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The image integrity of real-time monitoring is crucial for monitoring crop growth, helping farmers and researchers improve production efficiency and crop yields. Unfortunately, existing schemes just focus on ground equipment and drone imaging, neglecting satellite networks in remote or extreme environments. Given that satellite internet features wide area coverage, we propose SEAIS, a secure and efficient agricultural image storage scheme combining blockchain and satellite networks. SEAIS presents the mathematical model of image processing and transmission based on satellite networks. Moreover, to ensure the integrity and authenticity of image data during pre-processing such as denoising and enhancement, SEAIS includes a secure agricultural image storage and verification method based on blockchain, homomorphic encryption, and zero-knowledge proof. Specifically, images are stored via IPFS, with hash values and metadata recorded on the blockchain, ensuring immutability and transparency. The simulation results show that SEAIS exhibits more stable and efficient processing times in extreme environments. Also, it maintains low on-chain storage overhead, enhancing scalability. [ABSTRACT FROM AUTHOR]

Copyright of Space-Integrated-Ground Information Networks is the property of Beijing Xintong Media Co., Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Satellite networks have attracted a lot of attention due to their unique advantages such as wide coverage and high data rate. In particular, the use of inter-satellite links (ISLs) allows multiple satellites to collaborate to provide a wider range of services. However, it is more difficult for the design of ISLs and resource allocation with the increasing number of satellites, which further leads to high network cost. Therefore, this paper aims to design an efficient ISLs establishment scheme and power allocation method to reduce the network cost. First, the network cost optimization problem is formulated as a mixed integer linear programming. Then, with equal power allocation scheme, a Lagrange relaxation method is used to decompose the optimization problem into two subproblems, i.e., routing problem and ISLs establishment problem. Specifically, the optimal routing scheme is equivalent to solving a min-cost max-flow problem of time expanded graph. The ISLs design problem can be directly solved by using branch and bound method in parallel. Moreover, with given routing and ISL scheme, the optimal power allocation is given based on convex optimization theory. Finally, the simulation results have be provided for verifying the effectiveness of proposed algorithm. [ABSTRACT FROM AUTHOR]

Efficiently handling huge data amounts and enabling processing-intensive applications to run in faraway areas simultaneously is the ultimate objective of 5G networks. Currently, in order to distribute computing tasks, ongoing studies are exploring the incorporation of fog-cloud servers onto satellites, presenting a promising solution to enhance connectivity in remote areas. Nevertheless, analyzing the copious amounts of data produced by scattered sensors remains a challenging endeavor. The conventional strategy of transmitting this data to a central server for analysis can be costly. In contrast to centralized learning methods, distributed machine learning (ML) provides an alternative approach, albeit with notable drawbacks. This paper addresses the comparative learning expenses of centralized and distributed learning systems to tackle these challenges directly. It proposes the creation of an integrated system that harmoniously merges cloud servers with satellite network structures, leveraging the strengths of each system. This integration could represent a major breakthrough in satellite-based networking technology by streamlining data processing from remote nodes and cutting down on expenses. The core of this approach lies in the adaptive tailoring of learning techniques for individual entities based on their specific contextual nuances. The experimental findings underscore the prowess of the innovative lightweight strategy, LMAED2L (Enhanced Deep Learning for Earth Data Analysis), across a spectrum of machine learning assignments, showcasing remarkable and consistent performance under diverse operational conditions. Through a strategic fusion of centralized and distributed learning frameworks, the LMAED2L method emerges as a dynamic and effective remedy for the intricate data analysis challenges encountered within satellite networks interfaced with cloud servers. The empirical findings reveal a significant performance boost of our novel approach over traditional methods, with an average increase in reward (4.1 %), task completion rate (3.9 %), and delivered packets (3.4 %). This report suggests that these advancements will catalyze the integration of cutting-edge machine learning algorithms within future networks, elevating responsiveness, efficiency, and resource utilization to new heights.

