimakis [28], Gandhi et al [17], and Giakkoupis et al [19].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Slow Links, Fast Links, and the Cost of Gossip

Sourav

Robinson

Gilbert

2018

2018 IEEE 38th International Conference on Distributed Computing Systems (ICDCS)

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Consider the classical problem of information dissemination: one (or more) nodes in a network have some information that they want to distribute to the remainder of the network. In this paper, we study the cost of information dissemination in networks where edges have latencies, i.e., sending a message from one node to another takes some amount of time. We first generalize the idea of conductance to weighted graphs by defining φ * to be the "critical conductance" and * to be the "critical latency". One goal of this paper is to argue that φ * characterizes the connectivity of a weighted graph with latencies in much the same way that conductance characterizes the connectivity of unweighted graphs.We give near tight lower and upper bounds on the problem of information dissemination, up to polylogarithmic factors. Specifically, we show that in a graph with (weighted) diameter D (with latencies as weights) and maximum degree ∆, any information dissemination algorithm requires at least Ω(min(D+ ∆, * /φ * )) time in the worst case. We show several variants of the lower bound (e.g., for graphs with small diameter, graphs with small max-degree, etc.) by reduction to a simple combinatorial game.We then give nearly matching algorithms, showing that information dissemination can be solved in O(min((D + ∆) log 3 n, ( * /φ * ) log n) time. This is achieved by combining two cases. We show that the classical push-pull algorithm is (near) optimal when the diameter or the maximum degree is large. For the case where the diameter and the maximum degree are small, we give an alternative strategy in which we first discover the latencies and then use an algorithm for known latencies based on a weighted spanner construction. (Our algorithms are within polylogarithmic factors of being tight both for known and unknown latencies.)While it is easiest to express our bounds in terms of φ * and * , in some cases they do not provide the most convenient definition of conductance in weighted graphs. Therefore we give a second (nearly) equivalent characterization, namely the average conductance φ avg . arXiv:1611.06343v3 [cs.DC] 17 Dec 2018Consider the problem of disseminating information in a large-scale distributed system: a source node in the network has some information that it wants to share/aggregate/reconcile with others. This fundamental problem has been widely studied under various names, e.g., information dissemination (e.g., [5]), rumor spreading (e.g., [8]), global broadcast (e.g., [20]), one-to-all multicast, information spreading (e.g., [6]), and gossip (e.g., [21]).Real world network communication often has a time delay, which we model here as edges with latencies. The latency of an edge captures how long communication takes, i.e., how many rounds it takes for two neighbors to exchange information. Low latency on links imply faster message transmission whereas higher latency implies longer delays.In the case of unweighted graphs, all edges are considered the same and are said to have unit latencies. However, this is not true in real...

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Section: Arxiv:161106343v3 [Csdc] 17 Dec 2018mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Slow Links, Fast Links, and the Cost of Gossip

Sourav

Robinson

Gilbert

2018

2018 IEEE 38th International Conference on Distributed Computing Systems (ICDCS)

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“…Fault tolerant broadcast algorithms have also been studied extensively, especially in complete networks and in synchronous environments, where the focus has been on weak types of failures such as (probabilistic) message failures and initial node crashes. Essentially, it has been shown that there exist broadcast protocols that can overcome such faults with a relatively little penalty [21,23,24,35,38,39,43,60].…”

Section: Context and Related Workmentioning

confidence: 99%

Breathe before speaking: efficient information dissemination despite noisy, limited and anonymous communication

2015

Self Cite

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Distributed computing models typically assume reliable communication between processors. While such assumptions often hold for engineered networks, e.g., due to underlying error correction protocols, their relevance to biological systems, wherein messages are often distorted before reaching their destination, is quite limited. In this study we take a first step towards reducing this gap by rigorously analyzing a model of communication in large anonymous populations composed of simple agents which interact through short and highly unreliable messages.We focus on the broadcast problem and the majority-consensus problem. Both are fundamental information dissemination problems in distributed computing, in which the goal of agents is to converge to some prescribed desired opinion. We initiate the study of these problems in the presence of communication noise. Our model for communication is extremely weak and follows the push gossip communication paradigm: In each round each agent that wishes to send information delivers a message to a random anonymous agent. This communication is further restricted to contain only one bit (essentially representing an opinion). Lastly, the system is assumed to be so noisy that the bit in each message sent is flipped independently with probability 1/2 − ǫ, for some small ǫ > 0.Even in this severely restricted, stochastic and noisy setting we give natural protocols that solve the noisy broadcast and the noisy majority-consensus problems efficiently. Our protocols run in O(log n/ǫ 2 ) rounds and use O(n log n/ǫ 2 ) messages/bits in total, where n is the number of agents. These bounds are asymptotically optimal and, in fact, are as fast and message efficient as if each agent would have been simultaneously informed directly by an agent that knows the prescribed desired opinion. Our efficient, robust, and simple algorithms suggest balancing between silence and transmission, synchronization, and majority-based decisions as important ingredients towards understanding collective communication schemes in anonymous and noisy populations.

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“…Journal version update: Motivated by the conference version of this paper [1], Haeupler and Malkhi [21] improved our bound and presented an elegant algorithm that solves the problem we study here in O(log log n) rounds together with a macthing lower bound. Nevertheless we think our work contributes to the understanding of the gossiping process and may be useful in extension of the model to general graphs.…”

Section: Our Contributionmentioning

confidence: 99%