Abstract :
Notice of Violation of IEEE Publication Principles
"On the Analysis of Queues with Long Range Dependent Traffic: An Extended Maximum Entropy Approach,"
by D. Kouvatsos, and S.A. Assi,
in the Proceedings of the 3rd EuroNGI Conference on Next Generation Internet Networks, May 2007, pp. 226-233
After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE\´s Publication Principles.
This paper contains significant portions of original text from the unpublished work of the authors cited below. The original text was copied without attribution and without permission.
"Long Tail Behavior of Queue Lengths in Broadband Networks: Tsallis Entropy Framework"
by Karmeshu Gupta and Shachi Sharma, July 2005
http://arxiv.org/abs/1012.2464
An extended maximum entropy (EME) framework is proposed for capturing long tail behaviour of queue lengths in broadband heterogeneous networks. The work is based on the maximisation of Tsaliis parametric entropy function for non-extensive systems subject to appropriate mean value constraints. Novel closed form expressions and asymptotic power laws are characterised for the state probabilities of single server queues with (or, without) finite capacity and self-similar/long-range dependent traffic. The EME approach employs, by analogy, as a mean queue length constraint, a heuristic generalisation of a formula suggested by Norros in the context of a simple storage model with infinite capacity and fractional Brownian motion (FBM) process as an input traffic process. Consequently, a relationship is postulated between the non-extensivity parameter, q, of Tsallis entropy and the Hurst self-similarity measure, H. Moreover, efficient numerical procedures are devised, based on the Newton-Raphson method, to compute the Lagrange\´s undetermined multipliers and, thus, the EME queue length distributions and- associated performance metrics. Typical numerical tests are included to assess the credibility of the EME solutions and the adverse impact of self-similar traffic on queue performance.
Keywords :
Brownian motion; Newton-Raphson method; broadband networks; maximum entropy methods; optimisation; probability; queueing theory; telecommunication traffic; Hurst self-similarity measure; Newton-Raphson method; Tsallis parametric entropy function; asymptotic power law; broadband heterogeneous network; closed form expression; extended maximum entropy framework; fractional Brownian motion process; long range dependent traffic; maximisation; nonextensive system; queue analysis; simple storage model; state probability; Performance modelling and evaluation; Tsallis entropy function; fractional Brownian motion (FBM); heterogeneous networks; long range dependence; maximum entropy (ME) principle; self-similarity;
