Fuzzy expert system for load balancing in symmetric multiprocessor systems

Mika Rantonen, Tapio Frantti (Corresponding Author), Kauko Leiviskä

Research output: Contribution to journalArticleScientificpeer-review

4 Citations (Scopus)

Abstract

The aim of this paper is to describe a fuzzy expert system for load balancing in a symmetric multiprocessor environment. Load balancing algorithms are used to share the load of the system fairly among the processors. The developed load balancing algorithm use on demand based approach instead of the periodic load balancing in order to get fast and fair load balancing with minimal computational overhead. It uses the number of threads per processor and total load of the system as inputs. The method is compared to the periodic and another developed on demand based algorithms. The results show that during the load balancing the periodic algorithm causes temporary idle periods in the processors whereas the developed on demand-based algorithms respond faster to the fluctuating load level, stabilize the load more equally among the processors and increase the performance of the system. The results also proof that the fuzzy load balancer achieves the best load balance among the processors as well as the fastest response time.
Original languageEnglish
Pages (from-to)8711-8720
JournalExpert Systems with Applications
Volume37
Issue number12
DOIs
Publication statusPublished - 2010
MoE publication typeA1 Journal article-refereed

Fingerprint

Expert systems
Resource allocation

Keywords

  • Fuzzy expert system
  • Load balancing
  • Scheduling
  • Symmetric multiprocessors system

Cite this

Rantonen, Mika ; Frantti, Tapio ; Leiviskä, Kauko. / Fuzzy expert system for load balancing in symmetric multiprocessor systems. In: Expert Systems with Applications. 2010 ; Vol. 37, No. 12. pp. 8711-8720.
@article{09a5d822c0984e6cad09a4f21637b76b,
title = "Fuzzy expert system for load balancing in symmetric multiprocessor systems",
abstract = "The aim of this paper is to describe a fuzzy expert system for load balancing in a symmetric multiprocessor environment. Load balancing algorithms are used to share the load of the system fairly among the processors. The developed load balancing algorithm use on demand based approach instead of the periodic load balancing in order to get fast and fair load balancing with minimal computational overhead. It uses the number of threads per processor and total load of the system as inputs. The method is compared to the periodic and another developed on demand based algorithms. The results show that during the load balancing the periodic algorithm causes temporary idle periods in the processors whereas the developed on demand-based algorithms respond faster to the fluctuating load level, stabilize the load more equally among the processors and increase the performance of the system. The results also proof that the fuzzy load balancer achieves the best load balance among the processors as well as the fastest response time.",
keywords = "Fuzzy expert system, Load balancing, Scheduling, Symmetric multiprocessors system",
author = "Mika Rantonen and Tapio Frantti and Kauko Leivisk{\"a}",
year = "2010",
doi = "10.1016/j.eswa.2010.06.049",
language = "English",
volume = "37",
pages = "8711--8720",
journal = "Expert Systems with Applications",
issn = "0957-4174",
publisher = "Elsevier",
number = "12",

}

Fuzzy expert system for load balancing in symmetric multiprocessor systems. / Rantonen, Mika; Frantti, Tapio (Corresponding Author); Leiviskä, Kauko.

In: Expert Systems with Applications, Vol. 37, No. 12, 2010, p. 8711-8720.

Research output: Contribution to journalArticleScientificpeer-review

TY - JOUR

T1 - Fuzzy expert system for load balancing in symmetric multiprocessor systems

AU - Rantonen, Mika

AU - Frantti, Tapio

AU - Leiviskä, Kauko

PY - 2010

Y1 - 2010

N2 - The aim of this paper is to describe a fuzzy expert system for load balancing in a symmetric multiprocessor environment. Load balancing algorithms are used to share the load of the system fairly among the processors. The developed load balancing algorithm use on demand based approach instead of the periodic load balancing in order to get fast and fair load balancing with minimal computational overhead. It uses the number of threads per processor and total load of the system as inputs. The method is compared to the periodic and another developed on demand based algorithms. The results show that during the load balancing the periodic algorithm causes temporary idle periods in the processors whereas the developed on demand-based algorithms respond faster to the fluctuating load level, stabilize the load more equally among the processors and increase the performance of the system. The results also proof that the fuzzy load balancer achieves the best load balance among the processors as well as the fastest response time.

AB - The aim of this paper is to describe a fuzzy expert system for load balancing in a symmetric multiprocessor environment. Load balancing algorithms are used to share the load of the system fairly among the processors. The developed load balancing algorithm use on demand based approach instead of the periodic load balancing in order to get fast and fair load balancing with minimal computational overhead. It uses the number of threads per processor and total load of the system as inputs. The method is compared to the periodic and another developed on demand based algorithms. The results show that during the load balancing the periodic algorithm causes temporary idle periods in the processors whereas the developed on demand-based algorithms respond faster to the fluctuating load level, stabilize the load more equally among the processors and increase the performance of the system. The results also proof that the fuzzy load balancer achieves the best load balance among the processors as well as the fastest response time.

KW - Fuzzy expert system

KW - Load balancing

KW - Scheduling

KW - Symmetric multiprocessors system

U2 - 10.1016/j.eswa.2010.06.049

DO - 10.1016/j.eswa.2010.06.049

M3 - Article

VL - 37

SP - 8711

EP - 8720

JO - Expert Systems with Applications

JF - Expert Systems with Applications

SN - 0957-4174

IS - 12

ER -