Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/144760
Title: User experience-enhanced and energy-efficient task scheduling on heterogeneous multi-core mobile systems
Authors: Huang, Yanting
Liu, Weichen
Li, Mengquan
Chen, Peng
Yang, Lei
Xiao, Chunhua
Ye, Yaoyao
Keywords: Engineering::Computer science and engineering
Issue Date: 2019
Source: Huang, Y., Liu, W., Li, M., Chen, P., Yang, L., Xiao, C., & Ye, Y., (2018). User experience-enhanced and energy-efficient task scheduling on heterogeneous multi-core mobile systems. Proceedings of 2018 IEEE 24th International Conference on Parallel and Distributed Systems (ICPADS), 283-290. doi:10.1109/PADSW.2018.8645024
Project: NAP M4082282
SUG M4082087
Conference: 2018 IEEE 24th International Conference on Parallel and Distributed Systems (ICPADS)
Abstract: Heterogeneous Multi-Core Mobile Systems has been widely used to improve performance. However, it faces with the challenge of tradeoff between energy saving and user experience. ARM big. LITTLE architecture, a heterogeneous computing architecture, is a power-optimization technology. In most big. LITTLE devices, however, it still cannot achieve excellent user experience and higher energy saving. In this paper, we propose an improved task scheduling (UCES-GTS) by introducing the concept of user-centric task on big. LITTLE mobile device. In order to enhance user experience, the response time of user-centric tasks is shortened with reducing slack time of them properly. We then present a detailed algorithm to compute appropriate frequency and allocate the CPU resources to each task. The experimental evaluation results show that our improved global task scheduling model can achieve 17 % and 8 % energy saving average compared with the clustered switching scheduling and the original global task scheduling respectively. And the response time of user-centric tasks can decrease 27 % average, which means excellent user experience.
URI: https://hdl.handle.net/10356/144760
ISBN: 978-1-5386-7308-9
DOI: 10.1109/PADSW.2018.8645024
Schools: School of Computer Science and Engineering 
Rights: © 2018 IEEE. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:SCSE Conference Papers

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