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A scheduler for mobile cloud based on weighted metrics and dynamic context evaluation

Published: 13 April 2015 Publication History

Abstract

Resource scarcity is a major obstacle for many mobile applications, since devices have limited energy power and processing potential. As an example, there are applications that seamlessly augment human cognition and typically require resources that far outstrip mobile hardware's capabilities, such as language translation, speech recognition, and face recognition. The use of cloud computing may tackle this problem. This study presents SmartRank, a scheduling framework to perform load partitioning and offloading for mobile applications using cloud computing to increase performance in terms of response time. We first explore a benchmarking of face recognition application using mobile cloud and confirms its suitability to be used as case study with SmartRank. We have applied the approach to a face recognition process based on two strategies: cloudlet federation and resource ranking through balanced metrics (level of CPU utilization and round-trip time). Second, using a full factorial experimental design we tuned the SmartRank with the most suitable partitioning decision calibrating scheduling parameters. Nevertheless, SmartRank uses an equation that is extensible to include new parameters and make it applicable to other scenarios.

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  • (2019)TAME: An Efficient Task Allocation Algorithm for Integrated Mobile GamingIEEE Systems Journal10.1109/JSYST.2018.282949613:2(1546-1557)Online publication date: Jun-2019

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cover image ACM Conferences
SAC '15: Proceedings of the 30th Annual ACM Symposium on Applied Computing
April 2015
2418 pages
ISBN:9781450331968
DOI:10.1145/2695664
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 13 April 2015

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Author Tags

  1. mobile cloud computing
  2. offloading
  3. partitioning
  4. performance evaluation

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SAC 2015
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SAC 2015: Symposium on Applied Computing
April 13 - 17, 2015
Salamanca, Spain

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SAC '15 Paper Acceptance Rate 291 of 1,211 submissions, 24%;
Overall Acceptance Rate 1,650 of 6,669 submissions, 25%

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  • (2019)TAME: An Efficient Task Allocation Algorithm for Integrated Mobile GamingIEEE Systems Journal10.1109/JSYST.2018.282949613:2(1546-1557)Online publication date: Jun-2019

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