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Issue No.10 - Oct. (2013 vol.24)
pp: 2069-2078
Guangtao Xue , Shanghai Jiao Tong University, Shanghai
Qi He , Shanghai Jiao Tong University, Shanghai
Hongzi Zhu , Shanghai Jiao Tong University, Shanghai
Tian He , University of Minnesota, Minneapolis
Yunhuai Liu , Chinese Academy of Sciences, Shanghai
Well-balanced workload among wireless access points (APs) in a wireless local-area network (WLAN) can improve the user experience for accessing the Internet. Most load balancing solutions in WLANs focuses on the optimization of AP operations, assuming that the arrivals and departures of users are independent. However, through the analysis of AP usage based on a real WLAN trace of one-month collected at the Shanghai Jiao Tong University (SJTU), we find that such an assumption does not hold. In fact, due to users' social activities which is particularly time for enterprise environments, they tend to arrive or leave in unison, which would disruptively affect the load balance among APs. In this paper, we propose a novel AP allocation scheme to tackle the load balancing problem in WLANs, taking into account the social relationships of users. In this scheme, users with intense social relationships are assigned to different APs so that jointly departure of those users would have minor impact on the load balance of APs. Given that the problem of allocating an AP for each user so that the average of the sums of social relation intensity between any pair of users in each AP is NP-complete, we propose an online greedy algorithm. Extensive trace-driven simulations demonstrate the efficacy of our scheme. Comparing to the state-of-the-art method, we can achieve about 64.7 percent balancing performance gain on average during peak hours in workdays.
Wireless LAN, Indexes, Load management, Algorithm design and analysis, Correlation, Educational institutions, Resource management, social relation analysis, IEEE 802.11, Enterprise Wireless LANs, load balance
Guangtao Xue, Qi He, Hongzi Zhu, Tian He, Yunhuai Liu, "Sociality-Aware Access Point Selection in Enterprise Wireless LANs", IEEE Transactions on Parallel & Distributed Systems, vol.24, no. 10, pp. 2069-2078, Oct. 2013, doi:10.1109/TPDS.2012.301
[1] G. Judd and P. Steenkiste, "Fixing 802. 11 Access Point Selection," ACM SIGCOMM Computer Comm. Rev., vol. 32, no. 3, pp. 31-31, 2002.
[2] A. Balachandran, P. Bahl, and G. Voelker, "Hot-Spot Congestion Relief in Public-Area Wireless Networks," Proc. IEEE Fourth Workshop Mobile Computing Systems and Applications, pp. 70-80, 2002.
[3] A. Nicholson, Y. Chawathe, M. Chen, B. Noble, and D. Wetherall, "Improved Access Point Selection," Proc. ACM Fourth Int'l Conf. Mobile Systems, Applications and Services, pp. 233-245, 2006.
[4] F. Xu, C. Tan, Q. Li, G. Yan, and J. Wu, "Designing a Practical Access Point Association Protocol," Proc. IEEE INFOCOM, pp. 1-9, 2010.
[5] H. Velayos, V. Aleo, and G. Karlsson, "Load Balancing in Overlapping Wireless Lan Cells," Proc. IEEE Int'l Conf. Comm., vol. 7, pp. 3833-3836, 2004.
[6] Y. Bejerano, S. Han, and L. Li, "Fairness and Load Balancing in Wireless LANs Using Association Control," Proc. ACM 10th Ann. Int'l Conf. Mobile Computing and Networking, pp. 315-329, 2004.
[7] J. Kleinberg, E. Tardos, and Y. Rabani, "Fairness in Routing and Load Balancing," Proc. 40th Ann. Symp. Foundation Computer Science (FOCS), pp. 568-578, 1999.
[8] Y. Qiao, J. Skicewicz, and P. Dinda, "An Empirical Study of the Multiscale Predictability of Network Traffic," Proc. IEEE 13th Int'l Symp. High Performance Distributed Computing, pp. 66-76, 2004.
[9] D. Rathunde, "Dynamic Load Balancing During Message Processing in a Wireless Communication Service Network," US Patent 6,574,477, June 2003.
[10] K. Mittal, E. Belding, and S. Suri, "A Game-Theoretic Analysis of Wireless Access Point Selection by Mobile Users," Computer Comm., vol. 31, no. 10, pp. 2049-2062, 2008.
[11] X. Wan, X. Wang, U. Heo, and J. Choi, "A New Ap-Selection Strategy for High Density IEEE 802. 11 Wlans," Proc. Int'l Conf. Cyber-Enabled Distributed Computing and Knowledge Discovery, pp. 52-58, 2010.
[12] I. Jabri, N. Krommenacker, T. Divoux, and A. Soudani, "IEEE 802.11 Load Balancing: An Approach for Qos Enhancement," Int'l J. Wireless Information Networks, vol. 15, no. 1, pp. 16-30, 2008.
[13] Y. Bejerano and S. Han, "Cell Breathing Techniques for Load Balancing in Wireless LANs," IEEE Trans. Mobile Computing, vol. 8, no. 6, pp. 735-749, June 2009.
[14] R. Akl and S. Park, "Optimal Access Point Selection and Traffic Allocation in IEEE 802.11 Networks," Proc. Ninth World Multiconf. Systemics, Cybernetics and Informatics (WMSCI '05): Comm. and Network Systems, Technologies and Applications, vol. 8, pp. 75-79, 2005.
[15] E. Garcia, R. Vidal, and J. Paradells, "Cooperative Load Balancing in IEEE 802.11 Networks with Cell Breathing," Proc. IEEE Symp. Computers and Comm. (ISCC '08), pp. 1133-1140, 2008.
[16] X. Chen, Y. Zhao, B. Peck, and D. Qiao, "Sap: Smart Access Point with Seamless Load Balancing Multiple Interfaces," Proc. IEEE INFOCOM, pp. 1458-1466, 2012.
[17] K. Wu, H. Li, L. Wang, Y. Yi, Y. Liu, Q. Zhang, and L.M. Ni, "HJam: Attachment Transmission in WLANs," Proc. IEEE INFOCOM, pp. 1449-1457, 2012.
[18] M. Motani and V. Srinivasan, "Peoplenet: Engineering a Wireless Virtual Social Network," Proc. ACM MobiCom, pp. 243-257, 2005.
[19] W. Hsu, D. Dutta, and A. Helmy, "Mining Behavioral Groups in Large Wireless Lans," Proc. 13th Ann. ACM Int'l Conf. Mobile Computing and Networking, pp. 338-341, 2007.
[20] W. Hsu and A. Helmy, "On Nodal Encounter Patterns in Wireless LAN Traces," Proc. Fourth Int'l Symp. Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks, pp. 1-10, 2006.
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