Research on Joint Scheduling Method of Heterogeneous TT&amp;C Network Resources Based on Improved DQN Algorithm

Xue, Naiyang; Ding, Derui; Fan, Yile; Wang, Zhiqiang

doi:10.1109/iciba52610.2021.9688327

Cited by 2 publications

(3 citation statements)

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“…The existing methods for common TT&C task planning mainly include deterministic algorithms [7][8][9], heuristic algorithms [10][11][12], and intelligent algorithms [13][14][15][16][17]. Among them, the deterministic algorithm is mainly suitable for solving TT&C task scheduling problems on a small scale, but it is difficult to apply this algorithm to solve problems on a large scale.…”

Section: Introductionmentioning

confidence: 99%

“…The algorithm reduces the probability of falling into local optimum through an iterative neighborhood search and instability strategy to realize the reasonable allocation of multi-dimensional TT&C resources. Reference [17] established a mathematical model of TT&C task planning with a minimized overall task satisfaction rate as the optimization goal. It proposed an improved DQN (Deep Q-Network)-based TT&C resource optimization configuration method to effectively solve the joint planning problem of heterogeneous TT&C network resources.…”

Section: Introductionmentioning

confidence: 99%

“…Although, References [13][14][15][16][17] used intelligent algorithms to improve the completion rate of TT&C tasks effectively, which do not control the time fragments of TT&C equipment during the task-planning process, resulting in untimely responses to emergency tasks. Therefore, this paper designs a low time fragmentation-oriented TT&C task-planning method (LTFTT&C) based on DDQN (Double Deep Q-network) to minimize time fragmentation and maximize task revenue.…”

Section: Introductionmentioning

confidence: 99%

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Toward Low Time Fragmentation of Equipment: A Double-DQN Based TT&C Task Planning Approach

Liu

2023

Applied Sciences

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With the increase of the number of satellites in space, satellite tracking, telemetry, and command (TT&C) is becoming more and more important for aerospace. This paper proposes a method for a low time fragmentation oriented. TT&C task planning method based on Double Deep Q-Network (DDQN). This method mainly solves the problem of poor responses to emergency tasks caused by the large amount of time fragments of equipment under traditional TT&C task-planning methods. Firstly, a multi-objective optimization model aiming at minimizing time fragments and maximizing task revenue is formulated. Then, according to the conflict characteristics of tasks, a task-planning conflict graph is proposed, based on which a TT&C task-planning problem is transferred into an independent set problem. Finally, DDQN is combined with graph structure embedding to solve the transferred independent set problem. The experimental results demonstrate that the proposed method reduces the time fragment of TT&C equipment by 32% and shortens the response time of emergency tasks by 36% compared to existing methods.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Toward Low Time Fragmentation of Equipment: A Double-DQN Based TT&C Task Planning Approach

Liu

2023

Applied Sciences

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Reviews and prospects in satellite range scheduling problem

Li,

Yu,

Ding

2023

Auton. Intell. Syst.

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With the increasing number of space satellites, the demand for satellite communication (including maneuvering, command uploading and data downloading) has also grown significantly. However, the actual communication resources of ground station are relatively limited, which leads to an oversubscribed problem. How to make use of limited ground station resources to complete satellite communication requests more fully and efficiently in the strict visible time is the focus of satellite range scheduling research. This paper reviews and looks forward to the research on Satellite Range Scheduling Problem (SRSP). Firstly, SRSP is defined as the scheduling problem of establishing communication between satellites and ground stations, and the classification and development of SRSP are introduced. Then, this paper analyzes three common problem description models, and establishes a mathematical model based on the analysis of optimization objectives and constraints. Thirdly, this paper classifies and summarizes the common solving methods of SRSP, and analyzes their characteristics and application scenarios. Finally, combined with the work in this paper, the future research direction of SRSP is envisioned.

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Research on Joint Scheduling Method of Heterogeneous TT&C Network Resources Based on Improved DQN Algorithm

Cited by 2 publications

References 5 publications

Toward Low Time Fragmentation of Equipment: A Double-DQN Based TT&C Task Planning Approach

Toward Low Time Fragmentation of Equipment: A Double-DQN Based TT&C Task Planning Approach

Reviews and prospects in satellite range scheduling problem

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