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User-experience-aware system optimisation for mobile systems

User-experience-aware system optimisation for mobile systems
User-experience-aware system optimisation for mobile systems
This thesis considers the concept of Quality of Experience (QoE) in the context of mobile electronic consumer devices, such as smartphones. The modern smartphone is expected to deliver a high level of user experience across a wide variety of tasks, whilst remaining as power efficient as possible. Commonly, mobile devices undergo runtime optimisation to achieve the required level of performance, with the energy consumption being a secondary concern. In this thesis, we stress that it is vital to not focus on the raw performance of the device, but instead to concentrate on the needs and desires of the end user. This approach ensures that the end-user is satisfied at all times, and that the power consumption for a given level of user experience is minimised. Hence, we advocate user-experience-aware system optimisation.

We introduce the concept of Quality of Experience, which has traditionally been used only in the telecommunications industry, to mobile system optimisation. We develop user experience models in the form of utility functions, and use these to translate lowlevel metrics into the delivered user experience. Upon these models we build simple, yet effective, QoE-aware Central Processing Unit (CPU) and Graphics Processing Unit (GPU) governing algorithms which adjust the performance and power consumption at runtime to meet user experience requirements. When creating our algorithms, we first analyse and characterise the operation of both CPU and GPU workloads. Specifically, we investigate how the level of compute-boundedness or memory-boundedness of CPU workloads affects frequency scalability, as well as determining how the available bandwidth and core count for a GPU affects the rendering performance. We combine both gem5-based simulation driven analysis and hardware-based verification in order to validate our QoE-aware governing algorithms. Additionally, we validate the operation of our algorithms using a variety of common mobile workloads. As part of this work, we have also extended the gem5 simulator to allow use to investigate the potential for finegrained Dynamic Voltage and Frequency Scaling (DVFS) adjustment, and use this as a platform to investigate the operation of the Linux CPUFreq governors used on modern
mobile platforms.
Bischoff, Alexander S.
920d723b-ce9a-42da-944d-0f06c1657443
Bischoff, Alexander S.
920d723b-ce9a-42da-944d-0f06c1657443
Al-Hashimi, Bashir
0b29c671-a6d2-459c-af68-c4614dce3b5d

Bischoff, Alexander S. (2016) User-experience-aware system optimisation for mobile systems. University of Southampton, Electronics and Computer Science, Doctoral Thesis, 199pp.

Record type: Thesis (Doctoral)

Abstract

This thesis considers the concept of Quality of Experience (QoE) in the context of mobile electronic consumer devices, such as smartphones. The modern smartphone is expected to deliver a high level of user experience across a wide variety of tasks, whilst remaining as power efficient as possible. Commonly, mobile devices undergo runtime optimisation to achieve the required level of performance, with the energy consumption being a secondary concern. In this thesis, we stress that it is vital to not focus on the raw performance of the device, but instead to concentrate on the needs and desires of the end user. This approach ensures that the end-user is satisfied at all times, and that the power consumption for a given level of user experience is minimised. Hence, we advocate user-experience-aware system optimisation.

We introduce the concept of Quality of Experience, which has traditionally been used only in the telecommunications industry, to mobile system optimisation. We develop user experience models in the form of utility functions, and use these to translate lowlevel metrics into the delivered user experience. Upon these models we build simple, yet effective, QoE-aware Central Processing Unit (CPU) and Graphics Processing Unit (GPU) governing algorithms which adjust the performance and power consumption at runtime to meet user experience requirements. When creating our algorithms, we first analyse and characterise the operation of both CPU and GPU workloads. Specifically, we investigate how the level of compute-boundedness or memory-boundedness of CPU workloads affects frequency scalability, as well as determining how the available bandwidth and core count for a GPU affects the rendering performance. We combine both gem5-based simulation driven analysis and hardware-based verification in order to validate our QoE-aware governing algorithms. Additionally, we validate the operation of our algorithms using a variety of common mobile workloads. As part of this work, we have also extended the gem5 simulator to allow use to investigate the potential for finegrained Dynamic Voltage and Frequency Scaling (DVFS) adjustment, and use this as a platform to investigate the operation of the Linux CPUFreq governors used on modern
mobile platforms.

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More information

Published date: January 2016
Organisations: University of Southampton, Electronic & Software Systems

Identifiers

Local EPrints ID: 386570
URI: https://eprints.soton.ac.uk/id/eprint/386570
PURE UUID: 59816dfc-96c1-436a-b568-e1bdebc7fa6d

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Date deposited: 28 Jan 2016 15:24
Last modified: 17 Jul 2017 19:49

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Contributors

Author: Alexander S. Bischoff
Thesis advisor: Bashir Al-Hashimi

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