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A Framework for Speculative Job Scheduling on Mobile Cloud Resources

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Big Data Analytics for Cyber-Physical Systems

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Abstract

Advances in mobile technologies have made mobile devices more powerful and have also increased their penetration in the market. This trend has stimulated the prospect of making these devices participate in collaborative computing. Mobile devices are personal devices and any collaborative computing framework, which utilizes such devices, needs to ensure that the owners’ experience with their devices is not hindered. In this paper, we study the problem of opportunistic task scheduling and workload management in a mobile cloud setting considering computation power variation. We gathered mobile usage data for a number of persons and applied supervised clustering to show that a pattern of usage exists and that it can be modelled as a state transition system. We use this model in two different kinds of scenarios. First, we present a strategy to choose and offload a task on a mobile device based on its predicted free computation capacity. We also use this model to opportunistically schedule low-priority background tasks, like a scheduled virus scanning activity or a system update, such that user experience with the device improves. We present a framework and some experimental results showing the efficacy of our proposed approach in both these problem situations.

This work was done during Pubali’s association with TRDDC, Pune, India

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Author information

Authors and Affiliations

  1. ACMU, Indian Statistical Institute, Kolkata, India

    Ansuman Banerjee

  2. TCS Research and Innovation, Kolkata, India

    Himadri Sekhar Paul, Arijit Mukherjee & Swarnava Dey

  3. Department of Computer Science, University of Illinois Urbana Champaign, Champaign, IL, USA

    Pubali Datta

Authors
  1. Ansuman Banerjee
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  2. Himadri Sekhar Paul
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  3. Arijit Mukherjee
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  4. Swarnava Dey
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  5. Pubali Datta
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Correspondence to Himadri Sekhar Paul .

Editor information

Editors and Affiliations

  1. School of Electronics and Computer Science, University of Southampton, Southampton, UK

    Shiyan Hu

  2. Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong

    Bei Yu

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Banerjee, A., Paul, H.S., Mukherjee, A., Dey, S., Datta, P. (2020). A Framework for Speculative Job Scheduling on Mobile Cloud Resources. In: Hu, S., Yu, B. (eds) Big Data Analytics for Cyber-Physical Systems. Springer, Cham. https://doi.org/10.1007/978-3-030-43494-6_4

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  • DOI: https://doi.org/10.1007/978-3-030-43494-6_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-43493-9

  • Online ISBN: 978-3-030-43494-6

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