IEEE Communications Surveys and Tutorials最新文献

{"title":"Architectures, Benefits, Security, and Privacy Issues of Internet of Nano Things: A Comprehensive Survey, Opportunities, and Research Challenges","authors":"Aryan Rana;Deepika Gautam;Pankaj Kumar;Ashok Kumar Das","doi":"10.1109/COMST.2024.3423477","DOIUrl":"10.1109/COMST.2024.3423477","url":null,"abstract":"The Internet of Things (IoT) has profoundly impacted today’s world. Recent technological advancements in the Internet and Information Communication (ICT) have paved the way for revolutionary technologies, making life easier for humankind. IoT has found applications in almost every sector, enabling the connectivity of digital objects to the Internet. This technology has undergone significant advancements, leading to the emergence of a new paradigm called the Internet of Nano Things (IoNT). IoNT represents the latest evolution of IoT and has garnered attention from researchers and scientists. By combining nanotechnology with IoT, IoNT offers a more advanced paradigm than its generic counterpart, potentially reshaping the current IoT landscape. However, these limitless benefits come with challenges that persist in both IoT and the emerging IoNT ecosystem. Moreover, additional challenges need to be addressed due to the miniature nature and novelty of the IoNT ecosystem. The lack of research in the field of IoNT has motivated us to undertake this study. Our research aims to highlight the security and privacy challenges specific to IoNT and nano communication. Furthermore, we examine important architectures related to IoNT, nanoscale communication, real-life applications of IoNT, as well as simulators and testbeds useful for IoNT. We also address challenges associated with the incorporation of novel technologies, primarily Artificial Intelligence (AI), into IoNT. To achieve this, we provide a detailed review of existing works related to the IoNT ecosystem, emphasizing security and privacy concerns. Additionally, we explore the opportunities and future directions for IoNT, serving as a reference for further research.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"27 2","pages":"1152-1190"},"PeriodicalIF":34.4,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141546033","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CrowdTransfer: Enabling Crowd Knowledge Transfer in AIoT Community","authors":"Yan Liu;Bin Guo;Nuo Li;Yasan Ding;Zhouyangzi Zhang;Zhiwen Yu","doi":"10.1109/COMST.2024.3423319","DOIUrl":"10.1109/COMST.2024.3423319","url":null,"abstract":"Artificial Intelligence of Things (AIoT) is an emerging frontier based on the deep fusion of Internet of Things (IoT) and Artificial Intelligence (AI) technologies. The fundamental goal of AIoT is to establish a self-organizing, self-learning, self-adaptive, and continuous-evolving AIoT system by orchestrating intelligent connections among Humans, Machines, and IoT devices. Although advanced deep learning techniques enhance the efficient data processing and intelligent analysis of complex IoT data, they still suffer from notable challenges when deployed to practical AIoT applications, such as constrained resources, dynamic environments, and diverse task requirements. Knowledge transfer, a popular and promising area in machine learning, is an effective method to enhance learning performance by avoiding the exorbitant costs associated with data recollection and model retraining. Notably, although there are already some valuable and impressive surveys on transfer learning, these surveys introduce approaches in a relatively isolated way and lack the recent advances of various knowledge transfer techniques for AIoT field. This survey endeavors to introduce a new concept of knowledge transfer, referred to as Crowd Knowledge Transfer (CrowdTransfer), which aims to transfer prior knowledge learned from a crowd of agents to reduce the training cost and as well as improve the performance of the model in real-world complicated scenarios. Particularly, we present four transfer modes from the perspective of crowd intelligence, including derivation, sharing, evolution and fusion modes. Building upon conventional transfer learning methods, we further delve into advanced crowd knowledge transfer models from three perspectives for various AIoT applications: intra-agent knowledge transfer, centralized inter-agent knowledge transfer, and decentralized inter-agent knowledge transfer. Furthermore, we explore some applications of AIoT areas, such as human activity recognition, urban computing, multi-robot system, and smart factory. Finally, we discuss the open issues and outline future research directions of knowledge transfer in AIoT community.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"27 2","pages":"1191-1237"},"PeriodicalIF":34.4,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141546034","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Toward the Integration and Convergence Between 5G and TSN Technologies and Architectures for Industrial Communications: A Survey","authors":"Jorge Sasiain;David Franco;Asier Atutxa;Jasone Astorga;Eduardo Jacob","doi":"10.1109/COMST.2024.3422613","DOIUrl":"10.1109/COMST.2024.3422613","url":null,"abstract":"Communication networks are in constant evolution to adapt to the ever-changing demands of modern services and applications. On the one hand, technologies within the framework of the fifth generation of communication networks (5G), currently in a steady course towards 6G, are being designed with unprecedented performance and flexibility capabilities to empower the digital transformation of heterogeneous vertical industries. On the other hand, Time-Sensitive Networking (TSN) is being developed to enable converged network infrastructures able to satisfy the most stringent communication requirements in regards to bounded low latency and