Iterative distributed algorithms are studied for computing arithmetic averages over networks of agents connected through memoryless broadcast erasure channels. These algorithms do not require the agents to have any kn...
详细信息
Iterative distributed algorithms are studied for computing arithmetic averages over networks of agents connected through memoryless broadcast erasure channels. These algorithms do not require the agents to have any knowledge about the global network structure or size. Almost sure convergence to state agreement is proved, and the communication and computational complexities of the algorithms are analyzed. Both the number of transmissions and the number of computations performed by each agent of the network are shown to grow not faster than poly-logarithmically in the desired precision. The impact of the graph topology on the algorithms performance is analyzed as well. Moreover, it is shown how, in the presence of noiseless communication feedback, one can modify the algorithms, significantly improving their performance versus complexity trade-off. (C) 2010 Elsevier Ltd. All rights reserved.
Motivated by control with communication constraints, in this work we develop a time-invariant data compression architecture for linear-quadratic-Gaussian (LQG) control with minimum bitrate prefix-free feedback. For an...
详细信息
Motivated by control with communication constraints, in this work we develop a time-invariant data compression architecture for linear-quadratic-Gaussian (LQG) control with minimum bitrate prefix-free feedback. For any fixed control performance, the approach we propose nearly achieves known directed information (DI) lower bounds on the time-average expected codeword length. We refine the analysis of a classical achievability approach, which required quantized plant measurements to be encoded via a time-varying lossless source code. We prove that the sequence of random variables describing the quantizations has a limiting distribution and that the quantizations may be encoded with a fixed source code optimized for this distribution without added time-asymptotic redundancy. Our result follows from analyzing the long-term stochastic behavior of the system, and permits us to additionally guarantee that the time-average codeword length (as opposed to expected length) is almost surely within a few bits of the minimum DI. To our knowledge, this time-invariant achievability result is the first in the literature.
We propose a class of distributed algorithms for computing arithmetic averages (average consensus) over networks of agents connected through digital noisy broadcast channels. Our algorithms do not require the agents t...
详细信息
We propose a class of distributed algorithms for computing arithmetic averages (average consensus) over networks of agents connected through digital noisy broadcast channels. Our algorithms do not require the agents to have knowledge of the network structure, nor do they assume any noiseless feedback to be available. We prove convergence to consensus, with both number of channel uses and computational complexity which are poly-logarithmic in the desired precision.
暂无评论