Advertisement

AP load balance strategy in face of high user density

  • Wei ZhangEmail author
  • Ze Yu He
  • Li Min Ma
  • Rami Salem
  • Lu Han
Original Research

Abstract

The signal intensity based wireless terminal access mechanism is the key cause of imbalanced load of WLAN. In the environment where users are densely packed, such as banks, office buildings and malls, load imbalance will severely decrease the quality and source utility rate of WLAN, thus the node load balance strategy becomes increasingly in demand to solve the problem. First, this paper studied the mainstream node load balance technologies and proposed an evaluation model which identifies and measures the level of load; next, the load level gain calculation model was designed and the prediction-based load balance and resource adjustment strategy was put forward; at last, the load balance mechanism ST-WLB was enabled and the test result shows that it can improve the performance by 10% without excessive costs.

Keywords

Wireless local area networks Load balance Evaluation model Access control Qos Anti-interference 

Notes

Acknowledgements

This work was supported by KYJJ2016005. (Research Fund from Beijing Innovation Center for Future Chip). This work was supported by CIT&TCD201504057. (Beijing youth top-notch talent cultivation project).

References

  1. Chen X (2017) The development prospect and value research of commercial wireless WiFi. Wirel Internet Technol 13:14–15Google Scholar
  2. Chen A, Asaf C, Yoram H et al (2017) SINR diagram with interference cancellation. Ad Hoc Netw 54:1–16CrossRefGoogle Scholar
  3. Dwijaksara MH, Jeon WS, Jeong DG (2016) A joint user association and load balancing scheme for wireless LANs supporting multicast transmission. Acm symposium on applied computing, pp 688–695Google Scholar
  4. Fan Q (2017) Research on user access control and resource allocation in wireless heterogeneous network. University of Science and Technology of China, He FeiGoogle Scholar
  5. Giuseppe B (2000) Performance analysis of the IEEE 802.11 distributed coordination function. IEEE J Sel Areas Commun 18(3):535–547CrossRefGoogle Scholar
  6. He Y, Zheng X (2016) Research on wireless network co-existence at 2.4 GHz. J Comput Res Dev 53(1):26–37Google Scholar
  7. Huang B, Yu J, Cheng X et al (2017) SINR based shortest link scheduling with oblivious power control in wireless networks. J Netw Comput Appl 77:64–72CrossRefGoogle Scholar
  8. Jiang H, Liu B, Chen CW (2017) Performance analysis for zigBee under wifi interference in smart home, 2017 IEEE international conference on communications, ICC 2017Google Scholar
  9. Kosek-Szott K, Gozdecki J, Loziak K et al (2017) Coexistence issues in future WiFi networks. IEEE Netw 31(4):86–95CrossRefGoogle Scholar
  10. Lee H-W, Kim SH, Ryu W (2004) Performance of an efficient method for association admission control in public wireless LAN systems, 2004 IEEE 60th vehicular technology conference, VTC2004-Fall, pp 5049–5053Google Scholar
  11. Liu S, Xing G, Zhang H et al (2010) Passive interference measurement in wireless sensor networks, 18th IEEE international conference on network protocols, pp 52–61Google Scholar
  12. Liu Y, Ye Y, Ling J (2015) Transmission interference prediction approach in WLAN channel. Comput Sci 42(10):106–112Google Scholar
  13. Mehdi B, Perlaza SM, Blasco P et al (2013) Self-organization in small cell networks: a reinforcement learning approach. IEEE Trans Wireless Commun 12(7):3202–3212CrossRefGoogle Scholar
  14. Sehyun B, Kim J, Ban D et al (2015) Streetsense: effect of bus Wi-Fi APs on pedestrian smartphone. ACM internet measurement conference, IMC 2015, pp 347–353Google Scholar
  15. Sheshadri Ramanujan K, Arslan Mustafa Y, Sundaresan K et al (2016) AmorFi: amorphous WiFi networks for high-density deployments, 12th ACM conference on emerging networking experiments and technologies, ACM CoNEXT 2016, pp 161–175Google Scholar
  16. Stanislav M, Radeke R, Lehnert R (2013) CSMA/CA: improvements of the contention window adaptation, 2013 IEEE 17th international symposium on power line communications and its applications, ISPLC 2013, pp 53–57Google Scholar
  17. Wang Z (2010) Quantitative research of communication signals penetrate attenuation under urban environment. Zhengzhou University, ZhengzhouGoogle Scholar
  18. Wang Q (2013) Research on mechanism and improved algorithm of load balancing in WLAN. Chong-qing University, ChongqingGoogle Scholar
  19. Wang S, Yu X, Xie J (2015) WISDOM: an efficient framework of predicting WLAN availability with cellular fingerprints, 3rd ACM international joint conference on pervasive and ubiquitous computing, UbiComp 2015, pp 951–962Google Scholar
  20. Wu S, Mao W, Wang X (2014) Performance study on a CSMA/CA-based MAC protocol for multi-user MIMO wireless LANs. IEEE Trans Wireless Commun 13(6):3153–3166CrossRefGoogle Scholar
  21. Yang R, Hou Z (2006) Research on load distribution of access point in wireless LAN. Comput Eng 32(1):7–9Google Scholar
  22. Ye Q, Rong B, Chen Y et al (2012) User association for load balancing in heterogeneous cellular networks. IEEE Trans Wirel Commun 12(6):2706–2716CrossRefGoogle Scholar
  23. Zhang T (2014) Application and prospect of WIFI technology. Ind Technol Forum 03:98–99Google Scholar
  24. Zhao YJ (2010) Access-type load balancing research based on AC in WLAN. Beijing University of Posts and Telecommunications, BeijingGoogle Scholar
  25. Zhou G, Huango C, Yan T (2006) MMSN: multi-frequency media access control for wireless sensor networks, INFOCOM 2006: 25th IEEE international conference on computer communicationsGoogle Scholar
  26. Zhuang Y, Syed Z, Georgy J et al (2015) Autonomous smartphone-based WiFi positioning system by using access points localization and crowd sourcing. Pervasive Mobile Comput 18:118–136CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Wei Zhang
    • 1
    Email author
  • Ze Yu He
    • 1
  • Li Min Ma
    • 1
  • Rami Salem
    • 2
  • Lu Han
    • 2
  1. 1.Computer SchoolBeijing Information Science and Technology UniversityBeijingChina
  2. 2.Chalmers University of TechnologyGothenburgSweden

Personalised recommendations