The lack of terrestrial 4G and 5G communication infrastructure in rural and remote areas aggravates the digital divide. Satellite communication is important to achieve the universal goal of connecting the digitally unconnected population through global coverage. In this paper, first, we discuss the feasibility of hosting web services in satellites through several examples of radiation-hardened processors and computational boards. Next, we propose a Space-Based Hosting Service (SBHS) approach to deploy the content-servers or copies of terrestrial content-servers in satellites to achieve the low-latency service requirements. For SBHS, we develop mathematical models for communication, queuing, as well as computation, and use B+ tree to estimate computational delay and computational energy consumption of the content-server. Further, an optimization algorithm using Markov Decision Process (MDP) is designed to schedule computational cores in Low Earth Orbit (LEO) satellites to minimize queuing delay and computational energy consumption. The efficacy of our SBHS is evaluated using extensive simulations with the Wikipedia use-case in the Iridium-NEXT satellite constellation model under varying traffic conditions from different countries. The results show that SHBS is able to achieve less than 10 ms round trip latency worldwide and minimum end-to-end delays of 9.19 ms and 24.29 ms, respectively, for text-based and multimedia-based traffic. The 92.51% and 88.66% reduction in delay for text and multimedia traffic, respectively, compared to the benchmark schemes underlines the benefits of hosting content-servers in space for achieving ultra-low latency.

Recent technological advancements in space, air, and ground components have made possible a new network paradigm called “space-air-ground integrated network” (SAGIN). Unmanned aerial vehicles (UAVs) play a key role in SAGINs. However, due to UAVs' high dynamics and complexity, real-world deployment of a SAGIN becomes a significant barrier to realizing such SAGINs. UAVs are expected to meet key performance requirements with limited maneuverability and resources with space and terrestrial components. Therefore, employing UAVs in various usage scenarios requires well-designed planning in algorithmic approaches. This paper provides an essential review and analysis of recent learning algorithms in a UAV-assisted SAGIN. We consider possible reward functions and discuss the state-of-the-art algorithms for optimizing the reward functions, including Q-learning, deep Q-learning, multi-armed bandit, particle swarm optimization, and satisfaction-based learning algorithms. Unlike other survey papers, we focus on the methodological perspective of the optimization problem, applicable to various missions on a SAGIN. We consider real-world configurations and the 2-dimensional (2D) and 3-dimensional (3D) UAV trajectories to reflect deployment cases. Our simulations suggest the 3D satisfaction-based learning algorithm outperforms other approaches in most cases. With open challenges discussed at the end, we aim to provide design and deployment guidelines for UAV-assisted SAGINs.

The image integrity of real-time monitoring is crucial for monitoring crop growth, helping farmers and researchers improve production efficiency and crop yields. Unfortunately, existing schemes just focus on ground equipment and drone imaging, neglecting satellite networks in remote or extreme environments. Given that satellite internet features wide area coverage, we propose SEAIS, a secure and efficient agricultural image storage scheme combining blockchain and satellite networks. SEAIS presents the mathematical model of image processing and transmission based on satellite networks. Moreover, to ensure the integrity and authenticity of image data during pre-processing such as denoising and enhancement, SEAIS includes a secure agricultural image storage and verification method based on blockchain, homomorphic encryption, and zero-knowledge proof. Specifically, images are stored via IPFS, with hash values and metadata recorded on the blockchain, ensuring immutability and transparency. The simulation results show that SEAIS exhibits more stable and efficient processing times in extreme environments. Also, it maintains low on-chain storage overhead, enhancing scalability.

New versions of HTTP protocols have been developed to overcome many of the limitations of the original HTTP/1.1 protocol and its underlying transport mechanism over TCP. In this paper, we investigated the performance of modern Internet protocols such as HTTP/2 over TCP and HTTP/3 over QUIC in high-latency satellite links. The goal was to uncover the interaction of the new features of HTTP such as parallel streams and optimized security handshake with modern congestion control algorithms such as CUBIC and BBR over high-latency links. An experimental satellite network emulation testbed was developed for the evaluation. The study analyzed several user-level web performance metrics such as average page load time, First Contentful Paint and Largest Contentful Paint. The results indicate an overhead problem with HTTP/3 that becomes more significant when using a loss-based congestion control algorithm such as CUBIC which is widely used on the Internet. Also, the results highlight the significance of the web page structure and how objects are distributed in it. Among the various Internet protocols evaluated, the results show that HTTP/3 over QUIC will perform better by an average of 35% than HTTP/2 over TCP in satellites links specifically with a more aggressive congestion algorithm such as BBR. This can be attributed to the non-blocking stream multiplexing feature of QUIC and the reduced TLS handshake of HTTP/3.

