Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 Mar 16;21(6):2076.
doi: 10.3390/s21062076.

Optimal Access Point Power Management for Green IEEE 802.11 Networks

Rosario G Garroppo  1 , Gianfranco Nencioni  2 , Luca Tavanti  3 , Bernard Gendron  4 , Maria Grazia Scutellà  5
Affiliations

Optimal Access Point Power Management for Green IEEE 802.11 Networks

Rosario G Garroppo et al. Sensors (Basel). .

Abstract

In this paper, we present an approach and an algorithm aimed at minimising the energy consumption of enterprise Wireless Local Area Networks (WLANs) during periods of low user activity. We act on two network management aspects: powering off some Access Points (APs), and choosing the level of transmission power of each AP. An efficient technique to allocate the user terminals to the various APs is the key to achieving this goal. The approach has been formulated as an integer programming problem with nonlinear constraints, which comes from a general but accurate characterisation of the WLAN. This general problem formulation has two implications: the formulation is widely applicable, but the nonlinearity makes it NP-hard. To solve this problem to optimality, we devised an exact algorithm based on a customised version of Benders' decomposition method. The computational results proved the ability to obtain remarkable power savings. In addition, the good performance of our algorithm in terms of solving times paves the way for its future deployment in real WLANs.

Keywords: energy efficiency; green networking; mixed integer non-linear programming; network management; optimisation; resource allocation; wireless LAN.

PubMed Disclaimer

Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Sample instance topology of a wireless local area network.
Figure 2
Figure 2
Flow chart of Benders’ decomposition-based algorithm.
Figure 3
Figure 3
Sample assignment of traffic nodes to access points.
Figure 4
Figure 4
Occurrences of the power levels as a function of the test scenario for the case D = 21 m.
Figure 5
Figure 5
Occurrences of the power levels as a function of the test scenario for the case D = 42 m.
See this image and copyright information in PMC

References

    1. Wang X., Vasilakos A.V., Chen M., Liu Y., Kwon T.T. A Survey of Green Mobile Networks: Opportunities and Challenges. Mob. Netw. Appl. 2012;17:4–20. doi: 10.1007/s11036-011-0316-4. - DOI
    1. Wildemeersch M., Quek T., Slump C., Rabbachin A. Cognitive Small Cell Networks: Energy Efficiency and Trade-Offs. IEEE Trans. Commun. 2013;61:4016–4029. doi: 10.1109/TCOMM.2013.072213.120588. - DOI
    1. Pantazis N., Nikolidakis S., Vergados D. Energy-Efficient Routing Protocols in Wireless Sensor Networks: A Survey. IEEE Commun. Surv. Tutorials. 2013;15:551–591. doi: 10.1109/SURV.2012.062612.00084. - DOI
    1. Mehmood A., Khan S., Shams B., Lloret J. Energy-efficient multi-level and distance-aware clustering mechanism for WSNs. Int. J. Commun. Syst. 2015;28:972–989. doi: 10.1002/dac.2720. - DOI
    1. De La Oliva A., Banchs A., Serrano P. Throughput and energy-aware routing for 802.11 based mesh networks. Comput. Commun. 2012;35:1433–1446. doi: 10.1016/j.comcom.2012.04.004. - DOI

LinkOut - more resources