Intelligent strategies of access point selection for vehicle to infrastructure opportunistic communications

Abstract

The low price of commodity wireless LAN cards and access points (APs) has resulted in the rich proliferation of high density WLANs in enterprises, academic environments, and public spaces. In such environments, wireless clients have a variety of affiliation options. The state of the art mechanism behind such a decision typically relies on received signal strength indicator (RSSI). This approach however, might yield unbalanced traffic load among APs. In this paper, we design intelligent AP selection algorithms for Vehicle to wireless Infrastructure opportunistic (unplanned) communications (V2I). Our objective is to increase the distance for which the vehicle is in the coverage area of the selected AP. This distance is quantified based on realistic criteria like the distance between the vehicle and the AP and the direction of the vehicle. We design two intelligent approaches: SAPS (Scan-based AP Selection), and HAPS (History-based AP Selection). Through a simulation study, we demonstrated that SAPS and HAPS, compared to RSSI-based solution, achieve lower overhead and higher amount of data in a region with an average density of APs. Our findings show also that much data would be transferred at lower speeds. Moreover, either SAPS or HAPS permits to the vehicle to efficiently profit from the time it is associated to an AP more than a classic solution based on the RSSI do.