Satellite networks provide high-bandwidth, wide-coverage network services that complement ground networks.However, multitudinous loop links in satellite networks can lead to broadcast storms, where broadcast packets continuously propagate along the loops in the network, ultimately resulting in network paralysis. Existing solutions, such as Minimum Spanning Tree (MST) algorithm, often result in low bandwidth utilization and higher forwarding latency. This paper introduces a novel hardware-based approach to mitigate these challenges by selectively suppressing redundant broadcasts. Unlike traditional methods, our approach utilizes a RAM-based lookup table to record the characteristics and timestamps of broadcast packets, then determines whether the packets should be discarded or forwarded based on these records.In the experiment, the proposed approach achieves a frequency of 251.8 MHz and an on-chip power of 0.106W on the Field-Programmable Gate Array (FPGA) chip. [ABSTRACT FROM AUTHOR]

The low earth orbit (LEO) satellite constellations exhibit dynamic network topology due to the intermittent inter-satellite links (ISLs). To ensure efficient data delivery in LEO satellite networks, it is crucial to find an appropriate routing protocol that is capable of accommodating the dynamic topology. In this paper, we consider two typical IP-based and ICN-based link-state routing protocols (i.e., OSPF and NLSR, respectively) and investigate the adaptability in LEO satellite networks. Specifically, we first analyze and compare their advantages and disadvantages in LEO satellite networks from the perspectives of link state detection, link state synchronization, and packet forwarding scheme. To verify our analysis, we conduct extensive packet-level experiments on OMNeT++. Our analysis and simulation unveil several critical insights. First, IP-based OSPF (following push-based communication) outperforms the ICN-based NLSR (following pull-based communication) in terms of the routing convergence and control overhead in satellite networks. Specifically, OSPF converges faster than NLSR up to 90.8% and yields less control overhead under the Iridium constellation. Second, the ICN-based NLSR (supporting Interest aggregation and in-network caching) outperforms the IP-based OSPF in terms of the packet delivery performance, especially under the content-sharing traffic pattern (up to 206%). However, the occasional ISL failure significantly reduces the content delivery performance of NLSR under the point-to-point traffic pattern. To sum up, our study unveils the necessity of properly integrating IP-based and ICN-based link-state routing paradigms in LEO satellite networks. [ABSTRACT FROM AUTHOR]

Satellite edge computing has attracted the attention of many scholars, but the limited resources of satellite networks bring great difficulties to the processing of edge-computing-dependent tasks. Therefore, under the system model of the satellite-terrestrial joint network architecture, this paper proposes an efficient scheduling strategy based on task degrees and a resource allocation strategy based on the improved sparrow search algorithm, aiming at the low success rate of application processing caused by the dependency between tasks, limited resources, and unreasonable resource allocation in the satellite edge network, which leads to the decline in user experience. The scheduling strategy determines the processing order of tasks by selecting subtasks with an in-degree of 0 each time. The improved sparrow search algorithm incorporates opposition-based learning, random search mechanisms, and Cauchy mutation to enhance search capability and improve global convergence. By utilizing the improved sparrow search algorithm, an optimal resource allocation strategy is derived, resulting in reduced processing latency for subtasks. The simulation results show that the performance of the proposed algorithm is better than other baseline schemes and can improve the processing success rate of applications. [ABSTRACT FROM AUTHOR]

New versions of HTTP protocols have been developed to overcome many of the limitations of the original HTTP/1.1 protocol and its underlying transport mechanism over TCP. In this paper, we investigated the performance of modern Internet protocols such as HTTP/2 over TCP and HTTP/3 over QUIC in high-latency satellite links. The goal was to uncover the interaction of the new features of HTTP such as parallel streams and optimized security handshake with modern congestion control algorithms such as CUBIC and BBR over high-latency links. An experimental satellite network emulation testbed was developed for the evaluation. The study analyzed several user-level web performance metrics such as average page load time, First Contentful Paint and Largest Contentful Paint. The results indicate an overhead problem with HTTP/3 that becomes more significant when using a loss-based congestion control algorithm such as CUBIC which is widely used on the Internet. Also, the results highlight the significance of the web page structure and how objects are distributed in it. Among the various Internet protocols evaluated, the results show that HTTP/3 over QUIC will perform better by an average of 35% than HTTP/2 over TCP in satellites links specifically with a more aggressive congestion algorithm such as BBR. This can be attributed to the non-blocking stream multiplexing feature of QUIC and the reduced TLS handshake of HTTP/3. [ABSTRACT FROM AUTHOR]

