A user-centric network management framework for high-density Wireless LANs

With the ever increasing deployment density of Wireless Local Area Networks (WLANs), more and more access points (APs) are deployed within users' vicinity. The effective management of these APs to optimize users' eventual throughput becomes an important challenge in the high-density deployment environment. In this paper, we propose a user-centric network management framework to optimize the throughput of users operating in the high-density WLANs taking into consideration the network conditions sensed by users and their access priorities. The proposed framework is built around an information pipeline that facilitates the sharing of the information needed for optimal management of communication resources. Theoretical analysis and extensive simulations are presented on two major management activities: AP association and channel selection, and demonstrate that the proposed user-centric network management framework significantly outperforms traditional network management framework in the high-density deployment environment.

[1]  Marco Conti,et al.  Dynamic tuning of the IEEE 802.11 protocol to achieve a theoretical throughput limit , 2000, TNET.

[2]  Donald F. Towsley,et al.  Facilitating access point selection in IEEE 802.11 wireless networks , 2005, IMC '05.

[3]  Yuji Oie,et al.  Decentralized access point selection architecture for wireless LANs , 2007, 2004 Symposium on Wireless Telecommunications.

[4]  Srinivasan Seshan,et al.  Self-management in chaotic wireless deployments , 2005, MobiCom '05.

[5]  Hui Deng,et al.  Integration of SNR, load and time in handoff initiation for wireless LAN , 2003, 14th IEEE Proceedings on Personal, Indoor and Mobile Radio Communications, 2003. PIMRC 2003..

[6]  Jing Zhu,et al.  On Optimal Physical Carrier Sensing: Theoretical Analysis and Protocol Design , 2007, IEEE INFOCOM 2007 - 26th IEEE International Conference on Computer Communications.

[7]  Paramvir Bahl,et al.  MultiNet: connecting to multiple IEEE 802.11 networks using a single wireless card , 2004, IEEE INFOCOM 2004.

[8]  Haijun Zhang,et al.  A Hybrid Genetic Algorithm for Flexible Task Collaborative Scheduling , 2008, 2008 Second International Conference on Genetic and Evolutionary Computing.

[9]  Zhi Zhou,et al.  A Multi-AP Architecture for High-Density WLANs: Protocol Design and Experimental Evaluation , 2008, 2008 5th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks.

[10]  Konstantina Papagiannaki,et al.  Self Organization of Interfering 802.11 Wireless Access Networks , 2005 .

[11]  Hari Balakrishnan,et al.  Improving loss resilience with multi-radio diversity in wireless networks , 2005, MobiCom '05.

[12]  Zhisheng Niu,et al.  A Channel Assignment Scheme in High Density WLANs to Mitigate Pesudo Capture Effect , 2007, IEEE GLOBECOM 2007 - IEEE Global Telecommunications Conference.

[13]  Vasilios A. Siris,et al.  Access Point Selection for Improving Throughput Fairness in Wireless LANs , 2007, 2007 10th IFIP/IEEE International Symposium on Integrated Network Management.

[14]  Aravind Srinivasan,et al.  A Client-Driven Approach for Channel Management in Wireless LANs , 2006, Proceedings IEEE INFOCOM 2006. 25TH IEEE International Conference on Computer Communications.

[15]  A. Girotra,et al.  Performance Analysis of the IEEE 802 . 11 Distributed Coordination Function , 2005 .

[16]  Zhisheng Niu,et al.  Dynamic polling mechanism for enhancing voice transmission in IEEE 802.11e wireless LANs , 2006, Int. J. Wirel. Mob. Comput..

[17]  Kevin R. Fall,et al.  Ns: notes and documentation , 1997 .

[18]  Pavan Nuggehalli,et al.  Online Association Policies in IEEE 802.11 WLANs , 2006, 2006 4th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks.