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Filters: Author is Lee, Joohyun  [Clear All Filters]
2017-04-20
Lee, Joohyun, Lee, Kyunghan, Jeong, Euijin, Jo, Jaemin, Shroff, Ness B..  2016.  Context-aware Application Scheduling in Mobile Systems: What Will Users Do and Not Do Next? Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing. :1235–1246.

Usage patterns of mobile devices depend on a variety of factors such as time, location, and previous actions. Hence, context-awareness can be the key to make mobile systems to become personalized and situation dependent in managing their resources. We first reveal new findings from our own Android user experiment: (i) the launching probabilities of applications follow Zipf's law, and (ii) inter-running and running times of applications conform to log-normal distributions. We also find context-dependency in application usage patterns, for which we classify contexts in a personalized manner with unsupervised learning methods. Using the knowledge acquired, we develop a novel context-aware application scheduling framework, CAS that adaptively unloads and preloads background applications in a timely manner. Our trace-driven simulations with 96 user traces demonstrate the benefits of CAS over existing algorithms. We also verify the practicality of CAS by implementing it on the Android platform.