Power Management of Smartphones Based on Device Usage Patterns
Smartphones provide rich applications and offer many crowdsensing services to end users. However, the power consumption of smartphones is still a primary issue in green computing. This paper presents a general power management framework including a data logger, an unsupervised learning algorithm of classifier, and a power-saving decision maker. The framework gathers and analyses the usage patterns of smartphones and separates end users into non-active and active ones, and their mobile devices into low-power ones and high-power ones using an unsupervised learning algorithm. If the smartphone of a non-active user belongs to the high-power group, we observe abnormal usage behaviour. The framework provides recommendations, e.g. as a power-saving notification to the user. We collected device usage and power consumption attributes on two kinds of Android–smartphones and evaluated the framework in experimental studies with 22 users. The results show that our framework can correctly identify non-active users’ devices consuming much more power than active users by recognizing reasons of the abnormal usage behaviour of non-active users and providing recommendations for adjusting the device towards power saving.
KeywordsPower management Unsupervised learning algorithm Smartphones Usage patterns
The EU Erasmus Mundus project FUSION––featured Europe and south Asia mobility network (2013-2541/001-011) supported this research.
- Anand B, Thirugnanam K, Sebastian J, Kannan PG, Ananda AL, Chan MC, Balan RK (2011) Adaptive display power management for mobile games. In: Proceedings of the 9th international conference on mobile systems, applications, and servicesGoogle Scholar
- Bo Z, Qiang Z, Guohong C, Addepalli S (2013) Energy-aware web browsing in 3G based smartphones. In: IEEE 33rd international conference on distributed computing systemsGoogle Scholar
- Chen H, Li Y, Shi W (2012) Fine-grained power management using process-level profiling. Sustain Comput Inf Syst 2(1):33–42Google Scholar
- Kang J-M, Seo S-S, Hong J-K (2011) Usage pattern analysis of smartphones. In: IEEE 13th Asia-Pacific network operations and management symposiumGoogle Scholar
- Kyu-Han K, Min AW, Gupta D, Mohapatra P, Singh JP (2011) Improving energy efficiency of Wi-Fi sensing on smartphones. In: INFOCOMGoogle Scholar
- Min AW, Wang R, Tsai J, Ergin MA, Tai T-YC (2012) Improving energy efficiency for mobile platforms by exploiting low-power sleep states. In: Proceedings of the 9th conference on computing frontiersGoogle Scholar
- Rahmati A, Qian A, Zhong L (2007) Understanding human-battery interaction on mobile phones. In: Proceedings of the 9th international conference on human computer interaction with mobile devices and servicesGoogle Scholar
- Rodriguez Castillo JM, Lundqvist H, Qvarfordt C (2013) Energy consumption impact from Wi-Fi traffic offload. In: Proceedings of the 10th international symposium on wireless communication systemsGoogle Scholar