A Distributed Discrete Jaya Algorithm for Space-Ground Integrated Data Transmission Resource Scheduling

The Data Transmission Resource Scheduling Problem (DTRSP) is pivotal for effectively utilizing remotely-sensed Big Data. However, existing literature tends to address this challenge by separately considering ground-based or space-based antenna resources. This article introduces a paradigm, known as...

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Bibliographic Details
Published in:IEEE transactions on aerospace and electronic systems 2024-09, p.1-19
Main Authors: Ren, Sida, Feng, Yanxiang, Li, Xiaoling, Xing, Keyi, Yang, Yikang
Format: Article
Language:English
Subjects:
Aerospace and electronic systems
Data communication
Genetic algorithms
Mathematical models
Metaheuristics
Receiving antennas
Relays
Remote sensing
Satellites
Search problems
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Summary:The Data Transmission Resource Scheduling Problem (DTRSP) is pivotal for effectively utilizing remotely-sensed Big Data. However, existing literature tends to address this challenge by separately considering ground-based or space-based antenna resources. This article introduces a paradigm, known as the Space-Ground Integrated DTRSP (SGI-DTRSP), wherein both ground-based and space-based antennas are collaboratively scheduled for efficient data transmission back to the ground. For the first time, a mathematical integer programming model for addressing SGI-DTRSP is proposed. To tackle this problem efficiently, we present a Distributed Discrete Jaya (DD-Jaya) algorithm. In DD-Jaya, the entire population is divided into three subpopulations, each evolving independently through different global search strategies- best-Jaya or random-Jaya. Additionally, an adaptive local search strategy is incorporated into DD-Jaya to enhance exploitation capacity. The quality of individuals is further improved by sharing superior evolutionary information among subpopulations. Finally, extensive simulation experiments demonstrate that DD-Jaya outperforms the existing algorithms, especially when dealing with large-scale SGI-DTRSP.
ISSN:0018-9251
1557-9603
DOI:10.1109/TAES.2024.3462369