Comparative Study of Distributed Estimation Precision by Average Consensus Weight Models
Distributed algorithms for an aggregate function estimation are an important complement of many real-life applications based on wireless sensor networks. Achieving a high precision of an estimation in a shorter time can optimize the overall energy consumption. Therefore, the choice of a proper distr...
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doaj-ccc6483b869545098bf11cb2d125289a2020-11-24T21:16:58ZengCroatian Communications and Information Society (CCIS)Journal of Communications Software and Systems1845-64211846-60792017-12-01134165177Comparative Study of Distributed Estimation Precision by Average Consensus Weight ModelsMartin KenyeresJozef KenyeresDistributed algorithms for an aggregate function estimation are an important complement of many real-life applications based on wireless sensor networks. Achieving a high precision of an estimation in a shorter time can optimize the overall energy consumption. Therefore, the choice of a proper distributed algorithm is an important part of an application design. In this study, we focus our attention on the average consensus algorithm and evaluate six weight models appropriate for the implementation into real-life applications. Our aim is to find the most suitable model in terms of the estimation precision in various phases of the algorithm. We examine the deviation of the least precise estimate over iterations for a Gaussian, a Uniform and a Bernoulli distribution of the initial states in strongly and weakly connected networks with a randomly generated topology. We examine which model is the most and the least precise in various phases. Based on these findings, we determine the most suitable model for real-life applications.https://jcomss.fesb.unist.hr/index.php/jcomss/article/view/405Distributed computingwireless sensor networksaverage consensus algorithmestimation precision |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Martin Kenyeres Jozef Kenyeres |
spellingShingle |
Martin Kenyeres Jozef Kenyeres Comparative Study of Distributed Estimation Precision by Average Consensus Weight Models Journal of Communications Software and Systems Distributed computing wireless sensor networks average consensus algorithm estimation precision |
author_facet |
Martin Kenyeres Jozef Kenyeres |
author_sort |
Martin Kenyeres |
title |
Comparative Study of Distributed Estimation Precision by Average Consensus Weight Models |
title_short |
Comparative Study of Distributed Estimation Precision by Average Consensus Weight Models |
title_full |
Comparative Study of Distributed Estimation Precision by Average Consensus Weight Models |
title_fullStr |
Comparative Study of Distributed Estimation Precision by Average Consensus Weight Models |
title_full_unstemmed |
Comparative Study of Distributed Estimation Precision by Average Consensus Weight Models |
title_sort |
comparative study of distributed estimation precision by average consensus weight models |
publisher |
Croatian Communications and Information Society (CCIS) |
series |
Journal of Communications Software and Systems |
issn |
1845-6421 1846-6079 |
publishDate |
2017-12-01 |
description |
Distributed algorithms for an aggregate function estimation are an important complement of many real-life applications based on wireless sensor networks. Achieving a high precision of an estimation in a shorter time can optimize the overall energy consumption. Therefore, the choice of a proper distributed algorithm is an important part of an application design. In this study, we focus our attention on the average consensus algorithm and evaluate six weight models appropriate for the implementation into real-life applications. Our aim is to find the most suitable model in terms of the estimation precision in various phases of the algorithm. We examine the deviation of the least precise estimate over iterations for a Gaussian, a Uniform and a Bernoulli distribution of the initial states in strongly and weakly connected networks with a randomly generated topology. We examine which model is the most and the least precise in various phases. Based on these findings, we determine the most suitable model for real-life applications. |
topic |
Distributed computing wireless sensor networks average consensus algorithm estimation precision |
url |
https://jcomss.fesb.unist.hr/index.php/jcomss/article/view/405 |
work_keys_str_mv |
AT martinkenyeres comparativestudyofdistributedestimationprecisionbyaverageconsensusweightmodels AT jozefkenyeres comparativestudyofdistributedestimationprecisionbyaverageconsensusweightmodels |
_version_ |
1726015036219981824 |