Numerous services and applications have been developed to monitor anomalies or collect various sensing information in large-scale monitoring areas using drones. Nonetheless, interruptions of drone missions in such areas occasionally occur due to network errors, low battery levels, or physical defects, such as damage to the rotor and propeller. Checkpointing is a technique that periodically saves the system’s state, allowing it to be restored to that point in the event of a failure. In such circumstances, checkpointing techniques can be used to periodically save information related to the drone mission and replace a malfunctioning drone with the saved checkpoint information. In this paper, we propose a dynamic checkpoint interval decision algorithm for a live migration-based drone-recovery system. The proposed scheme minimizes the drone’s energy consumption while efficiently performing checkpointing. According to the basic experimental results, the proposed scheme consumed only about 3.51% more energy, while performing about 25.97% more checkpoint operations compared to the FIC (Fixed Interval Checkpointing) scheme. By using the proposed scheme, it is possible to increase the availability of checkpoint information and quickly resume drone missions, while minimizing the increase in energy consumption of the drone by saving checkpoints more frequently. Therefore, the proposed scheme can improve the reliability and stability of drone-based services.


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    Title :

    A Dynamic Checkpoint Interval Decision Algorithm for Live Migration-Based Drone-Recovery System


    Contributors:
    Bongjae Kim (author) / Jungkyu Han (author) / Joonhyouk Jang (author) / Jinman Jung (author) / Junyoung Heo (author) / Hong Min (author) / Dong Sop Rhee (author)


    Publication date :

    2023




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown




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