CFP last date
22 April 2024
Reseach Article

Dynamic Pricing for Congestion Avoidance and Utilization Improvement in Wireless Cellular Networks

Published on March 2012 by G. S. Mundada, B. S. Chaudhari, A. V. Walke
International Conference and Workshop on Emerging Trends in Technology
Foundation of Computer Science USA
ICWET2012 - Number 6
March 2012
Authors: G. S. Mundada, B. S. Chaudhari, A. V. Walke
76823fae-3d6e-468a-baae-3bafaed13989

G. S. Mundada, B. S. Chaudhari, A. V. Walke . Dynamic Pricing for Congestion Avoidance and Utilization Improvement in Wireless Cellular Networks. International Conference and Workshop on Emerging Trends in Technology. ICWET2012, 6 (March 2012), 31-34.

@article{
author = { G. S. Mundada, B. S. Chaudhari, A. V. Walke },
title = { Dynamic Pricing for Congestion Avoidance and Utilization Improvement in Wireless Cellular Networks },
journal = { International Conference and Workshop on Emerging Trends in Technology },
issue_date = { March 2012 },
volume = { ICWET2012 },
number = { 6 },
month = { March },
year = { 2012 },
issn = 0975-8887,
pages = { 31-34 },
numpages = 4,
url = { /proceedings/icwet2012/number6/5355-1046/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference and Workshop on Emerging Trends in Technology
%A G. S. Mundada
%A B. S. Chaudhari
%A A. V. Walke
%T Dynamic Pricing for Congestion Avoidance and Utilization Improvement in Wireless Cellular Networks
%J International Conference and Workshop on Emerging Trends in Technology
%@ 0975-8887
%V ICWET2012
%N 6
%P 31-34
%D 2012
%I International Journal of Computer Applications
Abstract

With tremendous growth in the wireless industry and due to scarcity of spectrum, the future cellular network will be limited by the number of channels available in each cell. The solutions like sectoring, cell splitting cannot cope up with the ever increasing demand of the subscribers. One of the other options to control the demand is through the economical means. Cellular users are sensitive to price and it can act as a tool to determine number of incoming calls and control the duration of such calls. In this paper we have studied and analyzed theimpact of dynamic pricing on traffic and congestion in cellular networks. The simulations are carried out using fixed, linear and nonlinear pricing for the incoming calls. The obtained results show that using dynamic pricing strategies in cellular networks reduces the congestion and blocking probability. It increases the system utilization. The results also illustrates that the dynamic nonlinear pricing has better performance than that of dynamic linear pricing.

References
  1. S.Yaipairoj and F.Harmantzis, “Dynamic Pricing with Alternatives for Mobile Networks”, WCNC 2004.
  2. J. Hou, J. Yang, and SymeonPapavassiliou,” Integration of pricing with call admission control to meet QoS requirements in cellular networks,” IEEE Transactions on Parallel and Distributed Systems, Vol.13,pp 898–910, September 2002.
  3. J.Felisa,A.Abad,L.Lachlan L. Andrew, and D. Everitt, “Estimation of blocking probabilities in cellular networks with dynamic channel assignment”,ACM Transactions on Modeling and Computer Simulation, Vol. 12, No. 1, January 2002.
  4. F. Priscoli, N.Magnani, V. Palestini, and F. Sestini, “Application of dynamic channel allocation strategies to the GSM cellular network,” IEEE Journal on Selected Areas in Communications, Vol. 15, No. 8, October 1997.
  5. D.Enrico, R. Fantacci, and G. Giambene, “Efficient dynamic channel allocation techniques with handover queuing for mobile satellite networks”, IEEE Journal On Selected Areas In Communications, Vol. 13. No. 2, February 1995.
  6. V.Pande and DipakGhosal, “Pricing-based approaches in the design of next generation wireless networks”. IEEE Communications Surveys & Tutorials, 2nd Quarter 2007
  7. M.Neely, “Optimal Pricing in a Free Market Wireless Network”, Proceedings of IEEE Infocom, May 2007.
  8. P. C. Fishburn and A. M. Odlyzko, “Dynamic Behavior of Differential Pricing and Quality of Service Options for the Internet,” Proc. First International Conf on Information and Computation Economies, 1998.
Index Terms

Computer Science
Information Sciences

Keywords

Congestion Control Dynamic Linear Pricing Dynamic Nonlinear Pricing