Ground-Station Based Software-Defined LEO Satellite Networks

Xia, Dan; Zheng, Xiaolong; Duan, Pengrui; Wang, Chaoyu; Liu, Liang; Ma, Huadóng

doi:10.1109/icpads47876.2019.00102

Cited by 12 publications

(3 citation statements)

References 16 publications

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“…However, even this alone is not enough for data exchange to be efficient. The quality of data exchange may also depend on antenna gain, network relay speed, and even geographical conditions [31][32][33]. LEO satellites, which are closer to the Earth than other satellite systems, move relatively faster in their orbits and therefore communication can be established from the ground stations for limited times.…”

Section: Intorductionmentioning

confidence: 99%

Modeling and simulation of earth coverage of a low earth orbit (LEO) satellite

Bakırcı

2024

European Mechanical Science

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Efficient management of operations in near space, just beyond the Earth’s atmosphere, relies on the precise control of satellites positioned relatively close to our planet. Satellite systems, serving critical functions in telecommunications, observation, exploration, and more, have demonstrated their prowess as a transformative technology, consistently delivering high-precision data over numerous years. Among satellite systems, Low Earth Orbit (LEO) technology is gaining prominence due to its advantages, including lower power requirements for transmission, reduced propagation delays, and heightened coverage for polar regions. Achieving optimal efficiency from LEO satellites necessitates a thorough understanding of their fundamental orbital parameters and precise control over them. This study explores the orbital analysis and Earth coverage considerations of LEO satellites, scrutinizing orbital parameters in detail to compute coverage areas across various scenarios. Through this investigation, the potential benefits of data exchange with ground stations facilitated by LEO satellites are explored. In addition, the implications are discussed regarding the adjustment of data exchange topologies according to geographical locations and country borders.

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Section: Intorductionmentioning

confidence: 99%

Modeling and simulation of earth coverage of a low earth orbit (LEO) satellite

Bakırcı

2024

European Mechanical Science

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“…Therefore [94] reuses the ground stations instead of dedicated GEO satellites to establish a more scalable control plane. This introduces other issues, mostly that the ground stations have a limited view of the satellites, and this is addressed in the paper.…”

Section: Sdn-based Solutionsmentioning

confidence: 99%

LEO satellite networking relaunched: Survey and current research challenges

Cedric Westphal,

Lin Han,

Richard Li

2023

ITU J-FET

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This document surveys recent and current developments in Low Earth Orbit (LEO) satellite networking. It presents a brief overview of satellite networking in order to contextualize the issue. It then focuses on current research work in emerging domains, such as machine learning, Software-Defined Networking (SDN), low latency networking, green networking, Information-Centric Networks (ICN), etc. For each of these, it presents recent works and a direction of the research community within that emerging domain. The paper also describes the current state of standardization efforts in 3GPP and in IETF for LEO satellite networking. In particular, we present in some detail the direction these standards bodies are pointing towards for LEO networking with inter-satellites links. Finally, some future challenges and interesting research directions are described and encouraged. This is an overview of the current state of the LEO satellite research in both academic and industrial standardization environments which we believe will be helpful to understand the current state of the art.

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“…For each satellite, the altitude is 780 km, the available resources include 96 vCPUs and 112 GB memory, and the number of inter-satellite links is 4. We assume that the delay time of the inter-satellite link for the same orbital plane is 7.25 ms and 12.6 ms, respectively, for the adjacent orbital planes is 13.4 ms, and for the satelliteground link is 13.1 ms [34]. The bandwidth capacity of each inter-satellite link is 1 Gbps.…”

Section: A Simulation Setupmentioning

confidence: 99%

A Distributed Virtual Network Function Placement Approach in Satellite Edge and Cloud Computing

Gao,

Liu,

Kaushik

2021

Preprint

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Satellite edge computing has become a promising way to provide computing services for Internet of Things (IoT) devices in remote areas, which are out of the coverage of terrestrial networks, nevertheless, it is not suitable for largescale IoT devices due to the resource limitation of satellites. Cloud computing can provide sufficient available resources for IoT devices but it does not meet the service requirements of delay sensitive users as high network latency. Collaborative edge and cloud computing is to facilitate flexible service provisioning for numerous IoT devices by incorporating the advantages of edge and cloud computing. In this paper, we investigate the virtual network function (VNF) placement problem in collaborative satellite edge and cloud computing to minimize the satellite network bandwidth usage and the service end-to-end delay. We formulate the VNF placement problem as an integer non-linear programming problem and propose a distributed VNF placement (D-VNFP) algorithm to address it, as the VNF placement problem is NP-hard. The experiments are conducted to evaluate the effectiveness of the proposed D-VNFP algorithm. The results show that the proposed D-VNFP algorithm outperforms the existing baseline algorithms of Greedy and Viterbi for solving the VNF placement problem in satellite edge and cloud computing.Index Terms-Satellite edge and cloud computing, virtual network function (VNF) placement, network bandwidth cost, end-to-end delay, distributed algorithm. I. INTRODUCTIONT HE Internet of Things (IoT) has been widely applied in various fields, e.g., disaster monitoring, ocean transportation, target recognition and tracking, etc [1]. Large amount of computation tasks produced by IoT devices need to be offloaded by terrestrial networks to remote servers for execution as IoT devices have the low computing capacity and battery power. However, terrestrial networks have not been set up in some remote areas due to high capital expenditures and harsh environments. Fortunately, low earth orbit (LEO) satellite networks, which have low communication delay and global coverage, can provide data collection, computing, and communication services for remote IoT devices without the coverage of terrestrial networks [2]. In general, there are two computation offloading approaches in satellite-based IoT environment, where one is that computation tasks should be offloaded to ground cloud data centers by satellite networks for further processing [3]-[5], the other is that edge servers deployed on satellites can directly provide computing services for computation tasks [6]- [8].

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Ground-Station Based Software-Defined LEO Satellite Networks

Cited by 12 publications

References 16 publications

Modeling and simulation of earth coverage of a low earth orbit (LEO) satellite

Modeling and simulation of earth coverage of a low earth orbit (LEO) satellite

LEO satellite networking relaunched: Survey and current research challenges

A Distributed Virtual Network Function Placement Approach in Satellite Edge and Cloud Computing

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