Evaluation of Natural Robustness of Best Constant Weights to Random Communication Breakdowns
One of the most crucial aspects of an algorithmdesign for the wireless sensors networks is the failure tolerance.A high natural robustness and an effectively bounded executiontime are factors that can significantly optimize the overall energyconsumption and therefore, a great emphasis is laid on the...
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doaj-adc2fff384e142fea11edf1fb6cf17e72020-11-24T21:09:59ZengCroatian Communications and Information Society (CCIS)Journal of Communications Software and Systems1845-64211846-60792018-09-01143201210Evaluation of Natural Robustness of Best Constant Weights to Random Communication BreakdownsMartin KenyeresJozef KenyeresRadim BurgetOne of the most crucial aspects of an algorithmdesign for the wireless sensors networks is the failure tolerance.A high natural robustness and an effectively bounded executiontime are factors that can significantly optimize the overall energyconsumption and therefore, a great emphasis is laid on theseaspects in many applications from the area of the wireless sensornetworks. This paper addresses the robustness of the optimizedBest Constant weights of Average Consensus with a stoppingcriterion (i.e. the algorithm is executed in a finite time) and theirfive variations with a lower mixing parameter (i.e. slowervariants) to random communication breakdowns modeled as a stochastic event of a Bernoulli distribution. We choose threemetrics, namely the deviation of the least precise final estimatesfrom the average, the convergence rate expressed as the numberof the iterations for the consensus, and the deceleration of eachinitial setup, in order to evaluate the robustness of various initialsetups of Best Constant weights under a varying failureprobability and over 30 random geometric graphs of either astrong or a weak connectivity. Our contribution is to find themost robust initial setup of Best Constant weights according tonumerical experiments executed in Matlab. Finally, theexperimentally obtained results are discussed, compared to theresults from the error-free executions, and our conclusions arecompared with the conclusions from related papers.https://jcomss.fesb.unist.hr/index.php/jcomss/article/view/487distributed computingaverage consensusbest constant weightscommunication breakdownsfailure analysis |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Martin Kenyeres Jozef Kenyeres Radim Burget |
spellingShingle |
Martin Kenyeres Jozef Kenyeres Radim Burget Evaluation of Natural Robustness of Best Constant Weights to Random Communication Breakdowns Journal of Communications Software and Systems distributed computing average consensus best constant weights communication breakdowns failure analysis |
author_facet |
Martin Kenyeres Jozef Kenyeres Radim Burget |
author_sort |
Martin Kenyeres |
title |
Evaluation of Natural Robustness of Best Constant Weights to Random Communication Breakdowns |
title_short |
Evaluation of Natural Robustness of Best Constant Weights to Random Communication Breakdowns |
title_full |
Evaluation of Natural Robustness of Best Constant Weights to Random Communication Breakdowns |
title_fullStr |
Evaluation of Natural Robustness of Best Constant Weights to Random Communication Breakdowns |
title_full_unstemmed |
Evaluation of Natural Robustness of Best Constant Weights to Random Communication Breakdowns |
title_sort |
evaluation of natural robustness of best constant weights to random communication breakdowns |
publisher |
Croatian Communications and Information Society (CCIS) |
series |
Journal of Communications Software and Systems |
issn |
1845-6421 1846-6079 |
publishDate |
2018-09-01 |
description |
One of the most crucial aspects of an algorithmdesign for the wireless sensors networks is the failure tolerance.A high natural robustness and an effectively bounded executiontime are factors that can significantly optimize the overall energyconsumption and therefore, a great emphasis is laid on theseaspects in many applications from the area of the wireless sensornetworks. This paper addresses the robustness of the optimizedBest Constant weights of Average Consensus with a stoppingcriterion (i.e. the algorithm is executed in a finite time) and theirfive variations with a lower mixing parameter (i.e. slowervariants) to random communication breakdowns modeled as a stochastic event of a Bernoulli distribution. We choose threemetrics, namely the deviation of the least precise final estimatesfrom the average, the convergence rate expressed as the numberof the iterations for the consensus, and the deceleration of eachinitial setup, in order to evaluate the robustness of various initialsetups of Best Constant weights under a varying failureprobability and over 30 random geometric graphs of either astrong or a weak connectivity. Our contribution is to find themost robust initial setup of Best Constant weights according tonumerical experiments executed in Matlab. Finally, theexperimentally obtained results are discussed, compared to theresults from the error-free executions, and our conclusions arecompared with the conclusions from related papers. |
topic |
distributed computing average consensus best constant weights communication breakdowns failure analysis |
url |
https://jcomss.fesb.unist.hr/index.php/jcomss/article/view/487 |
work_keys_str_mv |
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1716756722659360768 |