Green Wi-Fi Management: Implementation on Partially Overlapped Channels

The channel assignment in the non-overlapped channel space may result in low spatial utilization and non-uniform Wi-Fi performance, which makes it difficult to cater to the rapid increase in Wi-Fi devices as well as wireless traffic demand. In this paper, we propose a Green Wi-Fi management framewor...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on green communications and networking 2018-06, Vol.2 (2), p.346-359
Main Authors: Zhang, Yaodong, Jiang, Chunxiao, Wang, Jingjing, Han, Zhu, Yuan, Jian, Cao, Jiannong
Format: Article
Language:English
Subjects:
AP selection
Channel allocation
Channel capacity
Channels
Energy consumption
energy efficiency
Energy management
Green products
Green Wi-Fi management
Interference
Internet
Machine learning
partially overlapped channels
Power management
Search algorithms
Tabu search
Wireless communication
Wireless fidelity
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The channel assignment in the non-overlapped channel space may result in low spatial utilization and non-uniform Wi-Fi performance, which makes it difficult to cater to the rapid increase in Wi-Fi devices as well as wireless traffic demand. In this paper, we propose a Green Wi-Fi management framework for an enterprise environment in order to densely deploy the access points (APs), to appropriately turn off a portion of the APs and coordinate the APs with the partially overlapped channels (POCs). Commencing with a power monitoring experiment, we first demonstrate that energy efficiency can be achieved when clients connect the Internet with fewer APs, followed by a channel assignment experiment showing that the dense deployment of APs with POCs is capable of improving the overall channel capacity. In order to balance the energy consumption and the network capacity, the concept of AP pattern is proposed to denote the active APs and their corresponding POCs allocated including a backtracking Tabu search algorithm for yielding alternative AP patterns. Furthermore, relying on the alternative AP patterns considered, a reinforcement learning aided algorithm is presented for determining the optimal AP pattern in terms of the active interference measurement. Finally, extensive field experiments are conducted to evaluate our Green Wi-Fi framework.
ISSN:2473-2400
2473-2400
DOI:10.1109/TGCN.2017.2787604