Epidemic algorithms for replicated database maintenance
PODC '87 Proceedings of the sixth annual ACM Symposium on Principles of distributed computing
An optimal synchronizer for the hypercube
SIAM Journal on Computing
Time-optimal leader election in general networks
Journal of Parallel and Distributed Computing
Algorithms for random generation and counting: a Markov chain approach
Algorithms for random generation and counting: a Markov chain approach
Randomized Broadcast in Networks
SIGAL '90 Proceedings of the International Symposium on Algorithms
FOCS '00 Proceedings of the 41st Annual Symposium on Foundations of Computer Science
Gossip-Based Computation of Aggregate Information
FOCS '03 Proceedings of the 44th Annual IEEE Symposium on Foundations of Computer Science
Distributed Computing: Fundamentals, Simulations and Advanced Topics
Distributed Computing: Fundamentals, Simulations and Advanced Topics
Computing separable functions via gossip
Proceedings of the twenty-fifth annual ACM symposium on Principles of distributed computing
IEEE/ACM Transactions on Networking (TON) - Special issue on networking and information theory
Proceedings of the nineteenth annual ACM-SIAM symposium on Discrete algorithms
Many random walks are faster than one
Proceedings of the twentieth annual symposium on Parallelism in algorithms and architectures
On the complexity of asynchronous gossip
Proceedings of the twenty-seventh ACM symposium on Principles of distributed computing
Quasirandom Rumor Spreading: Expanders, Push vs. Pull, and Robustness
ICALP '09 Proceedings of the 36th International Colloquium on Automata, Languages and Programming: Part I
Almost tight bounds for rumour spreading with conductance
Proceedings of the forty-second ACM symposium on Theory of computing
Partial information spreading with application to distributed maximum coverage
Proceedings of the 29th ACM SIGACT-SIGOPS symposium on Principles of distributed computing
Efficient broadcast on random geometric graphs
SODA '10 Proceedings of the twenty-first annual ACM-SIAM symposium on Discrete Algorithms
Rumour spreading and graph conductance
SODA '10 Proceedings of the twenty-first annual ACM-SIAM symposium on Discrete Algorithms
Quasirandom Rumor Spreading on the Complete Graph Is as Fast as Randomized Rumor Spreading
SIAM Journal on Discrete Mathematics
Order optimal information spreading using algebraic gossip
Proceedings of the 30th annual ACM SIGACT-SIGOPS symposium on Principles of distributed computing
Rumor spreading and vertex expansion
Proceedings of the twenty-third annual ACM-SIAM symposium on Discrete Algorithms
On the impact of users availability in OSNs
Proceedings of the Fifth Workshop on Social Network Systems
STOC '12 Proceedings of the forty-fourth annual ACM symposium on Theory of computing
Experimental analysis of rumor spreading in social networks
MedAlg'12 Proceedings of the First Mediterranean conference on Design and Analysis of Algorithms
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Gathering data from nodes in a network is at the heart of many distributed applications, most notably, while performing a global task. We consider information spreading among n nodes of a network, where each node v has a message m(v) which must be received by all other nodes. The time required for information spreading has been previously upper-bounded with an inverse relationship to the conductance of the underlying communication graph. This implies high running times for graphs with small conductance. The main contribution of this paper is an information spreading algorithm which overcomes communication bottlenecks and thus achieves fast information spreading for a wide class of graphs, despite their small conductance. As a key tool in our study we use the recently defined concept of weak conductance, a generalization of classic graph conductance which measures how well-connected the components of a graph are. Our hybrid algorithm, which alternates between random and deterministic communication phases, exploits the connectivity within components by first applying partial information spreading, after which messages are sent across bottlenecks, thus spreading further throughout the network. This yields substantial improvements over the best known running times of algorithms for information spreading on any graph that has a large weak conductance, from polynomial to polylogarithmic number of rounds. We demonstrate the power of fast information spreading in accomplishing global tasks on the leader election problem, which lies at the core of distributed computing. Our results yield an algorithm for leader election that has a scalable running time on graphs with large weak conductance, improving significantly upon previous results.