Energy-Efficient Data Offloading for Earth Observation Satellite Networks

Lijun He*, Ziye Jia, Juncheng Wang, Feng Wang, Erick Lansard, Chau Yuen

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

Abstract

In Earth Observation Satellite Networks (EOSNs) with a large number of battery-carrying satellites, proper power allocation and task scheduling are crucial to improving the data offloading efficiency. As such, we jointly optimize power allocation and task scheduling to achieve energy-efficient data offloading in EOSNs, aiming to balance the objectives of reducing the total energy consumption and increasing the sum weights of tasks. First, we derive the optimal power allocation solution to the joint optimization problem when the task scheduling policy is given. Second, leveraging the conflict graph model, we transform the original joint optimization problem into a maximum weight independent set problem when the power allocation strategy is given. Finally, we utilize the genetic framework to combine the above special solutions as a two-layer solution for the joint optimization problem. Simulation results demonstrate that our proposed solution can properly balance the sum weights of tasks and the total energy consumption, thus achieving superior system performance over the current best alternatives.

Original languageEnglish
Title of host publicationProceedings - 2024 IEEE 99th Vehicular Technology Conference (VTC2024-Spring)
PublisherIEEE
Pages1-6
Number of pages6
ISBN (Electronic)9798350387414
ISBN (Print)9798350387421
DOIs
Publication statusPublished - Jun 2024
Event2024 IEEE 99th Vehicular Technology Conference, VTC2024-Spring - Marina Bay Sands Hotel, Singapore
Duration: 24 Jun 202427 Jun 2024
https://events.vtsociety.org/vtc2024-spring/ (Link to conference website)
https://events.vtsociety.org/vtc2024-spring/wp-content/uploads/sites/43/2024/06/Final-program-6-14-2024.pdf (Link to conference programme)
https://ieeexplore.ieee.org/xpl/conhome/10682988/proceeding (Conference Proceeding)

Publication series

NameProceedings - IEEE Vehicular Technology Conference
ISSN (Print)1090-3038
ISSN (Electronic)2577-2465

Conference

Conference2024 IEEE 99th Vehicular Technology Conference, VTC2024-Spring
Country/TerritorySingapore
Period24/06/2427/06/24
Internet address

Scopus Subject Areas

  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Applied Mathematics

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