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A Framework for Collaborative Computing on Top of Mobile Cloud Computing to Exploit Idle Resources

Author

Listed:
  • A. Ramesh Babu

    (Jawaharlal Nehru Technological University, Kukatpally)

  • Niraj Upadhayaya

    (J.B.Institute of Engineering & Technology, Moinabad)

Abstract

In the contemporary era, collaborative computing is the widely used model to exploit geographically distributed heterogeneous computing resources. Mobile Cloud Computing (MCC) offers an infrastructure that helps in offloading storage and computing resources to a public cloud. It has several advantages. However, in the context of modern Internet of Things based applications, it is essential to exploit idle resources of mobile devices as well. However, it is a challenging problem as mobile devices are resource-constrained and have mobility. Many existing MCC solutions concentrated on offloading tasks to outside mobile devices. In this paper, we investigate the possibility of using idle resources in mobile devices besides offloading tasks to the cloud. We proposed a novel algorithm known as Delay-aware Energy-Efficient Task Scheduling. The algorithm analyses locally available idle resources and schedules tasks over heterogeneous cores in mobile devices and also the cloud. In the process, it achieves strict deadlines associated with tasks and promotes energy conservation. A prototype application is built to simulate and evaluate the proposed algorithm. The experimental results revealed that the algorithm outperforms the existing baseline algorithms.

Suggested Citation

  • A. Ramesh Babu & Niraj Upadhayaya, 2023. "A Framework for Collaborative Computing on Top of Mobile Cloud Computing to Exploit Idle Resources," Annals of Data Science, Springer, vol. 10(6), pages 1635-1651, December.
    • Handle: RePEc:spr:aodasc:v:10:y:2023:i:6:d:10.1007_s40745-022-00390-z
    DOI: 10.1007/s40745-022-00390-z
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    References listed on IDEAS

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    1. Devansh Patel & Dhwanil Shah & Manan Shah, 2020. "The Intertwine of Brain and Body: A Quantitative Analysis on How Big Data Influences the System of Sports," Annals of Data Science, Springer, vol. 7(1), pages 1-16, March.
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