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.
A Distributed Discrete Jaya Algorithm for Space-Ground Integrated Data Transmission Resource Scheduling
IEEE Transactions on Aerospace and Electronic Systems ; 61 , 2 ; 1454-1471
01.04.2025
4124411 byte
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Integrated resource scheduling in a distributed scheduling environment
Tema Archiv | 1988
|