A Necessary and Sufficient Condition for Consensus Over Random Networks

By Alireza Tahbaz-Salehi, Ali Jadbabaie. 2008

464 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Molecular Biology

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Citations in the corpus

An Overview of Recent Progress in the Study of Distributed Multi-Agent Coordination (2012, background): “Consensus for single-integrator kinematics under stoch astic network topology has been extensively studied, in particular, wher e some general conditions for almost-surely consensus was derived [ 26], [27], [30].”
On the O(1=k) convergence of asynchronous distributed alternating Direction Method of Multipliers (2013, background): “This work is clearly also related to the extensive literature on consensus and cooperative control, where the goal is to design local deterministic or random update rules to achieve global coordination (for deterministic update rules, see [4], [7], [15], [23], [27], [38], [39], [40], [44]; for rando”
Stochastic consensus over noisy networks with Markovian and arbitrary switches (2010, background): “Tahbaz-Salehi and Jadbabaie (2008) considered averaging with a sequence of independent coefficient matrices, which indicates that the overall network topology evolves independently; such modelling was also adopted for linear synchronization (Wu, 2006).”
Convergence speed in distributed consensus over dynamically switching random networks (2009, background): “In addition, the weight matrix of a networkmay have negative elements, and thus classical results on stochasticmatrices (Blondel, Hendrickx, Olshevsky, & Tsitsiklis, 2005; Cao, Morse, & Anderson, 2008; Tahbaz-Salehi & Jadbabaie, 2008) are no longer applicable.”
Consensus in multi-agent systems: a review (2021, background): “In (Tahbaz-Salehi and Jadbabaie 2008), it was shown how a problem of consensus seeking over a network can be reduced to a problem of the ergodicity of a sequence of matrixes.”
Consensus Conditions of Multi-Agent Systems With Time-Varying Topologies and Stochastic Communication Noises (2010, background): “In addition to the above works, some researchers also considered the high-order dynamics [8], [9], the topologies of random graphs [10]–[13] or control design based on individual performance optimization [14]–[17].”
Stochastic Consensus Seeking With Noisy and Directed Inter-Agent Communication: Fixed and Randomly Varying Topologies (2010, background): “Third, convergence results are proved with both measurement noise and random independent link failures; for related random graph based modeling, see [14], [20], [24], [25], [31], [34].”
Consensus of Data-Sampled Multi-Agent Systems With Random Communication Delay and Packet Loss (2010, background): “In [9]–[11], the first-order consensus problem is formulated over networks with random packet losses.”
Opinion Dynamics and Learning in Social Networks (2011, background): “12 10 The DeGroot model and variations have also been studied extensively in the cooperative control literature as natural algorithms for achieving cooperative behavior with local information in networked-systems (see [18, 33, 62, 67, 71, 72, 87–89]).”
Consensus Over Ergodic Stationary Graph Processes (2010, methodology): “In [12], Tahbaz-Salehi and Jadbabaie study the asymptotic properties of random consensus algorithms over the general class of i.i.d. weighted and directed random graph sequences , where different communication links at a given time are correlated , even though realizations of the network at two…”
Distributed Subgradient Methods for Convex Optimization Over Random Networks (2011, methodology): “Our paper uses a random graph model which is similar to [21], and presents distributed subgradient methods that can optimize general convex (not necessarily smooth) local objective functions.”