About | Contact Us | Register | Login
ProceedingsSeriesJournalsSearchEAI
Communications and Networking. 18th EAI International Conference, ChinaCom 2023, Sanya, China, November 18–19, 2023, Proceedings

Research Article

Green Task Offloading with Integration of Communication and Computation for LEO Satellite Computing Networks

Cite
BibTeX Plain Text
  • @INPROCEEDINGS{10.1007/978-3-031-67162-3_34,
        author={Jinlu Gu and Danpu Liu and Zhilong Zhang},
        title={Green Task Offloading with Integration of Communication and Computation for LEO Satellite Computing Networks},
        proceedings={Communications and Networking. 18th EAI International Conference, ChinaCom 2023, Sanya, China, November 18--19, 2023, Proceedings},
        proceedings_a={CHINACOM},
        year={2024},
        month={8},
        keywords={LEO satellites task offloading energy efficiency cycle life genetic algorithm},
        doi={10.1007/978-3-031-67162-3_34}
    }
    
  • Jinlu Gu
    Danpu Liu
    Zhilong Zhang
    Year: 2024
    Green Task Offloading with Integration of Communication and Computation for LEO Satellite Computing Networks
    CHINACOM
    Springer
    DOI: 10.1007/978-3-031-67162-3_34
Jinlu Gu, Danpu Liu,*, Zhilong Zhang
    *Contact email: dpliu@bupt.edu.cn

    Abstract

    Low Earth Orbit (LEO) satellite computing networks have opened up new possibilities for handling onboard tasks in space, while facing the challenges such as latency, energy consumption, and satellite battery lifespan degradation. In the existing studies, onboard computations are often fully offloaded to ground stations, resulting in large delays and energy inefficiencies. Moreover, the impact of satellite battery discharge depth on network lifespan has been neglected. To address these issues, this paper proposes a novel approach to offload tasks among satellites, which enables in-space processing and collaborative computation. To effectively extend the overall lifespan of the satellite network, we formulate an optimization problem which aims to maximize the weighted sum utility of energy efficiency and satellite battery lifespan degradation. Furthermore, a green task offloading strategy based on genetic algorithm is proposed to solve the problem. Simulation results demonstrate its benefits in reducing both satellites’energy consumption and discharge depth. Compared to the baseline, the proposed strategy prolongs the lifespan of the satellite network by 42.2%.

    Keywords
    LEO satellites task offloading energy efficiency cycle life genetic algorithm
    Published
    2024-08-06
    Appears in
    SpringerLink
    http://dx.doi.org/10.1007/978-3-031-67162-3_34
    Copyright © 2023–2025 ICST
    EBSCOProQuestDBLPDOAJPortico
    EAI Logo

    About EAI

    • Who We Are
    • Leadership
    • Research Areas
    • Partners
    • Media Center

    Community

    • Membership
    • Conference
    • Recognition
    • Sponsor Us

    Publish with EAI

    • Publishing
    • Journals
    • Proceedings
    • Books
    • EUDL