• DocumentCode
    3370121
  • Title

    Load Balancing Based on Group Analytic Hierarchy Process

  • Author

    Jian-dong Zhang ; Xuan Ma ; Jin Yang ; Zhong-Hua Li

  • Author_Institution
    Dept. of Comput. Sci., LeShan Normal Univ., Leshan, China
  • fYear
    2013
  • fDate
    14-15 Dec. 2013
  • Firstpage
    758
  • Lastpage
    762
  • Abstract
    When determining the weights of the factor influencing the cluster system load balancing, judgments are inevitably somehow subjective, which will affect the results of decision making. Reducing the influence on weights from subjective factors as much as possible is very important for load balancing. This paper introduces the group decision theory based on analytic hierarchy process (AHP) and constructs load balancing model based on the group AHP. The dynamic weights of each expert can be obtained by analyzing the similarity of judgment matrixes experts offer, and then we can get the objective and representative polymerization decisive opinions which enhance the reliability of the decision-making results. The experiments in the paper prove the validity of the method which is simple and easy to implement.
  • Keywords
    analytic hierarchy process; decision theory; matrix algebra; resource allocation; cluster system load balancing; decision making; dynamic weights; group AHP; group analytic hierarchy process; group decision theory; judgment matrixes similarity; load balancing model; objective polymerization decisive opinions; representative polymerization decisive opinions; Analytic hierarchy process; Indexes; Load management; Load modeling; Servers; Vectors; analytic hierarchy process (AHP); group decision making; judgment matrix; load balancing; weight of decision-maker;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Security (CIS), 2013 9th International Conference on
  • Conference_Location
    Leshan
  • Print_ISBN
    978-1-4799-2548-3
  • Type

    conf

  • DOI
    10.1109/CIS.2013.165
  • Filename
    6746533