Comparative Study of Distributed Estimation Precision by Average Consensus Weight Models

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F17%3APU125891" target="_blank" >RIV/00216305:26220/17:PU125891 - isvavai.cz</a>

Výsledek na webu

<a href="https://jcomss.fesb.unist.hr/index.php/jcomss/article/view/405" target="_blank" >https://jcomss.fesb.unist.hr/index.php/jcomss/article/view/405</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.24138/jcomss.v13i4.405" target="_blank" >10.24138/jcomss.v13i4.405</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Comparative Study of Distributed Estimation Precision by Average Consensus Weight Models

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Comparative Study of Distributed Estimation Precision by Average Consensus Weight Models

Popis výsledku anglicky

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.

Druh

J_SC - Článek v periodiku v databázi SCOPUS

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2017

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Journal of Communications Software and Systems

ISSN

1845-6421

e-ISSN

—

Svazek periodika

13

Číslo periodika v rámci svazku

4

Stát vydavatele periodika

HR - Chorvatská republika

Počet stran výsledku

13

Strana od-do

165-177

Kód UT WoS článku

—

EID výsledku v databázi Scopus

2-s2.0-85042519177