In this paper, we theoretically study the achievable capacity of orthogonal and non-orthogonal multiple access (OMA and NOMA) schemes in supporting downlink satellite communication networks. Considering that various satellite applications have different delay quality-of-service (QoS) requirements, the concept of effective capacity is introduced as a delay-guaranteed capacity metric to represent users' various delay requirements. Specifically, the analytical expressions of effective capacities for each user achieved with the NOMA and OMA schemes are first studied. Then, approximated effective capacities achieved in some special cases, exact closed-form expressions of users' achievable effective capacity, and the capacity difference between NOMA and OMA schemes are derived. Simulation results are finally provided to validate the theoretical analysis and show the suitable limitations of the NOMA and OMA schemes, such as the NOMA scheme is more suitable for users with better channel quality when transmit signal-to-noise (SNR) is relatively large, while it is suitable for users with worse link gain when transmit SNR is relatively small. Moreover, the influences of delay requirements and key parameters on user selection strategy and system performance are also shown in the simulations. [ABSTRACT FROM AUTHOR]

In recent years, satellite networks with specialized features have been able to play a significant role in shaping daily life and lifestyle choices across different segments of society, particularly the youth population. With that in mind, the purpose of this study is to evaluate the performance of Persian language satellite networks on the lifestyle of young people from Bourdieu's perspective using a data envelopment analysis model. To achieve this objective, the input and output indices of the study were determined based on a literature review and expert opinions. However, due to the indeterministic nature of many indices, the Rough DEA model was applied. This model converts non-deterministic variables to intervals using the "α" level, resulting in an interval data envelopment analysis model. Then, the efficient intervals were ranked and compared using the MRA technique. The efficiency of each evaluated network was obtained by performing a sensitivity analysis at different "α" levels. The research revealed that "Man o To" network had the most significant impact on the lifestyle of young people, followed by "Persian BBC" in second place, "Nasim network" in third place, and "GEM" network in last place. Finally, strategies to prevent the negative effects of foreign satellite channels on the lifestyle of young people and increase the audience base of Persian language domestic channels are presented. [ABSTRACT FROM AUTHOR]

Satellite Internet-of-Things (IoT) is a critical part to build information infrastructure for environmental and ecological monitoring in remote areas where the cellular networks are uneasy to cover. When massive IoT terminals pour in the crowded satellite channels, how to enhance the spectrum utility of satellite band and guarantee the system capacity calls for full investigations. In this paper, a secure spectrum optimization scheme is proposed in satellite IoT by introducing blockchain to hamper malicious users to involve in the spectrum sharing. A market-oriented spectrum optimization strategy is designed to improve the satellite systems' benefits wherein the heterogeneous satellite channels are fully be considered and priced. In this circumstance, differentiated pricing is adopted to satisfy the various spectrum users' demands. When applying blockchain to secure the spectrum trading, the edge computing along with the mechanism of user reputation are devised to address the concerns of limited computation power for general IoT devices. Besides, the consensus algorithm of Delegated Proof of Stake is used to improve the computing efficiency so as to better fit in the application circumstance of satellite IoT. Numerical results are provided to evaluate the performances of our proposed solution on satellite channel pricing and system benefits. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Chongqing University of Posts & Telecommunications (Natural Science Edition) is the property of Chongqing University of Posts & Telecommunications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In view of the large response time delay of content placement in ICN satellite network, considering the regional characteristics of content and user's interest preference, a cache placement strategy for LEO satellite network based on regional interest perception is proposed, which takes into account the balanced distribution of content and reduces the response time delay. Firstly, the label of content is used as the distance measure of content similarity, and the whole network content is divided into multiple content clusters by a clustering algorithm. Secondly, according to the historical request data, the interest preference of the content cluster is evaluated, so as to divide the cache space of the whole network content. Finally, taking the average time delay as the optimization objective, the greedy algorithm is used to solve the problem of optimal placement of content. Simulation results show that the proposed method is superior to the comparison method in content response delay and cache hit rate. [ABSTRACT FROM AUTHOR]

