首页|信息中心卫星网络中缓解突发流量的最优替代策略—聚集遥感图像传输

信息中心卫星网络中缓解突发流量的最优替代策略—聚集遥感图像传输

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信息中心卫星网络在遥感图像传输中发挥着重要作用,然而,突发业务的出现在满足日益增长的带宽需求方面带来重大挑战.传统内容传输网络(CDN)由于需要预先部署内容,不具备应对此类突发流量的能力.本文提出一种最优替代策略,用于缓解信息中心卫星网络中的突发流量,特别是针对遥感图像传输.当多个用户在短时间内订阅相同的遥感图像内容时,所提策略选择最优的替代交付卫星节点,有效减少网络传输数据,防止突发流量导致的吞吐量下降.将内容传输过程公式化为一个多目标优化问题,应用马尔可夫决策确定突发流量减少的最优值,并利用联邦强化学习求解.此外,基于布隆过滤器设计了图像划分和识别方法,快速检索编码后的遥感图像.通过软件模拟低轨道卫星星座,验证了所提策略的有效性,平均交付时延减少17%.本文为卫星网络内容高效传输,特别是遥感图像传输,提供宝贵见解,并提出一种有前景的途径缓解信息中心环境中的突发流量挑战.
Optimal replication strategy for mitigating burst traffic in information-centric satellite networks:a focus on remote sensing image transmission
Information-centric satellite networks play a crucial role in remote sensing applications,particularly in the transmission of remote sensing images.However,the occurrence of burst traffic poses significant challenges in meeting the increased bandwidth demands.Traditional content delivery networks are ill-equipped to handle such bursts due to their pre-deployed content.In this paper,we propose an optimal replication strategy for mitigating burst traffic in information-centric satellite networks,specifically focusing on the transmission of remote sensing images.Our strategy involves selecting the most optimal replication delivery satellite node when multiple users subscribe to the same remote sensing content within a short time,effectively reducing network transmission data and preventing throughput degradation caused by burst traffic expansion.We formulate the content delivery process as a multi-objective optimization problem and apply Markov decision processes to determine the optimal value for burst traffic reduction.To address these challenges,we leverage federated reinforcement learning techniques.Additionally,we use bloom filters with subdivision and data identification methods to enable rapid retrieval and encoding of remote sensing images.Through software-based simulations using a low Earth orbit satellite constellation,we validate the effectiveness of our proposed strategy,achieving a significant 17%reduction in the average delivery delay.This paper offers valuable insights into efficient content delivery in satellite networks,specifically targeting the transmission of remote sensing images,and presents a promising approach to mitigate burst traffic challenges in information-centric environments.

Information-centric satellite networkBurst trafficContent deliveryFederated reinforcement learningMixed-integer linear programming modelBloom filterDynamic network

邢紫阳、底晓强、祁晖、陈静、曹金辉、刘晋尧、李旭生、张子初、朱玉臣、陈雷、黄锴、霍星翰

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吉林省网络与信息安全重点实验室,中国 长春市,130022

长春理工大学计算机科学技术学院,中国 长春市,130022

长春理工大学信息化中心,中国 长春市,130022

信息中心卫星网络 突发流量 内容传输 联邦强化学习 混合整数线性规划模型 布隆过滤器 动态网络

National Natural Science Foundation of China

U21A20451

2024

10.1631/FITEE.2400025

信息与电子工程前沿(英文)
浙江大学

信息与电子工程前沿(英文)

CSTPCD
影响因子：0.371
ISSN：2095-9184
年,卷(期)：2024.25(6)
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