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Channel measurement-based access point selection in IEEE 802.11 WLANs.
- Source :
- Pervasive & Mobile Computing; Aug2016, Vol. 30, p58-70, 13p
- Publication Year :
- 2016
-
Abstract
- With the wide deployment of IEEE 802.11 Wireless Local Area Networks, it has become common for mobile nodes (MNs) to have multiple access points (APs) to associate with. With the Received Signal Strength Indicator (RSSI)-based AP selection algorithm, which is implemented in most commercial IEEE 802.11 clients, the AP with the best signal strength is selected regardless of the candidate AP’s available throughput, resulting in unbalanced distribution of clients among the APs in the network. Several studies have shown performance improvement in not just the new MN (nMN), but also the network as a whole when the selection process considers the current load status of candidate APs. However, the proposed algorithms in these studies assume that there are no hidden terminal problems that severely affect the performance of the network. Hidden terminal problems frequently occur in wireless networks with unlicensed frequencies, like IEEE 802.11 in the 2.4 GHz band. Moreover, none of the previous studies have considered frame aggregation, a major improvement in transmission efficiency introduced and widely deployed with the IEEE 802.11n standard. In this paper, we propose a new AP selection algorithm based on the estimation of available throughput calculated with a model based on the IEEE 802.11 distributed coordination function in consideration of hidden terminal problems and frame aggregation. The proposed algorithm is evaluated through extensive simulation, and the results show that the nMN with the proposed AP selection algorithm can achieve up to 55.84% and 22.31% higher throughput compared to the traditional RSSI-based approach and the selection algorithm solely based on the network load, respectively. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 15741192
- Volume :
- 30
- Database :
- Supplemental Index
- Journal :
- Pervasive & Mobile Computing
- Publication Type :
- Academic Journal
- Accession number :
- 116158337
- Full Text :
- https://doi.org/10.1016/j.pmcj.2015.10.018