Gravity-based network traffic abstraction and laser ON/OFF control in optical satellite networks

卫星 计算机科学 激光器 卫星星座 网络拓扑 计算机网络 分布式计算 航空航天工程 工程类 物理 光学
作者
Wei Wang,Hongjie Zhang,Yongli Zhao,Kexin Gao,Liyazhou Hu,Jie Zhang
出处
期刊:Journal of Optical Communications and Networking [The Optical Society]
卷期号:15 (12): 958-958 被引量:6
标识
DOI:10.1364/jocn.499491
摘要

As the cost of launching low Earth orbit satellites continuously decreases, satellite-based communications networks are emerging as a new area for both academia and industry. Lasers are already employed for building inter-satellite links, forming optical satellite networks. The orbiting nature of satellites determines that the optical satellite networks are usually uniformly distributed around the Earth, to provide seamless coverage to any place at all times. However, the end users on the Earth are non-uniformly distributed. As a result, many satellites with laser links might not be utilized efficiently. From the energy perspective, this work studies the energy-efficiency issues of the inter-satellite laser links. We first model the optical satellite networks by presenting the satellite constellation with inter-satellite laser design principles and introduce the laser ON/OFF control problem accordingly. To explore the possibility of saving energy in the massive satellite deployment, we further introduce the gravity-based network traffic model and propose a gravity-based network traffic abstraction (GNTA) model to evaluate the importance of each laser link. Accordingly, we further propose a GNTA-based ON/OFF control (GOOC) algorithm to improve the energy efficiency of inter-satellite laser links by switching OFF parts of the laser links that are less utilized. We evaluate the GOOC’s performance using simulation, and results show that switching OFF 20% of the laser terminals in the full-gridmesh topology can improve the energy efficiency by about 10%, with an acceptable cost of network performance degradation.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
cwn完成签到,获得积分10
刚刚
zhuzhu完成签到,获得积分0
刚刚
丘比特应助彩色的蓝天采纳,获得10
刚刚
ChoccyPasta完成签到,获得积分10
1秒前
1秒前
感动的冬云完成签到,获得积分10
1秒前
嘤嘤嘤发布了新的文献求助10
2秒前
wuhaixia完成签到,获得积分10
2秒前
正版DY完成签到,获得积分10
2秒前
333发布了新的文献求助10
2秒前
醒醒发布了新的文献求助10
2秒前
xfxx发布了新的文献求助10
3秒前
Sissi完成签到 ,获得积分10
3秒前
校长完成签到,获得积分20
3秒前
尼亚吉拉完成签到,获得积分10
3秒前
3秒前
布布发布了新的文献求助10
3秒前
Zhang发布了新的文献求助10
4秒前
qinqin发布了新的文献求助10
5秒前
顾夏包发布了新的文献求助30
5秒前
钰宁发布了新的文献求助10
5秒前
NexusExplorer应助ZZZ采纳,获得10
6秒前
7秒前
顺心书琴完成签到,获得积分10
7秒前
习习应助Nifeng采纳,获得10
7秒前
mrmrer发布了新的文献求助10
7秒前
9秒前
MUSTer一一完成签到 ,获得积分10
9秒前
通通通完成签到,获得积分10
9秒前
9秒前
务实的菓完成签到 ,获得积分10
10秒前
似水流年完成签到,获得积分10
10秒前
An慧完成签到,获得积分10
10秒前
Hello应助阿金采纳,获得10
10秒前
10秒前
10秒前
12秒前
顾夏包完成签到,获得积分10
12秒前
小土豆发布了新的文献求助50
13秒前
科研通AI5应助跑在颖采纳,获得10
13秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Social media impact on athlete mental health: #RealityCheck 1020
Ensartinib (Ensacove) for Non-Small Cell Lung Cancer 1000
Unseen Mendieta: The Unpublished Works of Ana Mendieta 1000
Bacterial collagenases and their clinical applications 800
El viaje de una vida: Memorias de María Lecea 800
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3527849
求助须知:如何正确求助?哪些是违规求助? 3107938
关于积分的说明 9287239
捐赠科研通 2805706
什么是DOI,文献DOI怎么找? 1540033
邀请新用户注册赠送积分活动 716893
科研通“疑难数据库(出版商)”最低求助积分说明 709794