Optimal Access Point Power Management for Green IEEE 802.11 Networks
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 transmi...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-03-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/21/6/2076 |
| _version_ | 1797541162059300864 |
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| author | Rosario G. Garroppo Gianfranco Nencioni Luca Tavanti Bernard Gendron Maria Grazia Scutellà |
| author_facet | Rosario G. Garroppo Gianfranco Nencioni Luca Tavanti Bernard Gendron Maria Grazia Scutellà |
| author_sort | Rosario G. Garroppo |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T13:12:16Z |
| format | Article |
| id | doaj.art-17f37147492147dd8f24245531c85f84 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T13:12:16Z |
| publishDate | 2021-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-17f37147492147dd8f24245531c85f842023-11-21T10:39:55ZengMDPI AGSensors1424-82202021-03-01216207610.3390/s21062076Optimal Access Point Power Management for Green IEEE 802.11 NetworksRosario G. Garroppo0Gianfranco Nencioni1Luca Tavanti2Bernard Gendron3Maria Grazia Scutellà4Department of Ingegneria dell’Informazione, Università di Pisa, 56122 Pisa, ItalyDepartment of Electrical Engineering and Computer Science, University of Stavanger, 4021 Stavanger, NorwayCUBIT, Consortium Ubiquitous Technologies, 56021 Cascina, ItalyCIRRELT and DIRO, Université de Montréal, Montréal, QC H3T 1N8, CanadaDepartment of Informatica, Università di Pisa, 56127 Pisa, ItalyIn 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.https://www.mdpi.com/1424-8220/21/6/2076wireless LANenergy efficiencyresource allocationoptimisationmixed integer non-linear programminggreen networking |
| spellingShingle | Rosario G. Garroppo Gianfranco Nencioni Luca Tavanti Bernard Gendron Maria Grazia Scutellà Optimal Access Point Power Management for Green IEEE 802.11 Networks Sensors wireless LAN energy efficiency resource allocation optimisation mixed integer non-linear programming green networking |
| title | Optimal Access Point Power Management for Green IEEE 802.11 Networks |
| title_full | Optimal Access Point Power Management for Green IEEE 802.11 Networks |
| title_fullStr | Optimal Access Point Power Management for Green IEEE 802.11 Networks |
| title_full_unstemmed | Optimal Access Point Power Management for Green IEEE 802.11 Networks |
| title_short | Optimal Access Point Power Management for Green IEEE 802.11 Networks |
| title_sort | optimal access point power management for green ieee 802 11 networks |
| topic | wireless LAN energy efficiency resource allocation optimisation mixed integer non-linear programming green networking |
| url | https://www.mdpi.com/1424-8220/21/6/2076 |
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