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An Intelligent Framework for Energy-Aware Mobile Computing Subject to Stochastic System Dynamics


Abstract User satisfaction is pivotal to the success of mobile applications. At the same time, it is imperative to maximize the energy efficiency of the mobile device to ensure optimal usage of the limited energy source available to mobile devices while maintaining the necessary levels of user satisfaction. However, this is complicated due to user interactions, numerous shared resources, and network conditions that produce substantial uncertainty to the mobile device's performance and power characteristics. In this dissertation, a new approach is presented to characterize and control mobile devices that accurately models these uncertainties. The proposed modeling framework is a completely data-driven approach to predicting power and performance.... (more)
Created Date 2017
Contributor Gaudette, Benjamin David (Author) / Vrudhula, Sarma (Advisor) / Wu, Carole-Jean (Advisor) / Fainekos, Georgios (Committee member) / Shrivastava, Aviral (Committee member) / Arizona State University (Publisher)
Subject Computer engineering / DVFS Controller / Energy Efficiency / Mobile Computing / Performance Modeling / Power Modeling / Stochastic Workloads
Type Doctoral Dissertation
Extent 184 pages
Language English
Copyright
Reuse Permissions All Rights Reserved
Note Doctoral Dissertation Computer Engineering 2017
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS


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Description Dissertation/Thesis