Future integrated terrestrial, aerial, and space networks will involve thousands of low-Earth-orbit (LEO) satellites, which will form a network of mega-constellations. These mega-constellations will play a significant role in providing communication and Internet services anywhere, at any time, and for everything. Due to the large scale and highly dynamic nature of future LEO satellite networks (SatNets), their management will be a complicated process, especially the aspect of mobility management and its two components: location management and handover management. In this article, we present a comprehensive and critical review of the state-of-the-art research in location management for LEO SatNets. First, we give an overview of the Internet Engineering Task Force (IETF) mobility management standards (e.g., Mobile IPv6 and Proxy Mobile IPv6) and discuss the limitations of their location management techniques for future LEO SatNets. We highlight the mobility characteristics of future LEO SatNets and their challenging features, and we describe two unprecedented future location management scenarios. A taxonomy of existing location management solutions for LEO SatNets is also presented with solutions classified according to three approaches. The “Issues to consider” section draws attention to critical points related to each of the reviewed approaches that should be considered in future LEO SatNets location management. To identify the research gaps, the current state of LEO SatNets location management is summarized. Noteworthy future research directions are recommended. The article provides a road map for researchers and industry to shape the future of location management for LEO SatNets.

Low Earth Orbit (LEO) Satellite Network (SatNet) with their mega-constellations are expected to play a key role in providing ubiquitous Internet and communications services in the future. LEO SatNets will provide wide-area coverage and support service availability, continuity, and scalability. To support the integration of SatNets and terrestrial Fifth Generation (5G) networks and beyond, the satellite communication industry has become increasingly involved with the 3rd Generation Partnership Project (3GPP) standardization activities for 5G. In this work, we review the 3GPP standardization activities for the integration of SatNets in 5G and beyond. The 3GPP use cases of SatNets are highlighted and potential requirements to realize them are summarized as well. The impacted areas of New Radio (NR) are discussed with some potential solutions. The foreseen requirements for the management and orchestration of SatNets within 5G are described. Future standardization directions are discussed to support the full integration of SatNets in Sixth Generation (6G) with the goal of ubiquitous global connectivity.

Introduction Television and satellite channels, in addition to other forms of social media, have facilitated the rapid and widespread transmission of foreign lifestyles, social relationships, culture, art, beliefs, and values to Iranian society. As a result, satellite networks with their diverse capabilities have become capable of affecting all aspects of human life, particularly altering the daily lives and lifestyle choices of people from all sectors of society, particularly the youth. Thus, the aim of this study is to evaluate the effectiveness of Persian-language satellite networks in shaping the lifestyles of young people and from the perspective of Bourdieu's indicators by means of the data envelopment analysis model. Materials and Methods The research method employed is case-driven and context-specific. In order to implement the model, a library study was initially conducted to evaluate the impact of TV and satellite networks on youth lifestyles according to Bourdieu's perspective. Based on the opinions of experts in the field, the input and output indices of the study were determined. To account for the non-deterministic nature of many indices, the Rough DEA model was used, which converts non-deterministic variables to intervals using the "α" level and results in an interval data envelopment analysis model. Using the MRA ranking method, the efficient intervals were ranked and compared. Then the efficiency of each evaluated network was determined through a sensitivity analysis performed at different "α" levels. Finally, each of the networks was ranked. Discussion and Results Based on the data collected and analyzed, the "Man o To" network was found to have the greatest influence on the lifestyles of young people. The "Persian BBC" network ranked second, followed by the "Nasim network" in third place, and finally, the "GEM" network placed last. These results suggest that there are significant differences in the impact of satellite networks on the lifestyles of young people, and that the "Man o To" network has been the most effective at shaping the lifestyle choices of this demographic. Conclusions Based on the research findings, it is recommended that the administrators of domestic Persian-language satellite media produce high-quality and appealing content in the fields of information, news, entertainment, and educational programming. This strategy will help boost the lifestyle indicators among the youth. Additionally, it is suggested that individuals with greater social capital and trust consume media resources from these aforementioned fields.

Satellite edge computing has attracted the attention of many scholars, but the limited resources of satellite networks bring great difficulties to the processing of edge-computing-dependent tasks. Therefore, under the system model of the satellite-terrestrial joint network architecture, this paper proposes an efficient scheduling strategy based on task degrees and a resource allocation strategy based on the improved sparrow search algorithm, aiming at the low success rate of application processing caused by the dependency between tasks, limited resources, and unreasonable resource allocation in the satellite edge network, which leads to the decline in user experience. The scheduling strategy determines the processing order of tasks by selecting subtasks with an in-degree of 0 each time. The improved sparrow search algorithm incorporates opposition-based learning, random search mechanisms, and Cauchy mutation to enhance search capability and improve global convergence. By utilizing the improved sparrow search algorithm, an optimal resource allocation strategy is derived, resulting in reduced processing latency for subtasks. The simulation results show that the performance of the proposed algorithm is better than other baseline schemes and can improve the processing success rate of applications.

