MAMoC-Android: Multisite Adaptive Computation Offloading for Android applications

Dawand Jalil Sulaiman; Adam David Barker

doi:10.1109/MobileCloud.2019.00017

MAMoC-Android: Multisite Adaptive Computation Offloading for Android applications

Dawand Jalil Sulaiman, Adam David Barker

School of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Computational offloading has been widely used to improve the performance of mobile applications and conserve the energy of mobile devices. Prior studies have primarily focused on a form of offloading where only a single server is considered as the offloading site. However, mobile devices now have access to a range of nearby mobile and fixed devices and multiple cloud providers. This paper proposes a method for multisite computation offloading in dynamic mobile cloud environments, in order to save energy and improve application execution time. Our proposed dynamic offloading decision algorithm takes into consideration the offloading score and records of past offloading executions to select the best candidate(s) for offloading. Multisite offloading execution achieves a greater reduction with respect to the completion time and energy consumption of mobiles when compared to local execution or a single-site offloading execution on a public cloud instance.

Original language	English
Title of host publication	2019 7th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud)
Publisher	IEEE Computer Society
Pages	68-75
Number of pages	8
ISBN (Electronic)	9781728104638
ISBN (Print)	9781728104645
DOIs	https://doi.org/10.1109/MobileCloud.2019.00017
Publication status	Published - 13 May 2019
Event	2019 7th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering - Newark, San Fransisco, United States Duration: 4 Apr 2019 → 9 Apr 2019 Conference number: 7 http://www.mobile-cloud.net/

Conference

Conference	2019 7th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering
Abbreviated title	MobileCloud
Country/Territory	United States
City	San Fransisco
Period	4/04/19 → 9/04/19
Internet address	http://www.mobile-cloud.net/

Keywords

Mobile Clouds
Multisite offloading
Adaptive offloading
Android apps
Android offloading

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/MobileCloud.2019.00017

MAMoC-Android: Multisite Adaptive Computation Offloading for Android Applications
© 2019, IEEE. This work has been made available online in accordance with the publisher’s policies. This is the author created, accepted version manuscript following peer review and may differ slightly from the final published version. The final published version of this work is available at https://doi.org/10.1109/MobileCloud.2019.00017
Accepted author manuscript, 335 KB

ABC: Adaptive Brokerage for the Cloud: ABC: Adaptive Brokerage for the Cloud
Barker, A. D. (PI) & Thomson, J. D. (CoI)
EPSRC
1/04/18 → 30/09/22
Project: Standard

Cite this

@inproceedings{857a832c41f54ba392d48c3e90302f57,

title = "MAMoC-Android: Multisite Adaptive Computation Offloading for Android applications",

abstract = "Computational offloading has been widely used to improve the performance of mobile applications and conserve the energy of mobile devices. Prior studies have primarily focused on a form of offloading where only a single server is considered as the offloading site. However, mobile devices now have access to a range of nearby mobile and fixed devices and multiple cloud providers. This paper proposes a method for multisite computation offloading in dynamic mobile cloud environments, in order to save energy and improve application execution time. Our proposed dynamic offloading decision algorithm takes into consideration the offloading score and records of past offloading executions to select the best candidate(s) for offloading. Multisite offloading execution achieves a greater reduction with respect to the completion time and energy consumption of mobiles when compared to local execution or a single-site offloading execution on a public cloud instance.",

keywords = "Mobile Clouds, Multisite offloading, Adaptive offloading, Android apps, Android offloading",

author = "Sulaiman, {Dawand Jalil} and Barker, {Adam David}",

year = "2019",

month = may,

day = "13",

doi = "10.1109/MobileCloud.2019.00017",

language = "English",

isbn = "9781728104645",

pages = "68--75",

booktitle = "2019 7th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud)",

publisher = "IEEE Computer Society",

address = "United States",

note = "2019 7th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering, MobileCloud ; Conference date: 04-04-2019 Through 09-04-2019",

url = "http://www.mobile-cloud.net/",

}

Sulaiman, DJ & Barker, AD 2019, MAMoC-Android: Multisite Adaptive Computation Offloading for Android applications. in 2019 7th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud). IEEE Computer Society, pp. 68-75, 2019 7th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering, San Fransisco, California, United States, 4/04/19. https://doi.org/10.1109/MobileCloud.2019.00017

TY - GEN

T1 - MAMoC-Android

T2 - 2019 7th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering

AU - Sulaiman, Dawand Jalil

AU - Barker, Adam David

N1 - Conference code: 7

PY - 2019/5/13

Y1 - 2019/5/13

N2 - Computational offloading has been widely used to improve the performance of mobile applications and conserve the energy of mobile devices. Prior studies have primarily focused on a form of offloading where only a single server is considered as the offloading site. However, mobile devices now have access to a range of nearby mobile and fixed devices and multiple cloud providers. This paper proposes a method for multisite computation offloading in dynamic mobile cloud environments, in order to save energy and improve application execution time. Our proposed dynamic offloading decision algorithm takes into consideration the offloading score and records of past offloading executions to select the best candidate(s) for offloading. Multisite offloading execution achieves a greater reduction with respect to the completion time and energy consumption of mobiles when compared to local execution or a single-site offloading execution on a public cloud instance.

AB - Computational offloading has been widely used to improve the performance of mobile applications and conserve the energy of mobile devices. Prior studies have primarily focused on a form of offloading where only a single server is considered as the offloading site. However, mobile devices now have access to a range of nearby mobile and fixed devices and multiple cloud providers. This paper proposes a method for multisite computation offloading in dynamic mobile cloud environments, in order to save energy and improve application execution time. Our proposed dynamic offloading decision algorithm takes into consideration the offloading score and records of past offloading executions to select the best candidate(s) for offloading. Multisite offloading execution achieves a greater reduction with respect to the completion time and energy consumption of mobiles when compared to local execution or a single-site offloading execution on a public cloud instance.

KW - Mobile Clouds

KW - Multisite offloading

KW - Adaptive offloading

KW - Android apps

KW - Android offloading

U2 - 10.1109/MobileCloud.2019.00017

DO - 10.1109/MobileCloud.2019.00017

M3 - Conference contribution

SN - 9781728104645

SP - 68

EP - 75

BT - 2019 7th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud)

PB - IEEE Computer Society

Y2 - 4 April 2019 through 9 April 2019

ER -

MAMoC-Android: Multisite Adaptive Computation Offloading for Android applications

Abstract

Conference

Keywords

UN SDGs

Access to Document

Fingerprint

Projects

ABC: Adaptive Brokerage for the Cloud: ABC: Adaptive Brokerage for the Cloud

Cite this