Full Text:   <180>

CLC number: 

On-line Access: 2024-03-04

Received: 2024-01-11

Revision Accepted: 2024-02-20

Crosschecked: 0000-00-00

Cited: 0

Clicked: 378

Citations:  Bibtex RefMan EndNote GB/T7714

-   Go to

Article info.
Open peer comments

Journal of Zhejiang University SCIENCE C 1998 Vol.-1 No.-1 P.

http://doi.org/10.1631/FITEE.2400025


Optimal replication strategy for mitigating burst traffic in information-centric satellite networks: a focus on remote sensing image transmission


Author(s):  Ziyang XING, Xiaoqiang DI, Hui QI, Jing CHEN, Jinhui CAO, Jinyao LIU, Xusheng LI, Zichu ZHANG, Yuchen ZHU, Lei CHEN, Kai HUANG, Xinghan HUO

Affiliation(s):  Jilin Key Laboratory of Network and Information Security, Changchun 130022, China; more

Corresponding email(s):   dixiaoqiang@cust.edu.cn

Key Words:  Information-centric satellite network, Burst traffic, Content delivery, Federated reinforcement learning, Mixed integer linear programming model, Bloom filter, Dynamic network


Ziyang XING, Xiaoqiang DI, Hui QI, Jing CHEN, Jinhui CAO, Jinyao LIU,Xusheng LI, Zichu ZHANG, Yuchen ZHU, Lei CHEN, Kai HUANG, Xinghan HUO. Optimal replication strategy for mitigating burst traffic in information-centric satellite networks: a focus on remote sensing image transmission[J]. Frontiers of Information Technology & Electronic Engineering, 1998, -1(-1): .

@article{title="Optimal replication strategy for mitigating burst traffic in information-centric satellite networks: a focus on remote sensing image transmission",
author="Ziyang XING, Xiaoqiang DI, Hui QI, Jing CHEN, Jinhui CAO, Jinyao LIU,Xusheng LI, Zichu ZHANG, Yuchen ZHU, Lei CHEN, Kai HUANG, Xinghan HUO",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="-1",
number="-1",
pages="",
year="1998",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.2400025"
}

%0 Journal Article
%T Optimal replication strategy for mitigating burst traffic in information-centric satellite networks: a focus on remote sensing image transmission
%A Ziyang XING
%A Xiaoqiang DI
%A Hui QI
%A Jing CHEN
%A Jinhui CAO
%A Jinyao LIU
%A Xusheng LI
%A Zichu ZHANG
%A Yuchen ZHU
%A Lei CHEN
%A Kai HUANG
%A Xinghan HUO
%J Journal of Zhejiang University SCIENCE C
%V -1
%N -1
%P
%@ 2095-9184
%D 1998
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.2400025

TY - JOUR
T1 - Optimal replication strategy for mitigating burst traffic in information-centric satellite networks: a focus on remote sensing image transmission
A1 - Ziyang XING
A1 - Xiaoqiang DI
A1 - Hui QI
A1 - Jing CHEN
A1 - Jinhui CAO
A1 - Jinyao LIU
A1 - Xusheng LI
A1 - Zichu ZHANG
A1 - Yuchen ZHU
A1 - Lei CHEN
A1 - Kai HUANG
A1 - Xinghan HUO
J0 - Journal of Zhejiang University Science C
VL - -1
IS - -1
SP -
EP -
%@ 2095-9184
Y1 - 1998
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.2400025


Abstract: 
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 (CDNs) 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 focused 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 utilize 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 (LEO) satellite constellation, we validate the effectiveness of our proposed strategy, achieving a significant 17% reduction in 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.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Open peer comments: Debate/Discuss/Question/Opinion

<1>

Please provide your name, email address and a comment





Journal of Zhejiang University-SCIENCE, 38 Zheda Road, Hangzhou 310027, China
Tel: +86-571-87952783; E-mail: cjzhang@zju.edu.cn
Copyright © 2000 - 2024 Journal of Zhejiang University-SCIENCE