Optimizing User Satisfaction of Mobile Workloads Subject to Various Sources of Uncertainties

Benjamin Gaudette, Carole-Jean Wu, Sarma Vrudhula

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

The success of mobile devices and applications is directly linked to a user's satisfaction of the quality of service — a metric used to denote the user's perception of the quality of an application. The first and necessary building block to manage user satisfaction is to establish accurate performance and power models which are sensitive to the mobile device's controllable features such as scalable voltage and frequency. Traditionally, performance and power models have been developed with deterministic workloads in mind assuming long term, stable operating conditions. However, this is insufficient for mobile workloads, which are subject to many sources of variability leading to unpredictable phases of computation. This work establishes the importance and value of modeling the many sources of variations in mobile workloads. A completely data-driven approach is presented that provides accurate estimates of a workload's statistical characteristics, without any assumptions regarding its underlying statistical distribution. The method is light-weight allowing for real-time model evaluation and update. To demonstrate the usefulness of the proposed approach, the design of a dynamic voltage and frequency scaling controller is presented and implemented on an existing mobile device. The proposed controller achieves an energy efficiency improvement of 19% over existing Android frequency governors

Original languageEnglish (US)
JournalIEEE Transactions on Mobile Computing
DOIs
StateAccepted/In press - Jan 1 2018

Fingerprint

Mobile devices
Controllers
Governors
Energy efficiency
Quality of service
Electric potential
Uncertainty
Voltage scaling
Dynamic frequency scaling

Keywords

  • Computational modeling
  • energy management
  • Frequency control
  • Mobile computing
  • Mobile computing
  • Mobile handsets
  • Performance evaluation
  • Power demand
  • Quality of service
  • stochastic processes
  • user centered design

ASJC Scopus subject areas

  • Software
  • Computer Networks and Communications
  • Electrical and Electronic Engineering

Cite this

@article{e0f7d24715134d84be0be4b07a9d83ce,
title = "Optimizing User Satisfaction of Mobile Workloads Subject to Various Sources of Uncertainties",
abstract = "The success of mobile devices and applications is directly linked to a user's satisfaction of the quality of service — a metric used to denote the user's perception of the quality of an application. The first and necessary building block to manage user satisfaction is to establish accurate performance and power models which are sensitive to the mobile device's controllable features such as scalable voltage and frequency. Traditionally, performance and power models have been developed with deterministic workloads in mind assuming long term, stable operating conditions. However, this is insufficient for mobile workloads, which are subject to many sources of variability leading to unpredictable phases of computation. This work establishes the importance and value of modeling the many sources of variations in mobile workloads. A completely data-driven approach is presented that provides accurate estimates of a workload's statistical characteristics, without any assumptions regarding its underlying statistical distribution. The method is light-weight allowing for real-time model evaluation and update. To demonstrate the usefulness of the proposed approach, the design of a dynamic voltage and frequency scaling controller is presented and implemented on an existing mobile device. The proposed controller achieves an energy efficiency improvement of 19{\%} over existing Android frequency governors",
keywords = "Computational modeling, energy management, Frequency control, Mobile computing, Mobile computing, Mobile handsets, Performance evaluation, Power demand, Quality of service, stochastic processes, user centered design",
author = "Benjamin Gaudette and Carole-Jean Wu and Sarma Vrudhula",
year = "2018",
month = "1",
day = "1",
doi = "10.1109/TMC.2018.2883619",
language = "English (US)",
journal = "IEEE Transactions on Mobile Computing",
issn = "1536-1233",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

TY - JOUR

T1 - Optimizing User Satisfaction of Mobile Workloads Subject to Various Sources of Uncertainties

AU - Gaudette, Benjamin

AU - Wu, Carole-Jean

AU - Vrudhula, Sarma

PY - 2018/1/1

Y1 - 2018/1/1

N2 - The success of mobile devices and applications is directly linked to a user's satisfaction of the quality of service — a metric used to denote the user's perception of the quality of an application. The first and necessary building block to manage user satisfaction is to establish accurate performance and power models which are sensitive to the mobile device's controllable features such as scalable voltage and frequency. Traditionally, performance and power models have been developed with deterministic workloads in mind assuming long term, stable operating conditions. However, this is insufficient for mobile workloads, which are subject to many sources of variability leading to unpredictable phases of computation. This work establishes the importance and value of modeling the many sources of variations in mobile workloads. A completely data-driven approach is presented that provides accurate estimates of a workload's statistical characteristics, without any assumptions regarding its underlying statistical distribution. The method is light-weight allowing for real-time model evaluation and update. To demonstrate the usefulness of the proposed approach, the design of a dynamic voltage and frequency scaling controller is presented and implemented on an existing mobile device. The proposed controller achieves an energy efficiency improvement of 19% over existing Android frequency governors

AB - The success of mobile devices and applications is directly linked to a user's satisfaction of the quality of service — a metric used to denote the user's perception of the quality of an application. The first and necessary building block to manage user satisfaction is to establish accurate performance and power models which are sensitive to the mobile device's controllable features such as scalable voltage and frequency. Traditionally, performance and power models have been developed with deterministic workloads in mind assuming long term, stable operating conditions. However, this is insufficient for mobile workloads, which are subject to many sources of variability leading to unpredictable phases of computation. This work establishes the importance and value of modeling the many sources of variations in mobile workloads. A completely data-driven approach is presented that provides accurate estimates of a workload's statistical characteristics, without any assumptions regarding its underlying statistical distribution. The method is light-weight allowing for real-time model evaluation and update. To demonstrate the usefulness of the proposed approach, the design of a dynamic voltage and frequency scaling controller is presented and implemented on an existing mobile device. The proposed controller achieves an energy efficiency improvement of 19% over existing Android frequency governors

KW - Computational modeling

KW - energy management

KW - Frequency control

KW - Mobile computing

KW - Mobile computing

KW - Mobile handsets

KW - Performance evaluation

KW - Power demand

KW - Quality of service

KW - stochastic processes

KW - user centered design

UR - http://www.scopus.com/inward/record.url?scp=85057799610&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85057799610&partnerID=8YFLogxK

U2 - 10.1109/TMC.2018.2883619

DO - 10.1109/TMC.2018.2883619

M3 - Article

JO - IEEE Transactions on Mobile Computing

JF - IEEE Transactions on Mobile Computing

SN - 1536-1233

ER -