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Elusive Statistical Property of Arrival Rate and Holding Time used in Mobile Communication Networks

by Osahenvemwen O.a, Edeko F.o, Emagbetere J.
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 59 - Number 2
Year of Publication: 2012
Authors: Osahenvemwen O.a, Edeko F.o, Emagbetere J.
10.5120/9518-3922

Osahenvemwen O.a, Edeko F.o, Emagbetere J. . Elusive Statistical Property of Arrival Rate and Holding Time used in Mobile Communication Networks. International Journal of Computer Applications. 59, 2 ( December 2012), 15-18. DOI=10.5120/9518-3922

@article{ 10.5120/9518-3922,
author = { Osahenvemwen O.a, Edeko F.o, Emagbetere J. },
title = { Elusive Statistical Property of Arrival Rate and Holding Time used in Mobile Communication Networks },
journal = { International Journal of Computer Applications },
issue_date = { December 2012 },
volume = { 59 },
number = { 2 },
month = { December },
year = { 2012 },
issn = { 0975-8887 },
pages = { 15-18 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume59/number2/9518-3922/ },
doi = { 10.5120/9518-3922 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:05:01.212721+05:30
%A Osahenvemwen O.a
%A Edeko F.o
%A Emagbetere J.
%T Elusive Statistical Property of Arrival Rate and Holding Time used in Mobile Communication Networks
%J International Journal of Computer Applications
%@ 0975-8887
%V 59
%N 2
%P 15-18
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This research work is aimed at the study of arrival rate and holding time used in mobile communication networks, also to determine the best suitable statistical probability distribution of both arrival rate and holding time or service time in mobile communication network. The most general acceptable assumption about arrival rate is Poisson distribution and the holding time is exponential distribution in traffic modeling of mobile communication networks. Exhaustive literature review is deployed for details explanation on discrete random variables of arrival rate and continuous holding time use in traffic modeling of mobile communication networks. From the research work, the arrival rate is explained using point process or counting process, which leads to two unique properties, they are orderly and memorylessness. These unique properties are possessed by Bernoulli process with is discrete time, having Geometric distribution function, also with Poisson process, which is continuous time and discrete space, having Exponential distribution function which is used to characterize arrival rate based on interarrival rate process. Therefore, from the research work, it is assumed that arrivals rate is Poisson distribution and service time or holding time is exponentially distributed in traffic situation in mobile communication networks. These statistical properties since to the best suitable in mobile communication networks because of their unique parameters and are simple to analyses.

References
  1. Alberto E . Garcia and Elaus D. Hackbarth (2008) ,Approximation to a Behavioral Model for Estimating Traffic Aggregation scenarios,Journal of Universal Computer Science,Vol. 14,No. 5,pp 732-744
  2. Balint C. ,Budura G. , Budura A. , and Marza E. ,(2009),Dimensioning Rules Regarding Radio Resources In GSM /GPRS Network, WSEAS Transactions on Communications, Issue 8, Vol. 8,pp822-832.
  3. Chi Wa Leong, Weihua Zhuang, yu Cheng, and Lei Wang (2004),Call Admission Control for Integrated ON/OFF Voice and Best Effect Data Services In Mobile Cellular Communications, IEEE Transactions On Communications , Vol. 52, No. 5,pp 778-781
  4. Georgeta, B. , Cornel, B. , Adrian, B. and Eugen, M. (2009). "Traffic models and Associated parameters in GSM/(E)GPRS Networks"WSEAS Transaction on Communications,ISSN:1109-2742,Issue
  5. Hong D. and Rappaport S. (1986) Traffic model and performance analysis for cellular mobile radio telephone systems with prioritized and nonprioritized handoff procedures, IEEE Trans. Veh. Technol. Vol. VT-35, pp72-928, Volume 8,pp 833-841.
  6. Khan F. and Zeghalache D. ,(1997),Effect of cell residence time distribution on the performance of cellular mobile networks, in Proc. IEEE VTC 97 Phoenix Pp949-953.
  7. Kuumola E. , Resing ,J. Virtamo J. (2002),Joint Distribution of instantaneous and Average Queue length in an M/M/1/K System. In proceeding of the 15th Teletraffic congress specialist seminar "internet Traffic Engineering and Traffic management". Wurzburg, Germany Pp58-67.
  8. Sanjay, S. (2010). Computer networks, 1st Edition, S. K. Kataria and Sons, page 621-629.
  9. Singh L. K and Srivastava R. (2007) "Memory estimation of internet server using queuing theory:comparative study between M/G/1,G/M/1 &G/G/1 queuing model" world academy of science, engineering and Technology 33 page 153-157
  10. Stefano B. ,Roberto C. ,and Maurizio D. (2008)"An Empirical study on time –correlation of GSM telephone traffic"IEEE Transactions on wireless communications,Vol. 7,No. 9,pp3428-3435.
  11. Yuguang Fang(2005)"Modeling and Performance Analysis for wireless mobile networks:A New Analytical Approach" IEEE/ACM Transactions on Networking, Vol. 13,no. 5,pp 989-1002.
  12. Zukerman Moshe (2010) "Introduction to queue theory and stochastic teletraffic model"pp 67,87,104-127.
  13. http://www Cellular traffic-Wikipedia; Channeling holding time, page
  14. http://www. itu. int. "Teletraffic Engineering" International Telecommunication union page 68-69, 119-186, ITU-D 2/4/2010.
Index Terms

Computer Science
Information Sciences

Keywords

Random process exponentially distribution interarrival time orderly and memoryless

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