Impact of heterogeneous link qualities and network connectivity on binary consensus

In this paper we consider a network that is trying to reach consensus over the occurrence of an event while communicating over Additive White Gaussian Noise (AWGN) channels. We characterize the impact of different link qualities and network connectivity on consensus performance by analyzing both the asymptotic and transient behaviors. More specifically, we derive a tight approximation for the second largest eigenvalue of the probability transition matrix. We furthermore characterize the dynamics of each individual node. © 2009 AACC.

Oscillations in a decentralized economic network

The study of exchange markets dates back to LeonWalras's general equilibrium theory. Since then the economic market has been studied for its' equilibrium properties, fairness of allocations of private and public goods, and even the psychological incentives of participants. This paper studies the dynamics of an exchange economy built on a network of markets where consumers trade with suppliers to optimize utility. Viewing the market in as a decentralized network we study the system from the usual control theory point of view, evaluating the system's dynamic performance, stability and robustness. It is shown that certain consumer demand dynamics can lead to oscillations while others can converge to optimal allocations. © 2011 IFAC.

Network reconstruction using knock-out and over-expression data

This paper outlines necessary and sufficient conditions for network reconstruction of linear, time-invariant systems using data from either knock-out or over-expression experiments. These structural system perturbations, which are common in biological experiments, can be formulated as unknown system inputs, allowing the network topology and dynamics to be found. We assume that only partial state measurements are available and propose an algorithm that can reconstruct the network at the level of the measured states using either time-series or steady-state data. A simulated example illustrates how the algorithm successfully reconstructs a network from data. © 2013 EUCA.