| Summary: | Recently, WiFi networks have witnessed an unprecedented deployment, and WiFi APs are ubiquitous around the world. On one hand, the WiFi clients have to actively discover new WiFi access points (APs), and try to access to them, even though most of the APs are privately owned, which wastes the precious energy of mobile devices due to excessive listening and scanning operations of WiFi network interface cards. On the other hand, many wireless technologies coexist in overlapping channels (e.g., 2.4 GHz ISM bands). It provides a new opportunity of cross-technology communication (CTC) that utilizes these overlapping frequencies to share information among different technologies. This paper deeply investigates the application of wireless CTC into smart and energy-effective WiFi access with the assistance of low-power radio. Specifically, we design a smart WiFi access system assisted by Zigbee, SmartWAZ, for mobile terminals with both WiFi and Zigbee interfaces. The most prominent feature of this system is that the different WiFi beacon periods are intentionally used to distinguish publicly accessible and privately owned WiFi APs. Then, the folding algorithm is applied by the Zigbee module in clients to detect the specific WiFi beacon period used by public APs, and then the WiFi interface will be waked only when a public WiFi AP is detected. From the system design viewpoint, we investigate the influence of the beacon period of the sender (i.e., WiFi AP) and the judgment threshold of the mobile client on a false positive and false negative, and provide the basic rule to appropriately set those system parameters. Compared to the traditional WiFi access methods, the SmartWAZ significantly saves the energy consumption of continuous WiFi scanning; compared to other low-power radio assisted WiFi access systems, SmartWAZ avoids waking WiFi interface when private WiFi APs appear. The experiment results show that the SmartWAZ averagely consumes only 36% of the energy of traditional WiFi access schemes and achieves reliable detection with an error rate of less than 1%.
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