Modeling AP's substitutability in dense-deployed WLANs

For supporting peak usage, APs (Access Points) are always placed densely in today's WLAN, which leads to excessive energy consumption at the same time. Clustering APs of the same area and switching off some APs for normal network access are the main solution to saving energy. How to cluster APs and find the substitutability of APs is the key. RSSI between APs used to cluster APs in related research is not good enough for finding the substitutability of APs, since the substitutability of APs should be from not AP side but user side. This paper introduces a model of the AP's substitutability using RSSI that APs hear from users. Moreover, the relationship of coverage loss and substitutability can be quantified through the model, which can significantly reduce coverage loss while saving nearly the same amount of energy as related works. The strong point is that no matter how densely or scarcely APs are deployed, our model can work because it takes coverage into consideration inherently. Experiment results show that the model of AP substitutability is valid and stable.

[1]  Gerd Kortuem,et al.  Sensing Danger - Challenges in Supporting Health and Safety Compliance in the Field , 2007 .

[2]  Marco Ajmone Marsan,et al.  Energy-performance trade-off in dense WLANs: A queuing study , 2012, Comput. Networks.

[3]  Zhisheng Niu,et al.  Cell zooming for cost-efficient green cellular networks , 2010, IEEE Communications Magazine.

[4]  Marco Canini,et al.  Insomnia in the access , 2011, SIGCOMM 2011.

[5]  Lukas Kencl,et al.  Energy savings for cellular network with evaluation of impact on data traffic performance , 2010, 2010 European Wireless Conference (EW).

[6]  Haiyun Luo,et al.  Traffic-driven power saving in operational 3G cellular networks , 2011, MobiCom.

[7]  Konstantina Papagiannaki,et al.  Towards an Energy-Star WLAN Infrastructure , 2007, Eighth IEEE Workshop on Mobile Computing Systems and Applications.

[8]  Kevin C. Almeroth,et al.  Green WLANs: On-Demand WLAN Infrastructures , 2009, Mob. Networks Appl..

[9]  Sourjya Bhaumik,et al.  Breathe to stay cool: adjusting cell sizes to reduce energy consumption , 2010, Green Networking '10.

[10]  Marco Ajmone Marsan,et al.  A simple analytical model for the energy-efficient activation of access points in dense WLANs , 2010, e-Energy.

[11]  Jianping Wu,et al.  Study on real energy consumption of large-scale campus wireless network , 2013, 2013 International Conference on Computing, Networking and Communications (ICNC).

[12]  M. Cetron,et al.  Energy efficiency enhancements in radio access networks , 2004 .