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Reseach Article

Dynamic weight based Fair Resource Allocation in IEEE 802.16 Broadband Wireless Access Networks

by S. Geetha, R. Jayaparvathy, S. Anand
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 45 - Number 1
Year of Publication: 2012
Authors: S. Geetha, R. Jayaparvathy, S. Anand
10.5120/6742-8660

S. Geetha, R. Jayaparvathy, S. Anand . Dynamic weight based Fair Resource Allocation in IEEE 802.16 Broadband Wireless Access Networks. International Journal of Computer Applications. 45, 1 ( May 2012), 8-13. DOI=10.5120/6742-8660

@article{ 10.5120/6742-8660,
author = { S. Geetha, R. Jayaparvathy, S. Anand },
title = { Dynamic weight based Fair Resource Allocation in IEEE 802.16 Broadband Wireless Access Networks },
journal = { International Journal of Computer Applications },
issue_date = { May 2012 },
volume = { 45 },
number = { 1 },
month = { May },
year = { 2012 },
issn = { 0975-8887 },
pages = { 8-13 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume45/number1/6742-8660/ },
doi = { 10.5120/6742-8660 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:36:29.239779+05:30
%A S. Geetha
%A R. Jayaparvathy
%A S. Anand
%T Dynamic weight based Fair Resource Allocation in IEEE 802.16 Broadband Wireless Access Networks
%J International Journal of Computer Applications
%@ 0975-8887
%V 45
%N 1
%P 8-13
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The IEEE 802. 16 Broadband Wireless Access(BWA) system offers a cost-effective solution to the last-mile wireless connection problem. Optimal scheduling mechanisms and resource allocation strategies are required to provide the necessary QoS guarantees to the multimedia traffic in BWA systems while utilizing the resources as efficiently as possible. In this paper, we propose a utility based fractional knapsack framework for bandwidth allocation in IEEE 802. 16e broadband wireless networks with multiple classes of traffic flows. The proposed mechanism also includes dynamic weight adjustment to provide fairness among different competing traffic classes by prioritizing traffic depending on the load conditions and QoS requirements. We study the system performance in terms of normalized throughput and mean delay for each traffic class. From the results we find that the proposed mechanism improves throughput and decreases mean delay for varying traffic load compared to well-known allocation strategies.

References
  1. IEEE Std. 802. 16. 2004,"IEEE standards for Local and metropolitan area networks – Part 16 Air Interface for Fixed Broadband wireless access systems," October 2004
  2. IEEE 802. 16e Task Group, "Physical and medium access control Layers for combined fixed and mobile operation in licensed band," IEEE Standard 802. 16e-2005, Feb. 2006.
  3. P. Brucker, Scheduling Algorithms, Springer, Berlin, 1998.
  4. Abdel Karim Al Tamimi, Chakchai So-In, and Raj Jain, Fellow "Modeling and Resource Allocation for Mobile Video over WiMAX Broadband Wireless Networks" IEEE Journal On Selected Areas In Communications, vol. 28, no. 3, pp 354 – 365, April 2010.
  5. Sarabjot Singh, Sanjay K. Bose, and Maode Ma "Analytical and Simulation Studies for Call Admission and Resource Allocation Schemes proposed for WiMAX system" IEEE International Conference on Communication Systems, ICCS 2010, pp 522-526, Nov 2010.
  6. Dr. P. Satish Kumar "Resource Allocation -WiMAX Systems", Modern Applied Science, vol. 4, no. 12, pp 140- 150, December 2010.
  7. Ravi Kokku, Rajesh Mahindra, and SampathRangarajan "Accountable Resource Allocation in Broadband Wireless Networks", MobiArch'10,USA, September 2010.
  8. LiminPeng and Zhanmao Cao "Fairness resource allocation and scheduling for IEEE 802. 16 Mesh networks" Journal Of Networks, vol. 5, no. 6, pp 724 – 731, June 2010.
  9. Anderson Rissato, Augusto Neto, Eduardo and Paulo Mendes "WiRA: An Approach for Resource Control in WiMAX Systems" Next Generation Internet Networks, pp 239 – 249, April 2008.
  10. Network Simulator, http://www. isi. edu/nsnam/sn
  11. S. Shenker,"Fundamental design issues for future internet," IEEE Jl. on Sel. Areas in Commun. , vol. 13, no. 7, pp. 1176 – 1188, Sep - 1995.
  12. Z. Jiang, Y. Li, "Max-utility wireless resource management for best effort traffic," IEEE Trans. on wireless commun. , vol 4, no. 1, pp. 106-111, Jan - 2005
  13. D. Bertsekas, R. Gallager, Data Networks, Prentice-Hall, 1992.
  14. J. F. Shortle , P. H. Brill, M. J. Fisher, D. Gross, M. B. Masi, "An Algorithm to compute the waiting time distribution for the M/G/1 Queue," INFORMS Jl. on Computing, vol. 16, no. 2, pp: 152 – 161, Spring 2004
  15. Y. Jiang, C. K. Tham and C. C. Ko,"Delay analysis of a probabilistic priority discipline," European Trans. on Telecommun. ,vol. 13, no 6, pp: 563-577, Sep 2008.
  16. J. Abate and W. Whitt, " Asymptotics for M/G/1 low-priority waiting-time tail probabilities," Baltzer Jl. , Queuing Systems, vol. 25, pp. 173-223, 1997
  17. K. Deb, Optimization for Engineering and Design: Algorithm and Examples, Prentice-Hall, 1995.
  18. S. Pindyck, D. L. Rubin, Microeconomics, Prentice Hall, 2004.
  19. M. Martello and P. Toth, Knapsack Problems – Algorithms and Computer Implementations, John Wiley and Sons, 1990.
Index Terms

Computer Science
Information Sciences

Keywords

Ieee 802. 16 Utility Dynamic Weight Assignment Quality Of Service Resource Allocation