Abstract The dynamic weather condition is a major concern for optimum channel utilization in recent times, especially at higher frequencies with larger bandwidth for 5G applications. Over the years, rain-induced attenuation among the hydrometeors has been linked as the major cause of signal impairment especially at the frequency, f ≥ 10 GHz. However, when f > 18 GHz, the significant impact of other hydrometeors; cloud/fog, and scintillation increases tremendously, especially for Low Earth Orbit, LEO satellites. LEO satellites find applications in fibre optics technology, scientific research, remote sensing, surveillance, meteorology, satellite imaging, and other applications. In this paper, the assessment of combined impairments based on 5-year (2012-2016) data has been carried out and a dynamic adaptive intelligent scheme (DAIS) has been adopted to achieve a good quality of service along the satellite channels operating at Ku-V band frequencies over five stations representing different climatic regions in Nigeria namely: Port Harcourt (PH), Akure, Ilorin, Zaria, and Kano. The proposed DAIS based on fuzzy logic was able to achieve a significant reduction in the transmitting power by about 70% and SNR by 50% across the frequencies considered without altering the information content of the downlink parameters, thereby improving the QoS significantly and adhere to Customer Service Level Agreements (CSLAs) irrespective of the weather dynamics. The overall results show that the adaptive intelligent techniques can effectively fix signal links under the dynamic weather conditions for both satellite and wireless networks in this region. Information from the results is timely because it will serve as the bedrock for the newly launched transformation to the digital video broadcasting (DVB) system in Nigeria for effective service delivery.

In recent years, the adoption of innovative technologies in maritime transport and logistics systems has become a key aspect towards their development and growth, especially due to the complex and heterogeneous nature of the maritime environment. On the other hand, Internet of Things (IoT) solutions are gaining importance in the shipping industry thanks to the huge number of distributed cameras and sensors in modern ships, cargoes and sea ports, which can be exploited to improve safety, costs and productivity. This paper presents an experimental evaluation of a maritime platform, which enables a wide range of 5G-based services in the context of logistics and maritime transportation. Its core is a Narrow Band (NB)-IoT framework used to run massive IoT services on top of a hybrid terrestrial–satellite network and feed a OneM2M platform with significant data on maritime transport to develop high-level and value-added logistic applications on top. Among the many different services that could be provided by the maritime platform, we focus on the cargo-ship container tracking use case through the Global Tracking System, which allows for continuous container monitoring all over the seas in a port-to-port service scenario. The results of the experimental tests illustrate the capacity of the platform in managing the high number of messages transmitted by the container tracking devices (i.e., more than 3000) and its efficiency in limiting the average maximum latency and packet loss below 5.5 s and 0.9%, respectively.

With the rapid development of 5G and the Internet of Things, satellite networks are emerging as an indispensable part of realizing wide-area coverage. The growth of the constellation of low-orbit satellites makes it possible to deploy edge computing services in satellite networks. This is, however, challenging due to the topological dynamics and limited resources of satellite networks. To improve the performance of edge computing in a satellite network, we propose a satellite network task deployment method based on SDN (software-defined network) and ICN (information-centric network). In this method, based on the full analysis of satellite network resources, a mission deployment model of a low-orbit satellite network is established. The genetic algorithm is then used to solve the proposed method. Experiments confirm that this method can effectively reduce the response delay of the tasks and the network traffic caused by task processing. [ABSTRACT FROM AUTHOR]

