Portable devices such as smartphones and smartwartches have become an increasingly large part of our everyday lives.
We rely on these devices for a large number of tasks, from personal entertainment to tracking our fitness. However as these devices
have become common place, so has the need to make them more energy efficient and secure. This often comes at the price of degraded
user performance and satisfaction. In this thesis we propose to use user interactions as proactive hints, to optimize these system resources
without causing performance degradation. To that extend we outline the design, implementation and evaluation of three systems - GreenTouch, GreenMonitor and MultiLock.
Today's smartphones come equipped with multiple radios for cellular data communication such as 4G LTE, 3G, and 2G, that offer different bandwidths and power profiles. 4G LTE offers the highest bandwidth and is desired by users as it offers quick response while browsing the Internet, streaming media, or utilizing numerous network aware applications available to users. However, majority of the time this high bandwidth level is unnecessary, and the bandwidth demand can be easily met by 3G radios at a reduced power level. While 2G radios demand even lower power, they do not offer adequate bandwidth to meet the demand of interactive applications; however, the 2G radio may be utilized to provide connectivity when the phone is in the standby mode. To address different demands for bandwidth, we proposed GreenTouch, a system that dynamically adapts to the bandwidth demand and system state by switching between 4G LTE, 3G, and 2G with the goal of minimizing delays and maximizing energy efficiency. GreenTouch associates users’ behavior to network activity through capturing and correlating user interactions with the touch display. We have used top applications on the Google play store to show the potential of GreenTouch to reduce energy consumption of the radios by 10% on average, compared to running the applications in the standard Android. This translates to an overall energy savings of 7.5% for the entire smartphone.
Further health monitoring applications using smart devices are becoming increasingly popular due to an expanding number of new devices available and growing affordability of such devices. Smartwatches provide a new way to acquire data for heart rate and activity levels via accelerometers, gyroscopes, and other built-in sensors, which can enable a full range of health applications to improve users' lives. However, continuous heart rate monitoring can significantly reduce the operating time of a smartwatch, reducing the applicability for continuous monitoring.
We solve this we propose GreenMonitor to extend the operating time of a smartwatch while maintaining accuracy of heart rate monitoring by leveraging the correlation between heart rate and activity level changes indicated by the accelerometer data. Through detailed implementation and evaluation we show that GreenMonitor can save 26% energy, on average for our traces, while maintaining accurate physical activity tracking and evaluation.
While traditionally smartphones have relied on methods such as passcode or pattern based authentication, biometric authentication techniques are gaining popularity.
However current biometric methods are heavily dependent on various environmental factors. For example face authentication methods depend on lighting conditions, camera shake and picture framing, while finger print scanning relies on finger placement. All of these variables can result in these systems becoming time consuming for the user to use.
To remedy these problems we propose MultiLock, a passive, graded authentication system, which uses face authentication as a case study to propose a system that gives users access to their devices without requiring them to manually interact with the lock screen. MultiLock allows user to categorize applications into various security bins based on their sensitivity. By doing so MultiLock can grant users access to different sensitivity applications, based on varying degrees of sureness that the device is being used by its rightful owner. Thus allowing the device to be used even in adverse lighting conditions without hampering user experience. In our tests, MultiLock was able to grant access to users for 88\% of the interactions on average, while passively running in the background. While we use face authentication as an example to demonstrate and propose MultiLock, our system can be used with any confidence based biometric system
