Proceedings Article10.1109/CDC.2008.4738886
Quantized average consensus via dynamic coding/decoding schemes
Ruggero Carli,Francesco Bullo,Sandro Zampieri +2 more
- 01 Dec 2008
- pp 4916-4921
TL;DR: A consensus strategy in which the systems can exchange information among themselves according to a fixed connected digital communication network and two different encoding/decoding strategies are presented with theoretical and simulation results on their performance.
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Abstract: In the average consensus a set of linear systems has to be driven to the same final state which corresponds to the average of their initial states. This contribution presents a consensus strategy in which the systems can exchange information among themselves according to a fixed connected digital communication network. Beside the decentralized computational aspects induced by the choice of the communication network, we here have also to face the quantization effects due to the digital links. We here present and discuss two different encoding/decoding strategies with theoretical and simulation results on their performance.
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Citations
Global Synchronization of Complex Dynamical Networks Through Digital Communication With Limited Data Rate
TL;DR: This paper studies the global synchronization of complex dynamical network (CDN) under digital communication with limited bandwidth with so-called uniform-quantizer-sets, where a scaling function is utilized to guarantee the quantizers having bounded inputs and thus achieving bounded real-time quantization levels.
A Continuous-Time Algorithm with Quantified Event-Triggered for Distributed Resource Allocation Optimization
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On the convergence time of asynchronous distributed quantized averaging algorithms
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TL;DR: This paper introduces a class of distributed quantized averaging algorithms for asynchronous networks with fixed, switching, and random topologies, deriving polynomial bounds on the expected convergence time using random walks on graphs.
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Efficient information aggregation strategies for distributed control and signal processing
TL;DR: It is shown that a number of distributed control and signal processing problems can be solved straightforwardly if solutions to the averaging problem are available and a new model for distributed function computation which reflects the constraints facing many large-scale networks is proposed.
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On the Benefits of Multiple Gossip Steps in Communication-Constrained Decentralized Optimization.
TL;DR: This work shows that having gradient iterations with constant step size enables convergence to within $\epsilon$ of the optimal value for smooth non-convex objectives satisfying Polyak-Łojasiewicz condition, and this result also holds for smooth strongly convex objectives.
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Reza Olfati-Saber,J.A. Fax,Richard M. Murray +2 more
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TL;DR: A theoretical framework for analysis of consensus algorithms for multi-agent networked systems with an emphasis on the role of directed information flow, robustness to changes in network topology due to link/node failures, time-delays, and performance guarantees is provided.