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Modelling Energy-Aware Task Allocation in Mobile Workflows

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Mobile and Ubiquitous Systems: Computing, Networking, and Services (MobiQuitous 2013)

Abstract

Mobile devices are becoming the platform of choice for both business and personal computing needs. For a group of users to efficiently collaborate over the execution of a set workflow using their mobile devices, the question then arises as to which device should run which task of the workflow and when? In order to answer this question, we study two common energy requirements: in the minimum group energy cost problem (MGECP) we build the model as a quadratic 0–1 program and solve the optimisation problem with the objective to minimise the total energy cost of the devices as a group. In the minimum max-utilisation problem (MMUP) we aim to improve the fairness of the energy cost within the group of devices and present two adjustment algorithms to achieve this goal. We demonstrate the use of a Mixed Integer Quadratic Programming (MIQP) solver in both problem’s solutions. Simulation result shows that both problems are solved to good standards. Data generated by different workload pattern also give us a good indication of the type of workflow that benefit the most from MMUP. The model used in this work can also be adapted for other energy critical scenarios.

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Notes

  1. 1.

    E.g. we can assume that the support system is similar to that of an Excel application with embedded VBA macro modules. Data is stored in the local spreadsheet.

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Acknowledgement

This work is sponsored by the Research Project Grant of the Leverhulme Trust (Grant No. RPG-101).

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Authors and Affiliations

  1. Department of Computer Science, University of Warwick, Coventry, CV4 7AL, UK

    Bo Gao & Ligang He

Authors
  1. Bo Gao
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  2. Ligang He
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Correspondence to Bo Gao or Ligang He .

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Editors and Affiliations

  1. University of Ottawa, Ottawa, Ontario, Canada

    Ivan Stojmenovic

  2. School of Computer Science and Engineering,The University of Aizu Tsuruga, Fukushima, Japan

    Zixue Cheng

  3. School of Computer Science and Engineering, The University of Aizu Tsuruga, Fukushima, Japan

    Song Guo

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© 2014 Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Gao, B., He, L. (2014). Modelling Energy-Aware Task Allocation in Mobile Workflows. In: Stojmenovic, I., Cheng, Z., Guo, S. (eds) Mobile and Ubiquitous Systems: Computing, Networking, and Services. MobiQuitous 2013. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 131. Springer, Cham. https://doi.org/10.1007/978-3-319-11569-6_8

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  • DOI: https://doi.org/10.1007/978-3-319-11569-6_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11568-9

  • Online ISBN: 978-3-319-11569-6

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