A novel routing design in the IP-based GEO/LEO hybrid satellite networks

Wu, Zhaofeng; Hu, Guyu; Jin, Fenglin; Song, Yu; Fu, Yinjin; Ni, Guiqiang

doi:10.1002/sat.1174

Cited by 24 publications

(5 citation statements)

References 28 publications

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“…Three main methods of performing load balancing based on routing already exist according to existing technology: source-based, centralized, and distributed load balancing systems [22]. The distributed load balancing approach operates on the idea that each satellite independently chooses the best way to transmit data, allowing them to react quickly to fluctuations in traffic.…”

Section: Traffic Load Predictionmentioning

confidence: 99%

Machine Learning with Adaptive Time Stepping for Dynamic Traffic Load Prediction in 6G Satellite Networks

Zhang,

et al. 2023

Electronics

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The rapid development of sixth-generation (6G) mobile broadband networks and Internet of Things (IoT) applications has led to significant increases in data transmission and processing, resulting in severe traffic congestion. To better allocate network resources, predicting network traffic has become crucial. However, satellite networks face global imbalances in IoT traffic demand, with substantial variations in satellite density and load distribution within the same constellation. These disparities render traditional traffic prediction algorithms inadequate for dynamically changing satellite network topologies. This paper thoroughly examines the impact of adaptive time stepping on the prediction of dynamic traffic load. Particularly, we propose a high-speed traffic prediction method that employs machine learning and recurrent neural networks over the 6G Space Air Ground Integration Network (SAGIN) structure. In our proposed method, we first investigate a variable step size-normalized least mean square (VSS-NLMS) adaptive prediction method for transforming time series prediction datasets. Then, we propose an adaptive time stepping-Gated Recurrent Unit (ATS-GRU) algorithm for real-time network traffic prediction. Finally, we compare the prediction accuracy of the ATS-GRU algorithm with that of the fixed time stepping-Gated Recurrent Unit (FTS-GRU) algorithm and compared the prediction results of three different step sizes (FSS, VSS, and ATS) based on normalized least mean square (NLMS). Numerical results demonstrate that our proposed scheme can automatically choose a suitable time stepping to track and predict the traffic load curve with acceptable accuracy and reasonable computational complexity, as its time stepping dynamically adjusts with the traffic.

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Section: Traffic Load Predictionmentioning

confidence: 99%

Machine Learning with Adaptive Time Stepping for Dynamic Traffic Load Prediction in 6G Satellite Networks

Zhang,

et al. 2023

Electronics

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“…To ensure services' continuity and real-time, the flexibility of the forwarding strategy is crucial. Firstly, frequent changes of node's address will cause link instability, and outdated information in the routing table will lead to routing path nonconvergence [104]. Secondly, the design of the forwarding strategy will affect the efficiency of the routing algorithm.…”

Section: Impact On Mobility Managementmentioning

confidence: 99%

Threat analysis for space information network based on network security attributes: a review

Fan

et al. 2022

Complex Intell. Syst.

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Space Information Network (SIN) is a multi-purpose heterogeneous network. Due to the large-scale of SIN, its secure and stable operation is vulnerable to various threats. Much of current threat analysis for SIN is based on the network function or architecture. However, this approach cannot clearly divide the relation between threats and secure communication measures for a highly integrated network. Furthermore, it will lead to overlapping in segregation of secure duties. This paper presents a comprehensive review of threats and corresponding solutions in SIN from the perspective of network security attributes. In order to make the analysis applicable to more scenarios, the following three most essential attributes, confidentiality, integrity and availability, are selected as the threatened objectives. At the same time, for cross-reference with the analysis based on network function or architecture, this paper relates network layers to network security attributes through secure communication mechanisms. Specifically, the confidentiality includes confidential information-exchange and Authentication and Key Agreement (AKA), the integrity includes information identification and information restoration, and the availability includes link establishment, routing mechanism, and mobility management. According to above framework, this paper provides a cross-layer perspective for analyzing threat and enhancing the security and stability of SIN. Finally, this paper concludes with a summary of challenges and future work in SIN.

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“…Moreover, the idealized traffic distribution and topology assumptions limit the algorithm scalability. Besides, there are routing algorithms 17,18 designed for the above hybrid satellite network. Regardless of throughput performance, few consider to decouple link variability from routing decisions for better responsiveness to traffic load.…”

Section: Related Workmentioning

confidence: 99%

Towards a throughput-optimal routing algorithm for data collection on satellite networks

Chen

Liu

2016

International Journal of Distributed Sensor Networks

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To perform Earth observation, more and more satellites are equipped with high-resolution sensors like hyperspectral imagers, which generate data at tens of Gbps. Researchers aim to maximize the volume of data available for use on the ground in near-real time. To achieve this goal, many solutions have recently been proposed to perform data collection through satellite networks. Most of these solutions have so far been focusing on either source rate control and load balancing, or heuristic routing. However, optimizing routing together with resources allocation is critical for improving delivery performance. In this paper, we challenge the fact that transmission paths have to be built under high link variability with limited resources, and develop a throughput-optimal solution based on the utility maximization framework. For delay performance, we embed a distance factor into the objective of the framework and derive a geographic-location-aware backpressure algorithm. Further, we exploit transmission opportunities missed by backpressure-type algorithms to accelerate data transfer. The simulation results show that our algorithms are able to deliver large volumes of data in time, and scale well in all scenarios tested.

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A novel routing design in the IP-based GEO/LEO hybrid satellite networks

Cited by 24 publications

References 28 publications

Machine Learning with Adaptive Time Stepping for Dynamic Traffic Load Prediction in 6G Satellite Networks

Machine Learning with Adaptive Time Stepping for Dynamic Traffic Load Prediction in 6G Satellite Networks

Threat analysis for space information network based on network security attributes: a review

Towards a throughput-optimal routing algorithm for data collection on satellite networks

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