The Need for Cross-Layer Information in Access Point Selection Algorithms

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).