Sniffing Only Control Packets: A Lightweight Client-Side WiFi Traffic Characterization Solution

The advancement of the Internet of Things (IoT) is bringing unprecedented convenience into our daily life. However, with the relentlessly increasing number of mobile devices connected to the Internet, the wireless network environment is becoming more crowded than ever before. Particularly, WiFi, with its evolving role in IoT, is shouldering a tremendous amount of traffic from IoT and other mobile devices. As a result, exploding numbers of competing devices, encroachment by cellular technology, and dramatic increases in content richness deliver a more variable Quality of Experience (QoE) on WiFi than desired. Moreover, such variance tends to occur both across time and space making it an extremely difficult problem to debug. Existing active approaches tend to be expensive or impractical while existing passive approaches tend to be too narrow. To conduct efficient and nonobtrusive WiFi traffic characterization, in this article, we propose a novel passive client-side approach that delivers efficient and accurate characterization by taking advantage of the properties of frame aggregation (FA) and block acknowledgment (BA). The devised approach requires only capturing and analyzing certain types of control packets thus making it feasible to deploy on IoT devices that have limited computation power. We show in this article that we can accurately derive important characterization metrics, such as airtime, queuing information, and transmission rates with only a minimal amount of observed BAs. We show through extensive experiments the validity of our approach and conduct validation studies in the dense environment of a campus tailgate.