reliability. In verticals such as manufacturing, a joint usage of 5G and TSN is very promising to enable revolutionary use cases that coexist with the constraints imposed by industrial communications and systems. In this paper, we exhaustively survey the technology landscape concerning the integration between 5G and TSN technologies, including the perspectives of both industry and academia. In the first part of this paper, we provide a comprehensive review of relevant standards and outcomes from industry initiatives. We first examine the capabilities provided by TSN and their application to industrial communications. Likewise, we contextualize the 5G architecture and its key enabling technologies, and later provide a comprehensive review of the architecture and mechanisms to enable the integration between TSN and 5G. In the second part of this paper, we extensively survey the state of the art from academic literature concerning proposals that contribute to enabling, improving, and/or demonstrating different aspects of the integration or interworking between 5G and TSN technologies.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"27 1","pages":"259-321"},"PeriodicalIF":34.4,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10584103","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141546037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"On the Ground and in the Sky: A Tutorial on Radio Localization in Ground-Air-Space Networks","authors":"Hazem Sallouha;Sharief Saleh;Sibren De Bast;Zhuangzhuang Cui;Sofie Pollin;Henk Wymeersch","doi":"10.1109/COMST.2024.3417336","DOIUrl":"10.1109/COMST.2024.3417336","url":null,"abstract":"The inherent limitations in scaling up ground infrastructure for future wireless networks, combined with decreasing operational costs of aerial and space networks, are driving considerable research interest in multisegment ground-air-space (GAS) networks. In GAS networks, where ground and aerial users share network resources, ubiquitous and accurate user localization becomes indispensable, not only as an end-user service but also as an enabler for location-aware communications. This breaks the convention of having localization as a byproduct in networks primarily designed for communications. To address these imperative localization needs, the design and utilization of ground, aerial, and space anchors require thorough investigation. In this tutorial, we provide an in-depth systemic analysis of the radio localization problem in GAS networks, considering ground and aerial users as targets to be localized. Starting from a survey of the most relevant works, we then define the key characteristics of anchors and targets in GAS networks. Subsequently, we detail localization fundamentals in GAS networks, considering 3D positions, orientations, and velocities. Afterward, we thoroughly analyze radio localization systems in GAS networks, detailing the system model, design aspects, and considerations for each of the three GAS anchors. Preliminary results are presented to provide a quantifiable perspective on key design aspects in GAS-based localization scenarios. We then identify the vital roles 6G enablers are expected to play in radio localization in GAS networks.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"27 1","pages":"218-258"},"PeriodicalIF":34.4,"publicationDate":"2024-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141944597","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Semantics-Empowered Space-Air-Ground-Sea Integrated Network: New Paradigm, Frameworks, and Challenges","authors":"Siqi Meng;Shaohua Wu;Jiaming Zhang;Junlan Cheng;Haibo Zhou;Qinyu Zhang","doi":"10.1109/COMST.2024.3416309","DOIUrl":"10.1109/COMST.2024.3416309","url":null,"abstract":"In the coming sixth generation (6G) communication era, to provide seamless and ubiquitous connections, the space-air-ground-sea integrated network (SAGSIN) is envisioned to address the challenges of communication coverage in areas with difficult conditions, such as the forest, desert, and sea. Considering the fundamental limitations of the SAGSIN including large-scale scenarios, highly dynamic channels, and limited device capabilities, traditional communications based on Shannon information theory cannot satisfy the communication demands. Moreover, bit-level reconstruction is usually redundant for many human-to-machine or machine-to-machine applications in the SAGSIN. Therefore, it is imperative to consider high-level communications towards semantics exchange, called semantic communications. In this survey, according to the interpretations of the term “semantics”, including “significance”, “meaning”, and “effectiveness-related information”, we review state-of-the-art works on semantic communications from three perspectives, which are 1) significance representation and protection, 2) meaning similarity measurement and meaning enhancement, and 3) ultimate effectiveness and effectiveness yielding. Sequentially, three types of semantic communication systems can be correspondingly introduced, namely the significance-oriented, meaning-oriented, and effectiveness/task-oriented semantic communication systems. Implementation of the above three types of systems in the SAGSIN necessitates a new perception-communication-computing-actuation-integrated paradigm (PCCAIP), where all the available perception, computing, and actuation techniques jointly facilitate significance-oriented sampling & transmission, semantic extraction & reconstruction, and task decision. Finally, we point out some future challenges on semantic communications in the SAGSIN. This survey provides a comprehensive review on the future semantic communications in the SAGSIN, and elaborates on the performance metrics and techniques related to semantic communications for references and further in-depth investigations.