Structural Performance of Satellite Networks: A Complex Network Perspective

Lü, Yong; Min, Geyong; Zuo, Zhihong; Liang, Ruishi; Duan, Zhuohua

doi:10.1109/jsyst.2020.3003633

Cited by 7 publications

(4 citation statements)

References 37 publications

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“…Outdated static or semi-static scheduling frameworks cannot adapt to fluctuating task complexity and resource constraints in modern satellite networks. In the field of remote-sensing satellite mission scheduling, it is mainly confronted with huge consumption of computational resources [2,9], insufficient dynamic adjustment capability [8], adaptability [17,18] and real-time [15,16] challenges. These challenges lead to sub-optimal resource allocation as well as inefficiencies, especially in demanding as well as task-mobile situations.…”

Section: Related Workmentioning

confidence: 99%

“…Lu et al [17]'s study of satellite network structure has laid the groundwork for innovative scheduling strategies, providing a new perspective on the complexity of network performance. Implementing dynamic grouping in satellites improves routing efficiency and flexibility [23], crucial for mission scheduling flexibility.…”

Section: Dynamic Task Priority and Satellite Schedulingmentioning

confidence: 99%

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Remote-Sensing Satellite Mission Scheduling Optimisation Method under Dynamic Mission Priorities

Li,

Sun,

Fan

et al. 2024

Mathematics

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Mission scheduling is an essential function of the management control of remote-sensing satellite application systems. With the continuous development of remote-sensing satellite applications, mission scheduling faces significant challenges. Existing work has many inherent shortcomings in dealing with dynamic task scheduling for remote-sensing satellites. In high-load and complex remote sensing task scenarios, there is low scheduling efficiency and a waste of resources. The paper proposes a scheduling method for remote-sensing satellite applications based on dynamic task prioritization. This paper combines the and Bound methodologies with an onboard task queue scheduling band in an active task prioritization context. A purpose-built emotional task priority-based scheduling blueprint is implemented to mitigate the flux and unpredictability characteristics inherent in the traditional satellite scheduling paradigm, improve scheduling efficiency, and fine-tune satellite resource allocation. Therefore, the Branch and Bound method in remote-sensing satellite task scheduling will significantly save space and improve efficiency. The experimental results show that comparing the technique to the three heuristic algorithms (GA, PSO, DE), the BnB method usually performs better in terms of the maximum value of the objective function, always finds a better solution, and reduces about 80% in terms of running time.

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Section: Related Workmentioning

confidence: 99%

Section: Dynamic Task Priority and Satellite Schedulingmentioning

confidence: 99%

Remote-Sensing Satellite Mission Scheduling Optimisation Method under Dynamic Mission Priorities

Li,

Sun,

Fan

et al. 2024

Mathematics

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“…The satellite network is an integral part of global communication in the future network. Compared with terrestrial networks, satellite networks not only have global coverage, large communication capacity, and flexible networking but can also provide safe, reliable, and high‐quality data communication services for the whole world at any time 4,5 …”

Section: Introductionmentioning

confidence: 99%

“…Compared with terrestrial networks, satellite networks not only have global coverage, large communication capacity, and flexible networking but can also provide safe, reliable, and high-quality data communication services for the whole world at any time. 4,5 In order to improve the efficiency of data transmission by the satellite network, we need to design a reasonable routing scheme. 6 Most of the traditional routing schemes are based on the idea of the shortest path, but the global Internet user distribution is non-uniform distribution, and with the growth of satellite network access, the shortest path routing scheme will lead to link congestion in the satellite network, which will affect the communication quality of the satellite network and may lead to network failure in serious cases.…”

mentioning

confidence: 99%

Software defined network‐based multipath state‐aware routing with traffic prediction in satellite network

Luo,

Ning,

Chen

et al. 2023

Trans Emerging Tel Tech

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Uneven traffic demand in satellite networks can lead to link congestion and influence network communication quality. To tackle this problem, we propose a state‐aware routing algorithm based on traffic prediction to disperse network traffic. Reducing the onboard processing requirements, the routing algorithm in this paper introduces a software‐defined network to decouple the control plane and data plane of the satellite network. Also, to better sense the trend of network state, the routing algorithm devises a Spatial‐Temporal Attention Fusion Graph Neural Network (STAFGNN) to predict the future network state by capturing the spatial‐temporal correlation of satellite network traffic. In the control plane, the routing algorithm senses the network state by predicting the future satellite traffic and aggregates the real‐time states of neighboring satellites to identify the load level of the zone. The data plane forwards data based on the control information. Based on the routing algorithm in this paper, multipath routing is designed to reduce the probability of link congestion by dispersing each end‐to‐end traffic. The simulation results demonstrate that the routing algorithm in this paper reduces the number of congestion links and balances the load distribution. The proposed algorithm provides an idea to introduce deep learning to solve the load balancing problem in satellite networks.

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