• DocumentCode
    75213
  • Title

    Analysis of Finite Buffer Queue: Maximum Entropy Probability Distribution With Shifted Fractional Geometric and Arithmetic Means

  • Author

    Singh, Amit Kumar ; Singh, Harendra Pratap ; Karmeshu

  • Author_Institution
    Sch. of Comput. & Syst. Sci., Jawaharlal Nehru Univ., New Delhi, India
  • Volume
    19
  • Issue
    2
  • fYear
    2015
  • fDate
    Feb. 2015
  • Firstpage
    163
  • Lastpage
    166
  • Abstract
    A theoretical method based on maximum Shannon entropy framework (MSEF) in the presence of the geometric/or shifted fractional geometric mean of the queue size is applied to study the finite buffer system. Analytical expression of the loss probability for large buffer size is found to depict power law behavior. The maximum entropy framework is extended to incorporate additional shifted fractional arithmetic mean constraint to yield the expression of loss probability which is similar to the one derived by Kim and Shroff who have employed an entirely different approach based on maximum variance asymptotic (MVA) approximation. An important finding is the relationship between fractional order and the Hurst parameter. The advantage of MSEF is that it has enabled one to derive the analytical closed form generalized expression of the probability distribution of queue size in finite buffer system. Further, MSEF with shifted fractional geometric mean constraint gives the same distribution of queue size as the one obtained by maximizing Tsallis entropy subject to the fractional arithmetic mean of queue size.
  • Keywords
    approximation theory; buffer storage; maximum entropy methods; queueing theory; statistical distributions; Hurst parameter; MSEF; MVA; Tsallis entropy; analytical closed form generalized expression; buffer size; finite buffer queue analysis; finite buffer system; fractional order; loss probability; maximum Shannon entropy framework; maximum entropy probability distribution; maximum variance asymptotic approximation; power law behavior; queue size; shifted fractional arithmetic mean constraint; shifted fractional geometric means; Computers; Educational institutions; Entropy; Presses; Probability distribution; Queueing analysis; Maximum entropy principle; Shannon entropy; finite buffer system; loss probability; power law behavior;
  • fLanguage
    English
  • Journal_Title
    Communications Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1089-7798
  • Type

    jour

  • DOI
    10.1109/LCOMM.2014.2377236
  • Filename
    6975026