Modified differential evolution in the load balancing problem for the iFDAQ of the COMPASS experiment at CERN

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21340%2F19%3A00335039" target="_blank" >RIV/68407700:21340/19:00335039 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.5220/0008319102130220" target="_blank" >https://doi.org/10.5220/0008319102130220</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.5220/0008319102130220" target="_blank" >10.5220/0008319102130220</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Modified differential evolution in the load balancing problem for the iFDAQ of the COMPASS experiment at CERN

Popis výsledku v původním jazyce

In general, state-of-the-art data acquisition systems in high energy physics experiments must satisfy high requirements in terms of reliability, efficiency and data rate capability. The paper introduces the Load Balancing (LB) problem of the intelligent, FPGA-based Data Acquisition System (iFDAQ) of the COMPASS experiment at CERN and proposes a solution based on genetic algorithms. Since the LB problem is NP-complete, it challenges analytical and heuristic methods in finding optimal solutions in reasonable time. Differential Evolution (DE) is a type of evolutionary algorithms, which has been used in many optimization problems due to its simplicity and efficiency. Therefore, the Modified Differential Evolution (MDE) is inspired by DE and is presented in more detail. The MDE algorithm has newly-designed crossover and mutation operator and its selection mechanism is inspired by Simulated Annealing (SA). Moreover, the proposal uses an adaptive scaling factor and recombination rate affecting the exploration and exploitation of the MDE algorithm. Thus, the MDE represents a new efficient stochastic search technique for the LB problem. The proposed MDE algorithm is examined on two LB test cases and compared with other LB solution methods.

Název v anglickém jazyce

Modified differential evolution in the load balancing problem for the iFDAQ of the COMPASS experiment at CERN

Popis výsledku anglicky

In general, state-of-the-art data acquisition systems in high energy physics experiments must satisfy high requirements in terms of reliability, efficiency and data rate capability. The paper introduces the Load Balancing (LB) problem of the intelligent, FPGA-based Data Acquisition System (iFDAQ) of the COMPASS experiment at CERN and proposes a solution based on genetic algorithms. Since the LB problem is NP-complete, it challenges analytical and heuristic methods in finding optimal solutions in reasonable time. Differential Evolution (DE) is a type of evolutionary algorithms, which has been used in many optimization problems due to its simplicity and efficiency. Therefore, the Modified Differential Evolution (MDE) is inspired by DE and is presented in more detail. The MDE algorithm has newly-designed crossover and mutation operator and its selection mechanism is inspired by Simulated Annealing (SA). Moreover, the proposal uses an adaptive scaling factor and recombination rate affecting the exploration and exploitation of the MDE algorithm. Thus, the MDE represents a new efficient stochastic search technique for the LB problem. The proposed MDE algorithm is examined on two LB test cases and compared with other LB solution methods.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

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

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2019

Kód důvěrnosti údajů

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

Název statě ve sborníku

Proceedings of the 11th International Joint Conference on Computational Intelligence

ISBN

978-989-758-384-1

ISSN

—

e-ISSN

—

Počet stran výsledku

8

Strana od-do

213-220

Název nakladatele

SciTePress - Science and Technology Publications

Místo vydání

Porto

Místo konání akce

Viden

Datum konání akce

17. 9. 2019

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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