A bandwidth allocation method to improve user QoS satisfaction without decreasing system throughput in wireless access networks

In this paper, we focus on the bandwidth allocation issue in wireless access networks, which are made up of Ethernet Passive Optical Network (EPON) and Worldwide Interoperability for Microwave Access (WiMAX) networks, i.e., Fiber-Wire (FiWi) networks. Since the bandwidth allocation scheme largely determines the performance of the entire wireless access network, in the past decades, researchers have dedicated much effort to design bandwidth allocation algorithms based on different criteria in order to satisfy various performance requirements. Various types of bandwidth allocation scheme based on Max-Min Fairness (MMF) or Proportional Fairness (PF) criteria have been developed to increase not only system throughput but also user fairness. However, in general, there is a tradeoff relationship between maximizing system throughput and increasing the fairness among users in throughput, and the users satisfaction in their Quality of Service (QoS) cannot always be maximized by adopting fair bandwidth allocation methods. To cope with this issue, we propose a bandwidth allocation method which improves the QoS satisfaction of all users while maintaining the system throughput similar to standard schemes, such as MMF and PF. In our method, users satisfaction is quantified by using utility functions which can be different among users according to their applications and services. By transferring portions of bandwidth from fully filled users to others so as not to decrease the system throughput, the proposed scheme is able to eventually converge to a compromised point. The results of performance evaluation through computer simulations have demonstrated that our proposed scheme can successfully enhance the performance of wireless access networks.

[1]  David Flanagan,et al.  The Ruby Programming Language , 2007 .

[2]  Nei Kato,et al.  A survey of routing attacks in mobile ad hoc networks , 2007, IEEE Wireless Communications.

[3]  Seung-Jae Han,et al.  Fairness and Load Balancing in Wireless LANs Using Association Control , 2004, IEEE/ACM Transactions on Networking.

[4]  S. Shenker Fundamental Design Issues for the Future Internet , 1995 .

[5]  Carl Eklund,et al.  Quality of service support in IEEE 802.16 networks , 2006, IEEE Network.

[6]  Kwang-Cheng Chen,et al.  Fair Adaptive Radio Resource Allocation of Mobile OFDMA , 2006, 2006 IEEE 17th International Symposium on Personal, Indoor and Mobile Radio Communications.

[7]  Hoon Kim,et al.  A proportional fair scheduling for multicarrier transmission systems , 2004 .

[8]  Yang Richard Yang,et al.  Proportional Fairness in Multi-Rate Wireless LANs , 2008, IEEE INFOCOM 2008 - The 27th Conference on Computer Communications.

[9]  Abd-Elhamid M. Taha,et al.  Utility optimized bandwidth allocation in WiMAX networks , 2011, 2011 7th International Wireless Communications and Mobile Computing Conference.

[10]  Fernando Casadevall,et al.  Control of the trade-off between resource efficiency and user fairness in wireless networks using utility-based adaptive resource allocation , 2011, IEEE Communications Magazine.

[11]  Nei Kato,et al.  Detecting Blackhole Attack on AODV-based Mobile Ad Hoc Networks by Dynamic Learning Method , 2007, Int. J. Netw. Secur..

[12]  Jules J. Berman,et al.  Ruby: The Programming Language , 2008 .

[13]  Raj Jain,et al.  Scheduling in IEEE 802.16e mobile WiMAX networks: key issues and a survey , 2009, IEEE Journal on Selected Areas in Communications.

[14]  Wanjiun Liao,et al.  Utility-based radio resource allocation for QoS traffic in wireless networks , 2008, IEEE Transactions on Wireless Communications.