Towards the optimization of power and bandwidth consumption in mobile-cloud hybrid applications

Peter Lewis; Aamir Akbar

doi:10.1109/FMEC.2017.7946433

Towards the optimization of power and bandwidth consumption in mobile-cloud hybrid applications

Peter Lewis, Aamir Akbar

Research output: Chapter in Book/Published conference output › Conference publication

Abstract

Mobile devices can now support a wide range of applications, many of which demand high computational power. Backed by the virtually unbounded resources of cloud computing, today’s mobile-cloud (MC) computing can meet the demands of even the most computationally and resource intensive applications. However, many existing MC hybrid applications are inefficient in terms of achieving objectives like minimizing battery power consumption and network bandwidth usage, which form a tradeoff. To counter this problem we propose a technique that: 1) measures, at run time, how well the MC application meets these two objectives; and 2) allows arbitrary configurations to be applied to the MC application in order to optimize the efficiency tradeoff. Our experimental evaluation considers two MC hybrid applications. We modularized them first, based on computationally-intensive tasks, and then executed them using a simple MC framework while measuring the power and bandwidth consumption at run-time. Analysis of results shows that efficient configurations of the apps can be obtained in terms of minimizing the two objectives. However, there remain challenges such as scalability and automation of the process, which we discuss.

Original language	English
Title of host publication	Proceedings of the Third International Workshop on Mobile Cloud Computing systems, Management, and Security (MCSMS-2017)
Publisher	IEEE
ISBN (Electronic)	978-1-5386-2859-1
ISBN (Print)	978-1-5386-2860-7
DOIs	https://doi.org/10.1109/FMEC.2017.7946433
Publication status	E-pub ahead of print - 15 Jun 2017
Event	IEEE 3rd International Workshop on Mobile Cloud Computing systems, Management, and Security: in conjunction with the 2nd IEEE International Conference on Fog and Mobile Edge Computing (FMEC-2017) and the 4th IEEE International Conference on Software Defined Systems (SDS-2017) - Valencia, Spain Duration: 8 May 2017 → 11 May 2017

Workshop

Workshop	IEEE 3rd International Workshop on Mobile Cloud Computing systems, Management, and Security
Abbreviated title	MCSMS-2017
Country/Territory	Spain
City	Valencia
Period	8/05/17 → 11/05/17

Bibliographical note

© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

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10.1109/FMEC.2017.7946433

Optimization of power and bandwidth consumption in mobile-cloud hybrid applications
© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Accepted author manuscript, 209 KB

Cite this

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title = "Towards the optimization of power and bandwidth consumption in mobile-cloud hybrid applications",

abstract = "Mobile devices can now support a wide range of applications, many of which demand high computational power. Backed by the virtually unbounded resources of cloud computing, today{\textquoteright}s mobile-cloud (MC) computing can meet the demands of even the most computationally and resource intensive applications. However, many existing MC hybrid applications are inefficient in terms of achieving objectives like minimizing battery power consumption and network bandwidth usage, which form a tradeoff. To counter this problem we propose a technique that: 1) measures, at run time, how well the MC application meets these two objectives; and 2) allows arbitrary configurations to be applied to the MC application in order to optimize the efficiency tradeoff. Our experimental evaluation considers two MC hybrid applications. We modularized them first, based on computationally-intensive tasks, and then executed them using a simple MC framework while measuring the power and bandwidth consumption at run-time. Analysis of results shows that efficient configurations of the apps can be obtained in terms of minimizing the two objectives. However, there remain challenges such as scalability and automation of the process, which we discuss.",

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Lewis, P & Akbar, A 2017, Towards the optimization of power and bandwidth consumption in mobile-cloud hybrid applications. in Proceedings of the Third International Workshop on Mobile Cloud Computing systems, Management, and Security (MCSMS-2017). IEEE, IEEE 3rd International Workshop on Mobile Cloud Computing systems, Management, and Security, Valencia, Spain, 8/05/17. https://doi.org/10.1109/FMEC.2017.7946433

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PY - 2017/6/15

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N2 - Mobile devices can now support a wide range of applications, many of which demand high computational power. Backed by the virtually unbounded resources of cloud computing, today’s mobile-cloud (MC) computing can meet the demands of even the most computationally and resource intensive applications. However, many existing MC hybrid applications are inefficient in terms of achieving objectives like minimizing battery power consumption and network bandwidth usage, which form a tradeoff. To counter this problem we propose a technique that: 1) measures, at run time, how well the MC application meets these two objectives; and 2) allows arbitrary configurations to be applied to the MC application in order to optimize the efficiency tradeoff. Our experimental evaluation considers two MC hybrid applications. We modularized them first, based on computationally-intensive tasks, and then executed them using a simple MC framework while measuring the power and bandwidth consumption at run-time. Analysis of results shows that efficient configurations of the apps can be obtained in terms of minimizing the two objectives. However, there remain challenges such as scalability and automation of the process, which we discuss.

AB - Mobile devices can now support a wide range of applications, many of which demand high computational power. Backed by the virtually unbounded resources of cloud computing, today’s mobile-cloud (MC) computing can meet the demands of even the most computationally and resource intensive applications. However, many existing MC hybrid applications are inefficient in terms of achieving objectives like minimizing battery power consumption and network bandwidth usage, which form a tradeoff. To counter this problem we propose a technique that: 1) measures, at run time, how well the MC application meets these two objectives; and 2) allows arbitrary configurations to be applied to the MC application in order to optimize the efficiency tradeoff. Our experimental evaluation considers two MC hybrid applications. We modularized them first, based on computationally-intensive tasks, and then executed them using a simple MC framework while measuring the power and bandwidth consumption at run-time. Analysis of results shows that efficient configurations of the apps can be obtained in terms of minimizing the two objectives. However, there remain challenges such as scalability and automation of the process, which we discuss.

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Towards the optimization of power and bandwidth consumption in mobile-cloud hybrid applications

Abstract

Workshop

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