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Mobile and Ubiquitous Systems: Computing, Networking and Services. 20th EAI International Conference, MobiQuitous 2023, Melbourne, VIC, Australia, November 14–17, 2023, Proceedings, Part I

Research Article

LOADHoC: Towards the Automatic Local Distribution of Computation Using Existing IoT Devices

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BibTeX Plain Text
  • @INPROCEEDINGS{10.1007/978-3-031-63989-0_9,
        author={Shaine Christmas and Kevin Lee and Jean-Guy Schneider},
        title={LOADHoC: Towards the Automatic Local Distribution of Computation Using Existing IoT Devices},
        proceedings={Mobile and Ubiquitous Systems: Computing, Networking and Services. 20th EAI International Conference, MobiQuitous 2023, Melbourne, VIC, Australia, November 14--17, 2023, Proceedings, Part I},
        proceedings_a={MOBIQUITOUS},
        year={2024},
        month={7},
        keywords={Internet of Things IoT Offloading Distribution},
        doi={10.1007/978-3-031-63989-0_9}
    }
    
  • Shaine Christmas
    Kevin Lee
    Jean-Guy Schneider
    Year: 2024
    LOADHoC: Towards the Automatic Local Distribution of Computation Using Existing IoT Devices
    MOBIQUITOUS
    Springer
    DOI: 10.1007/978-3-031-63989-0_9
Shaine Christmas1,*, Kevin Lee1, Jean-Guy Schneider2
  • 1: Deakin University, Geelong
  • 2: Monash University, Clayton
*Contact email: schristmas@deakin.edu.au

Abstract

Mobile devices often use offloading nodes to reduce the amount of power used locally, or because of the low computational power of the device. Mobile devices can take advantage of offloading to reduce the power usage and increase the battery life of the device. Cloud offloading architectures are largely out of the users control and have higher latency than running the computation on the local device. Cloud computing architectures use specialised nodes, which need to be designed for the service provider. As more Internet of Things (IoT) devices are created and deployed, the number of idle devices also increases. These devices use power to stay in an idle state, which constitutes an inefficient usage of computational resources; both as network resources and physical materials used to make the device. To address an alternative to cloud offloading architectures, this work proposes an architecture for taking advantage of idle computing power of IoT devices for offloading computations from devices locally to improve privacy, latency, and sustainability. Testing of the proposed architecture demonstrates that computations can be successfully offloaded, with acceptable latency, and minimal increase to the individual power use of the connected IoT devices.

Keywords
Internet of Things IoT Offloading Distribution
Published
2024-07-19
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-031-63989-0_9
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