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Ready-time partitioning algorithm for computation offloading of workflow applications in mobile cloud computing

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Abstract

To augment the capabilities of mobile devices, application partitioning solutions in mobile cloud computing have emerged to decide the execution location of each application part between mobile device and cloud servers. To adapt to the network and server status changes during application execution, we propose a cloudlet-assisted ready-time partitioning technique, which partitions each task of the users’ workflow exactly when it is ready to run. It aims at minimizing the energy consumption of each mobile user’s device, while meeting user-defined deadlines. The proposed deadline distribution–ready-time partitioning algorithm has two phases: deadline distribution phase, which distributes each user deadline among its workflow tasks before application execution, and ready-time partitioning phase, which partitions each ready task by effectively considering the network and cloudlet status. Using real mobile applications, the experimental results prove its adaptability to environmental changes, its energy-efficiency, and its ability to satisfy the deadline over other methods.

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Authors and Affiliations

  1. Department of Computer Engineering, Engineering Faculty, Ferdowsi University of Mashhad, Azadi Square, Mashhad, Iran

    Mahsa Shadi, Saeid Abrishami, Amir Hossein Mohajerzadeh & Behrooz Zolfaghari

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  1. Mahsa Shadi
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  2. Saeid Abrishami
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  3. Amir Hossein Mohajerzadeh
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  4. Behrooz Zolfaghari
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Correspondence to Saeid Abrishami.

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Shadi, M., Abrishami, S., Mohajerzadeh, A.H. et al. Ready-time partitioning algorithm for computation offloading of workflow applications in mobile cloud computing. J Supercomput 77, 6408–6434 (2021). https://doi.org/10.1007/s11227-020-03528-z

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  • DOI: https://doi.org/10.1007/s11227-020-03528-z

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