Satellite networks (SNs) are heterogeneous networks composed of typical functional domains, such as communication domains, observation domains, etc. Since the resources are independent among domains, and are highly dynamic with the movement of satellites, it is extremely difficult to capture the potential interaction relationship among various resources, even less to realize the coordinated scheduling of cross-domain resources in large-scale SNs. Motivated by these factors, we firstly propose a multi-aspect expanded hypergraph (MAEH) to accurately depict the Spatio-temporal features of resources in various domains as well as functional property, which is presented by different aspects. Particularly, the “aspect” can involve a group of resources with a similar feature in a hyperedge rather than a bilateral relationship between two individuals, thus the MAEH can dramatically reduce the redundant connections. By exploiting the MAEH, we model the multi-domain resource allocation problem in the form of mixed-integer linear programming to maximize the completed tasks. Through the topological nested characteristic of the MAEH, we propose a two-stage scheme to accomplish the resource allocation rapidly with lower computational complexity and to improve the resource utilization ratio efficiently. Simulation results validate that compared with the optimal performance, the executive time of the proposed scheme is average fivefold less under 4% extra communication resource cost. Besides, the resource utilization ratio improves over 15% by cross-domain collaboration. [ABSTRACT FROM AUTHOR]

Mobile relaying is envisioned as a promising technology to alleviate the masking effect in satellite links. Nevertheless, due to the mobility and limited communication range, the network topology in mobile relay networks becomes highly dynamic and time-varying, resulting in increased difficulty of network optimization. This letter investigates unmanned aerial vehicles (UAVs) aided hybrid satellite-terrestrial network, where UAVs are served as mobile relay base stations to assist the communication between the satellite and ground users. We aim to maximize the number of served users by optimizing UAV trajectory and user link selection. To solve the formulated mixed-integer and non-convex optimization problem, we first find the optimal link selection via a designed graph neural network (GNN), and then adjust the UAV locations by using model-free reinforcement learning (RL), alternately. Numerical results demonstrate that our proposed scheme is superior to the state-of-the-art RL algorithms. [ABSTRACT FROM AUTHOR]

Recent years have witnessed a growing interest in Internet access from space assisted by low earth orbit (LEO) satellite networks. In the domain of the last-mile access for the Internet of Vehicles (IoV), hybrid free-space optical (FSO)/radio-frequency (RF) communication has recently attracted worldwide research efforts. While the transmission control protocol (TCP) is the most widely deployed transport protocol on the Internet, its performance in the error-prone environment of LEO satellite-assisted hybrid FSO/RF vehicular networks is not well understood. This paper develops a comprehensive analytical model based on the cross-layer approach for TCP performance, considering the FSO and RF satellite fading channels, modeled by the Gamma-Gamma and Nakagami- $m$ distributions, respectively. The error-control solutions, including the Reed-Solomon (RS) code and Selective repeat automatic repeat request (SR-ARQ), are also employed. Numerical results quantitatively demonstrate the impact of transmission errors at last-mile links and different parameters/settings of error-control solutions on the TCP performance. The paper also supports the selection of proper TCP variants for the considered networks.

Modern satellite VSAT networks can be applied not only to provide satellite radio and television broadcasting, but also to other domains, such as a two-way Internet access. For this objective it has become necessary to develop appropriate standards and data transmission techniques. An unquestionable advantage of satellite systems is reception range, which translates into possibility of building networks in almost any place on Earth. Depending on the application, such networks can use many topologies. The aim of the article is to review distributed information in this area, as well as to determine the directions of development of the next generation VSAT networks. For this purpose, the literature review has been provided, with due regard to the IEEE Xplore digital library databases, and supported by practical examples.

A random access framework based on random interleaving multiplexing (RIM) is proposed to further improve throughput for internet of things in satellite networks, which resort to the state-of-art physical layer techniques that can resolve multiple packet collisions issue. The interleavers are randomly selected by active devices from a set of available interleavers, which are used to differentiate signals of different devices sharing a subframe that consists of multiple time slots. The message passing detector (MPD) is utilized to decode collided packets. By means of transmission diversity and interference cancellation, the proposed scheme can be linked with the irregular repetition slotted ALOHA (IRSA), the RIM-IRSA protocol is proposed. The analysis of packet loss ratio (PLR) of the RIM-IRSA is given by using the density evolution method, and the optimal degree distributions are given. Simulation results show that the RIM-IRSA outperforms traditional IRSA protocol.

Copyright of Transactions of Nanjing University of Aeronautics & Astronautics is the property of Editorial Department of Journal of Nanjing University of Aeronautics & Astronautics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The current research status of SDN-based satellite communication networks was investigated, the SDN-based satellite communication network architecture and related key technical solutions was introduced and discussed; The opportunities and challenges faced by SDN-based satellite networks were discussed.