The Solution of the Problem of the Delay Determination in the Information Transmission and Processing in the LEO Satellite Internet of Things System

Ilchenko, M. E.; Нарытник, Т. Н.; Prisyazhny, Vladimir; Kapshtyk, Sergii; Matvienko, Sergey

doi:10.1109/picst47496.2019.9061350

Cited by 5 publications

(6 citation statements)

References 5 publications

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“…The processing time is t P k = D k α k f k , where α k is the average CPU cycles to process the task per bit, and f k is the CPU frequency. From the perspective of system robustness, we consider the maximum propagation delay based on the satellite orbit height H S , the minimum elevation angle β min and the maximum central angle θ max , denoted as τ max = (Re+H S ) sin θmax c cos βmin [15], where R e is the Earth radius. Therefore, the total delay, when a task is conducted on the cloud, can be calculated as…”

Section: System Model and Problem Formulationmentioning

confidence: 99%

Control-Oriented Power Allocation for Integrated Satellite-UAV Networks

Lei

Feng

Wang

et al. 2023

IEEE Wireless Commun. Lett.

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This letter presents a sensing-communicationcomputing-control (SC 3 ) integrated satellite unmanned aerial vehicle (UAV) network, where UAVs are equipped with sensors, mobile edge computing (MEC) servers, base stations and satellite communication modules. Like a nervous system, this integrated network is capable of organizing multiple field robots in remote areas, so as to perform mission-critical tasks which are dangerous for humans. Aiming at activating this nervous system with multiple SC 3 loops, we present a control-oriented optimization problem. Different from traditional studies which mainly focused on communication metrics, we address the power allocation issue to minimize the sum linear quadratic regulator (LQR) control cost of all SC 3 loops. Specifically, we show the convexity of the problem and reveal the relationship between the optimal transmit power and intrinsic entropy rates of different SC 3 loops. For the assure-to-be-stable case, we derive a closed-form solution for ease of practical applications. After demonstrating the superiority of the control-oriented power allocation, we further highlight its difference from the classic capacity-oriented water-filling method.

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Section: System Model and Problem Formulationmentioning

confidence: 99%

Control-Oriented Power Allocation for Integrated Satellite-UAV Networks

Lei

Feng

Wang

et al. 2023

IEEE Wireless Commun. Lett.

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“…Реалізувати туманні обчислення у супутниковому сегменті систем інтернету речей можна шляхом внесення до орбітального сегменту обчислювальної потужності для реалізації туманних обчислень. В роботах [1,6,20] Враховуючи особливості архітектури LoRaWAN, корисне навантаження кубсату, можна доповнити таким обладнанням:…”

Section: реалізація граничних та туманних обчислень у супутникових си...unclassified

“…Використання в архітектурі системи StarLink оптичних/лазерних ліній зв'язку між супутниками (Laser Inter-Satellite Link) [13,20] дозволяє розглядати рішення про доповнення орбітального угруповання супутників StarLink (Star Link Constellation) супутниками-обчислювачами (див. рис.…”

Section: низькоорбітальна система широкосмугового доступуunclassified

“…27. № 6 М. Ю. Ільченко, Т. М. Наритник, В. І. Присяжний, С. В. Капштик, С. А. Матвієнко ВСТУП Протягом останнього десятиріччя інтернет речей став важливою складовою частиною сучасних інфокомунікацій [12,[19][20][21]. За даними компанії Transforma Insights [12] в 2019 році загальна кількість активних пристроїв інтернету речей становила 7.6 млрд.…”

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Space infrastructure of the Internet of things. State and prospects of development

Ilchenko¹,

Narytnyk²,

Prysiazhnyi³

et al. 2021

Kosm. nauka tehnol.

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We present an overview of possibilities for existing Satellite Communication Systems utilization to provide Internet of Things Services. It is shown that existing Satellite Communication Systems provide traffic transmission for IoT Systems with Cloud Architecture. The proposals are explicated on the possibility of using Fog and Edge Computing for Satellite Communication Systems. The implementation of Fog and Edge computing in IoT Systems requires the modernization of the Low-Earth Orbit (LEO) and Geostationary Orbit (GEO) Satellite Communication Systems, and we show the ways of their enhancement. To increase the efficiency of IoT data processing and the reliability of IoT Data Storage, we propose to construct an Orbital Cloud Data Storage in GEO, which consists of several GEO Satellites - Cloud Computing Data Centers. Such a structure would require the development of methods of access providing to the Orbital Cloud Data Storage. For these purposes, our propositions include using GEO High-Throughput Satellites and satellites from the structure of LEO Satellite Communication. The issues of interaction between Orbital Cloud Data Storage and ground-based Cloud Data Processing and Storage Infrastructure are briefly considered. The orbital slots in GEO are proposed for the location of GEO Satellites - Cloud Computing Data Centers.

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“…Regarding cloudization in LEO satellite systems, the authors in [198] investigated an LEO satellite constellation with nanosatellites and CubeSats using fog computing. To realize fog computing, satellite computers were included in each of the distributed satellites [199].…”

Section: Refmentioning

confidence: 99%

Survey on Aerial Radio Access Networks: Toward a Comprehensive 6G Access Infrastructure

Dao

Pham

et al. 2021

Preprint

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Current network access infrastructures are characterized by heterogeneity, low latency, high throughput, and high computational capability, enabling massive concurrent connections and various services. Unfortunately, this design does not pay significant attention to mobile services in underserved areas. In this context, the use of aerial radio access networks (ARANs) is a promising strategy to complement existing terrestrial communication systems. Involving airborne components such as unmanned aerial vehicles, drones, and satellites, ARANs can quickly establish a flexible access infrastructure on demand. ARANs are expected to support the development of seamless mobile communication systems toward a comprehensive sixthgeneration (6G) global access infrastructure. This paper provides an overview of recent studies regarding ARANs in the literature. First, we investigate related work to identify areas for further exploration in terms of recent knowledge advancements and analyses. Second, we define the scope and methodology of this study. Then, we describe ARAN architecture and its fundamental features for the development of 6G networks. In particular, we analyze the system model from several perspectives, including transmission propagation, energy consumption, communication latency, and network mobility. Furthermore, we introduce technologies that enable the success of ARAN implementations in terms of energy replenishment, operational management, and data delivery. Subsequently, we discuss application scenarios envisioned for these technologies. Finally, we highlight ongoing research efforts and trends toward 6G ARANs.

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The Solution of the Problem of the Delay Determination in the Information Transmission and Processing in the LEO Satellite Internet of Things System

Cited by 5 publications

References 5 publications

Control-Oriented Power Allocation for Integrated Satellite-UAV Networks

Control-Oriented Power Allocation for Integrated Satellite-UAV Networks

Space infrastructure of the Internet of things. State and prospects of development

Survey on Aerial Radio Access Networks: Toward a Comprehensive 6G Access Infrastructure

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