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- Bassam Bamieh, Mihailo R. Jovanovic, Partha P. Mitra, Stacy Patterson
- IEEE Trans. Automat. Contr.
- 2012

We consider distributed consensus and vehicular formation control problems. Specifically we address the question of whether local feedback is sufficient to maintain coherence in large-scale networks subject to stochastic disturbances. We define macroscopic performance measures which are global quantities that capture the notion of coherence; a notion of… (More)

- Stacy Patterson, Bassam Bamieh
- CDC
- 2010

We consider the problem of leader-based distributed coordination in networks where agents are subject to stochastic disturbances, but where certain designated leaders are immune to those disturbances. Specifically, we address the effect of leader selection on the coherence of the network, defined in terms of an H2 norm of the system. This quantity captures… (More)

- Achour Mostéfaoui, Michel Raynal, Corentin Travers, Stacy Patterson, Divyakant Agrawal, Amr El Abbadi
- 24th IEEE Symposium on Reliable Distributed…
- 2005

A noteworthy advance in distributed computing is due to the recent development of peer-to-peer systems. These systems are essentially dynamic in the sense that no process can get a global knowledge on the system structure. They mainly allow processes to look up for data that can be dynamically added/suppressed in a permanently evolving set of nodes.… (More)

- Stacy Patterson, Bassam Bamieh, Amr El Abbadi
- IEEE Trans. Automat. Contr.
- 2010

We consider a distributed average consensus algorithm over a network in which communication links fail with independent probability. In such stochastic networks, convergence is defined in terms of the variance of deviation from average. We first show how the problem can be recast as a linear system with multiplicative random inputs which model link… (More)

- Stacy Patterson, Yonina C. Eldar, Idit Keidar
- IEEE Transactions on Signal Processing
- 2014

We consider the problem of in-network compressed sensing from distributed measurements. Every agent has a set of measurements of a signal x, and the objective is for the agents to recover x from their collective measurements using only communication with neighbors in the network. Our distributed approach to this problem is based on the centralized Iterative… (More)

- Stacy Patterson, Yonina C. Eldar, Idit Keidar
- 2013 IEEE International Conference on Acoustics…
- 2013

We propose a distributed algorithm for sparse signal recovery in sensor networks based on Iterative Hard Thresholding (IHT). Every agent has a set of measurements of a signal x, and the objective is for the agents to recover x from their collective measurements at a minimal communication cost and with low computational complexity. A naïve… (More)

- Stacy Patterson, Bassam Bamieh, Amr El Abbadi
- CDC
- 2007

We consider a distributed average consensus algorithm over a network in which communication links fail with independent probability. Convergence in such stochastic networks is defined in terms of the variance of deviation from average. We characterize the decay factor of the variance in terms of the eigenvalues of a Lyapunov-like matrix recursion. We give… (More)

We present a framework for concurrency control and availability in multi-datacenter datastores. While we consider Google’s Megastore as our motivating example, we define general abstractions for key components, making our solution extensible to any system that satisfies the abstraction properties. We first develop and analyze a transaction management and… (More)

- Stacy Patterson, Bassam Bamieh
- CDC-ECE
- 2011

We study distributed consensus algorithms in fractal networks where agents are subject to external disturbances. We characterize the coherence of these networks in terms of an H2 norm of the system that captures how closely agents track the consensus value. We show that, in first-order systems, the coherence measure is closely related to the global mean… (More)

- Stacy Patterson, Bassam Bamieh
- SOMA@KDD
- 2010

Online social networks provide a globally available, massive-scale infrastructure for people to exchange information and ideas. A topic of great interest in social networks research is how to model this information exchange and, in particular, how to model and analyze the effects of interpersonal influence on processes such as information diffusion,… (More)