The Need for Cross-Layer Information in Access Point Selection
Algorithms
Konstantina Papagiannaki
The low price of commodity wireless LAN cards and
access points (APs) has resulted in the rich proliferation of
high density WLANs in enterprise, academic environments, and
public spaces. In such environments wireless clients have a
variety of affiliation options that ultimately determine the
quality of service they receive from the network. The state of the art
mechanism behind such a decision typically relies on received signal
strength, associating clients to that access point (AP) in their
neighborhood that features the strongest signal. More intelligent
algorithms have been further proposed in the literature. In this
work we take a step back and look into the fundamental metrics
that determine end user throughput in 802.11 wireless networks. We
identify three such metrics pertaining to wireless channel
quality, AP capacity in the presence of interference, and client
contention. We modify the low level software functionality
(firmware and microcode) of a commercial wireless adaptor to
measure the necessary quantities. We then test, in a real testbed,
the ability of each metric to capture end user throughput through
a range of diverse network conditions. Our experimental results
indicate that user affiliation decisions should be based on
metrics that do not only reflect physical layer performance, or
network occupancy, but also concretely capture MAC layer behavior.
Based on the acquired insight, we propose a new metric that is
shown to be highly accurate across all tested network scenarios.
This is joint work with Karthikeyan Sundaresan (Georgia Tech).
|