• Publications
  • Influence
Randomized gossip algorithms
TLDR
We study distributed algorithms, also known as gossip algorithms, for exchanging information and for computing in an arbitrarily connected network of nodes, and find that the averaging time of a gossip algorithm depends on the second largest eigenvalue of a doubly stochastic matrix characterizing the algorithm. Expand
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Rumors in a Network: Who's the Culprit?
  • D. Shah, T. Zaman
  • Computer Science, Mathematics
  • IEEE Transactions on Information Theory
  • 24 September 2009
TLDR
We provide a systematic study of the problem of finding the source of a rumor in a network with the popular susceptible-infected model and then construct an estimator for the rumor source. Expand
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Throughput-delay trade-off in wireless networks
TLDR
This paper provides a definition of delay in ad hoc networks and obtains optimal throughput-delay trade-off in fixed and mobile wireless networks. Expand
  • 640
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Optimal throughput-delay scaling in wireless networks - part I: the fluid model
TLDR
We show that the optimal throughput-delay tradeoff is given by D(n)=Theta(nT(n)), where T(n) and D( n) are the throughput and delay scaling, respectively. Expand
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Gossip algorithms: design, analysis and applications
TLDR
We study distributed asynchronous algorithms, also known as gossip algorithms, for computation and information exchange in an arbitrarily connected network of nodes, and show that the averaging time of a gossip algorithm depends on the second largest eigenvalue of a doubly stochastic matrix characterizing the algorithm. Expand
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Network Coding Meets TCP: Theory and Implementation
TLDR
The theory of network coding promises significant benefits in network performance, especially in lossy networks and in multipath scenarios. Expand
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Network Coding Meets TCP
TLDR
We propose a mechanism that incorporates network coding into TCP with only minor changes to the protocol stack, thereby allowing incremental deployment. Expand
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Iterative Learning for Reliable Crowdsourcing Systems
TLDR
Crowdsourcing systems, in which tasks are electronically distributed to numerous "information piece-workers", have emerged as an effective paradigm for human-powered solving of large scale problems in domains such as image classification, data entry, optical character recognition, and proofreading. Expand
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Iterative ranking from pair-wise comparisons
TLDR
In this paper, we propose a novel iterative rank aggregation algorithm for discovering scores for objects from pairwise comparisons. Expand
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Network adiabatic theorem: an efficient randomized protocol for contention resolution
TLDR
We design an efficient Aloha-like algorithm for a network of queues where contention is modeled through independent-set constraints over the network graph. Expand
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