Achieving Robust Average Consensus Over Lossy Wireless Networks

Acciani, Francesco; Frasca, Paolo; Heijenk, Geert; Stoorvogel, Anton A.

doi:10.1109/tcns.2018.2800407

Cited by 12 publications

(10 citation statements)

References 20 publications

(31 reference statements)

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“…lower convergence rate) and a higher deceleration. This statement is concluded also in [35]. In [37], the experiments show that a higher probability of the successful transmission (and so, a lower value of a communication breakdown) ensures a higher convergence rate.…”

Section: Discussion About Achieved Resultsmentioning

confidence: 53%

“…This statement is confirmed in [35], where the authors change the connectivity probability and its lower values result in a slower convergence rate.…”

Section: Discussion About Achieved Resultsmentioning

confidence: 61%

“…In [35], the authors pay their attention to a compensation mechanism for lost information caused by transmitter-based random failures. In the analysis, they demonstrate the impact of the failure on a network formed by 81 nodes.…”

Section: Related Workmentioning

confidence: 99%

“…They show that the nodes are able to reach the consensus in spite of these constraints and find the trade-off between the mean square error (determining the precision of the states) and the convergence rate of the algorithm. It is proven that the mean square error takes low values when the convergence rate of the algorithm is low.In [35], the authors pay their attention to a compensation mechanism for lost information caused by transmitter-based random failures. In the analysis, they demonstrate the impact of the failure on a network formed by 81 nodes.…”

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confidence: 99%

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Evaluation of Natural Robustness of Best Constant Weights to Random Communication Breakdowns

Kenyeres

Bürget

2018

JCOMSS

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Abstract-One of the most crucial aspects of an algorithm design for the wireless sensors networks is the failure tolerance. A high natural robustness and an effectively bounded execution time are factors that can significantly optimize the overall energy consumption and therefore, a great emphasis is laid on these aspects in many applications from the area of the wireless sensor networks. This paper addresses the robustness of the optimized Best Constant weights of Average Consensus with a stopping criterion (i.e. the algorithm is executed in a finite time) and their five variations with a lower mixing parameter (i.e. slower variants) to random communication breakdowns modeled as a stochastic event of a Bernoulli distribution. We choose three metrics, namely the deviation of the least precise final estimates from the average, the convergence rate expressed as the number of the iterations for the consensus, and the deceleration of each initial setup, in order to evaluate the robustness of various initial setups of Best Constant weights under a varying failure probability and over 30 random geometric graphs of either a strong or a weak connectivity. Our contribution is to find the most robust initial setup of Best Constant weights according to numerical experiments executed in Matlab. Finally, the experimentally obtained results are discussed, compared to the results from the error-free executions, and our conclusions are compared with the conclusions from related papers.Index Terms-Distributed computing, Average Consensus algorithm, Best Constant weights, communication breakdowns, failure analysis. I. INTRODUCTIONIRELESS Sensor Networks (abbreviated as WSNs) is a technology with a wide usage in the field of the realtime detection of global events and monitoring [1]. Manuscript received March 15, 2018; revised August 20, 2018. Date of publication September 4, 2018. Prof. Nikola Rožić has been coordinating the review of this manuscript and approved it for publication.Martin Kenyeres and Radim Burget are with Department of Telecommunications, Brno University of Technology, Technicka 12, Brno, burget@feec.vutbr.cz).Jozef Kenyeres is with Sipwise GmbH, Europaring F15, 2345 Brunn am Gebirge, Austria. (e-mail: jkenyeres@sipwise.com).Research described in this paper was financed by the National Sustainability Program under grant LO1401. For the research, infrastructure of the SIX Center was used.Digital Object Identifier (DOI): 10.24138/jcomss.v14i3.487These networks consist of power and computationally constrained devices (labeled as nodes) situated in a geographical area in order to sense important information about a particular physical quantity, process it, share the measured data with other nodes and make a meaningful decision on the observed quantity [2]. Due to their specific character, the WSNs find the usage in various applications such as military surveillance, a natural disaster detection, industrial automation, inventory tracking, an acoustic detection, wildlife applications, medical systems, target tracking,...

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Section: Discussion About Achieved Resultsmentioning

confidence: 53%

“…This statement is confirmed in [35], where the authors change the connectivity probability and its lower values result in a slower convergence rate.…”

Section: Discussion About Achieved Resultsmentioning

confidence: 61%

Section: Related Workmentioning

confidence: 99%

mentioning

confidence: 99%

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Evaluation of Natural Robustness of Best Constant Weights to Random Communication Breakdowns

Kenyeres

Bürget

2018

JCOMSS

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“…For the other type of consensus problems, validity property is stated differently or not defined. For example, validity property for average consensus [1] and max-min consensus [8], which are mostly used in robotics, is not defined. In this paper, we focus on a subset of the first type which is subject to FLP [4] (it is leader-based and should provide strong consistency in addition to satisfying validity).…”

Section: Introductionmentioning

confidence: 99%

Time-Based Consensus

Heydari

Silvestre

Larrieu

et al. 2020

Euro-Par 2019: Parallel Processing Workshops

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Reaching consensus is fundamental in distributed computing. For each execution of a consensus algorithm, there is no difference between the proposed values by different nodes with respect to their proposed times. By presenting a realistic application scenario related to distributed asynchronous mobile robots in dynamic environments, we argue some safety-critical, real-time systems require reaching consensus on the newest proposed values when the old proposed values may not be valid anymore. Afterward, we formulate a new type of consensus problem called time-based consensus, which requires to take into account the times of proposed values. Finally, to tackle such a consensus problem, we determine an essential characteristic which should be considered.

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Retracted: State estimation of Takagi‐Sugeno fuzzy system in networked control system with stochastic time delays under unknown attacks

Shamrooz

2021

Adaptive Control & Signal

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This article concerns the event‐triggered fuzzy filter design for Takagi‐Sugeno (T‐S) fuzzy systems subject to deception attacks under the stochastic multiple time‐varying delays. A sequence of random variables, which are mutually independent but obey the Bernoulli distribution, is introduced to account for the randomly occurring communication delays. In order to efficiently utilize limited network communication bandwidth resources, the event‐triggering scheme is adopted. A fuzzy filter with the attacked input signal is presented. Moreover, due to communication delays caused by event‐triggering schemes and transmission, the filter adopts non‐synchronous premise variables with the system. Then, by utilizing a model transformation technique, the fuzzy systems are developed. Furthermore, using the piecewise Lyapunov functional method technique, the resulting criterion provides sufficient conditions to ensure that fuzzy systems under deception attacks are stochastically stable with an H∞ performance. Accordingly, the conditions for the co‐design of the fuzzy filter and event‐triggering schemes are given. Finally, numerical simulation with the industrial process provided to verify the proposed event‐triggered design.

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Achieving Robust Average Consensus Over Lossy Wireless Networks

Cited by 12 publications

References 20 publications

Evaluation of Natural Robustness of Best Constant Weights to Random Communication Breakdowns

Evaluation of Natural Robustness of Best Constant Weights to Random Communication Breakdowns

Time-Based Consensus

Retracted: State estimation of Takagi‐Sugeno fuzzy system in networked control system with stochastic time delays under unknown attacks

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