DOI QR코드

DOI QR Code

A Dynamic Load Balancing Scheme Using Genetic Algorithm in Heterogeneous Distributed Systems

이질형 분산 시스템에서 유전자 알고리즘을 이용한 동적 부하 균등 기법

  • 이동우 (우송대학교 컴퓨터전자공학부) ;
  • 이성훈 (천안대학교 정보통신학부) ;
  • 황종선 (고려대학교 컴퓨터학과)
  • Published : 2003.03.01

Abstract

In a sender-initiated load balancing algorithm, a sender (overloaded processor) continues to send unnecessary request messages for load transfer until a receiver (underloaded processor) is found while the system load is heavy. Therefore, it yields many problems such as low cpu utilization and system throughput because of inefficient inter-processor communications until the sender receives an accept message from the receiver in this environment. This paper presents an approach based on genetic algorithm (GA) for dynamic load balancing in heterogeneous distributed systems. In this scheme the processors to which the requests are sent off are determined by the proposed GA to decrease unnecessary request messages.

송신자 개시 부하 균등 알고리즘에서는 전체 시스템이 과부하일 때 송신자(과부하 프로세서)가 부하를 이전하기 위해 수신자(과부하 프로세서)를 발견할 때까지 불필요한 이전 요청 메시지를 계속 보내게 된다. 따라서 이 같은 상황에서는 저부하 상태인 수신자 프로세서로부터 승인 메시지를 받기까지 불필요한 프로세서간 통신으로 인하여 프로세서의 이용률이 저하되고 또한 타스크의 처리율이 낮아지는 문제점이 발생한다. 본 논문에서는 이질형 분산 시스템에서의 동적 부하 균등을 위해 유전자 알고리즘을 기반으로 하는 접근 방법을 제안한다. 이 기법에서는 불필요한 요청 메시지를 줄이기 위해 요청 메시지가 전송될 프로세서들이 제안된 유전자 알고리즘에 의해 결정된다.

Keywords

References

  1. D. L. Eager, E. D. Lazowska, J. Zahorjan, 'Adaptive Load Sharing in Homogeneous Distributed Systems,' IEEE Transactions on Software Engineering, Vol.12, No.5, pp.662-675, May, 1986
  2. N. G. Shivaratri, P. Krueger and M. Singhal, 'Load Distributing for Locally Distributed Systems,' IEEE Computer, Vol.25, No.12, pp.33-44, December, 1992 https://doi.org/10.1109/2.179115
  3. J. Grefenstette, 'Optimization of Control Parameters for Genetic Algorithms,' IEEE Transactions on System, Man and Cybernetics, Vol.SMC-16, No.1, January, 1986 https://doi.org/10.1109/TSMC.1986.289288
  4. L. M. Ni, C. W. Xu and T. B. Gendreau, 'A Distributed Drafting Algorithm for Load Balancing,' IEEE Transactions on Software Engineering, Vol.SE-11, No.10, pp.1153-1161, October, 1985 https://doi.org/10.1109/TSE.1985.231863
  5. Philip D. Wasserman, Advanced Methods in Neural Computing, Van Nostrand Reinhold, New York, 1993
  6. Branco Soucek, Dynamic, Genetic and Chaotic Programming, John wiley & Sons, 1992
  7. M. Livny and M. Melman, 'Load Balancing in Homogeneous Broadcast Distributed Systems,' Proc. ACM Computer Network Performance Symp., pp.44-55, 1982 https://doi.org/10.1145/800047.801689
  8. Terence C. Fogarty, Frank Vavak and Phillip Cheng, 'Use of the Genetic Algorithm for Load Balancing of Sugar Beet Presses,' Proc. Sixth International Conference on Genetic Algorithms, pp.617-624, 1995
  9. Garrison W. Greenwood, Christian Lang and Steve Hurley, 'Scheduling Tasks in Real-Time systems Using Evolutionary Strategies,' Proc. Third Workshop on Parallel and Distributed Real-Time Systems, pp.195-196, 1995 https://doi.org/10.1109/WPDRTS.1995.470487
  10. Chin Lu and Sau-Ming Lau, 'An Adaptive Load Balancing Algorithm for Heterogeneous Distributed Systems with Multiple Task Classes,' Proc. International Conference on Distributed Computing Systems, pp.629-636, 1996
  11. David B. Fogel and Lawence J. Fogel, 'Using Evolutionary Programming to Schedule Tasks on a Suite of Heterogeneous Computers,' Computers & Operations Research, Vol.23, No.6, pp.527-534, 1996 https://doi.org/10.1016/0305-0548(95)00057-7
  12. S. H. Lee, T. W. Kang and C. S. Hwang, 'A Genetic Algorithm with a Local Improvement Mechanism for Dynamic Load Balancing in Distributed Systems,' Proc. 4th International Conference on Soft Computing, Vol.2, pp.486-489, 1996