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"27 1","pages":"140-183"},"PeriodicalIF":34.4,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141944598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Survey of mmWave Radar-Based Sensing in Autonomous Vehicles, Smart Homes and Industry","authors":"Hao Kong;Cheng Huang;Jiadi Yu;Xuemin Shen","doi":"10.1109/COMST.2024.3409556","DOIUrl":"10.1109/COMST.2024.3409556","url":null,"abstract":"Sensing technology plays a crucial role in bridging the physical and digital worlds. By transforming a multitude of physical phenomena into digital data, it significantly enhances our understanding of the environment and is instrumental in a wide range of applications. Given the wide bandwidth and short wavelength characteristics, millimeter wave (mmWave) radar sensing is considered one of the most promising sensing techniques beyond mmWave communication. In this paper, we provide a comprehensive survey of mmWave radar-based sensing techniques and applications in autonomous vehicles, smart homes, and industry. Specifically, we first review widely exploited mmWave radar techniques and signal processing techniques from the perspective of dedicated radars and communication integration, which are the basis of mmWave radar sensing. Then, we introduce mainstream machine learning techniques, especially the latest deep learning techniques for designing applications with mmWave signals. Related hardware devices, available public datasets, and evaluation metrics are also presented. Afterward, we provide a taxonomy of emerging mmWave radar sensing applications, and review the developments in object detection, ego-motion estimation, simultaneous localization and mapping, activity recognition, pose estimation, gesture recognition, speech recognition, vital sign monitoring, user authentication, indoor positioning, industrial imaging, industrial measurement, environmental monitoring, etc. We conclude the paper by discussing challenges and potential future research directions.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"27 1","pages":"463-508"},"PeriodicalIF":34.4,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141944600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Less Data, More Knowledge: Building Next-Generation Semantic Communication Networks","authors":"Christina Chaccour;Walid Saad;Mérouane Debbah;Zhu Han;H. Vincent Poor","doi":"10.1109/COMST.2024.3412852","DOIUrl":"10.1109/COMST.2024.3412852","url":null,"abstract":"Semantic communication is viewed as a revolutionary paradigm that can potentially transform how we design and operate wireless communication systems. However, despite a recent surge of research activities in this area, remarkably, the research landscape is still limited in at least three ways. First and foremost, the definition of a “semantic communication system” is ambiguous and varies widely between different studies. This lack of consensus makes it challenging to develop rigorous and scalable frameworks for building semantic communication networks. Secondly, current approaches to building semantic communication networks are limited by their reliance on data-driven and information-driven AI-augmented networks. These networks remain “tied” to the data, which limits their ability to perform versatile logic. In contrast, knowledge-driven and reasoning-driven AI-native networks would allow for more flexible and powerful communication capabilities. However, there is currently a lack of technical foundations to support such networks. Thirdly, the concept of “semantic representation” is not well understood yet, and its role in embedding meaning and structure in data transferred across wireless network is still a subject of active research. The development of semantic representations that are minimalist, generalizable, and efficient is critical to enabling the transmitter and receiver to generate content via a minimally semantic representation. To address these limitations, in this tutorial, we propose the first rigorous and holistic vision of an end-to-end semantic communication network that is founded on novel concepts from artificial intelligence (AI), causal reasoning, transfer learning, and minimum description length theory. We first discuss how the design of semantic communication networks requires a move from data-driven AI-augmented networks, in which wireless networks remain “tied” to data, towards reasoning-driven AI-native networks which can perform versatile logic and generalizable intelligence. We then distinguish the concept of semantic communications from several other approaches that have been conflated with it. We opine that building effective and efficient semantic communication systems necessitates surpassing the creation of new encoder and decoder types at the transmitter/receiver side, or developing an “AI for wireless” framework that only extracts application features or fine-tunes wireless protocols/algorithms. Then, we identify the main tenets that are needed to build an end-to-end semantic communication network. Among those building blocks of a semantic communication network, we highlight the necessity of creating semantic representations of data that satisfy the key properties of minimalism, generalizability, and efficiency so as to faithfully represent the data and enable the transmitter and receiver to do more with less. We then explain how those representations can form the basis of a so-called semantic language that will ","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"27 1","pages":"37-76"},"PeriodicalIF":34.4,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10554663","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141944602","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Survey on Beyond 5G Network Slicing for Smart Cities Applications","authors":"Wajid Rafique;Joyeeta Rani Barai;Abraham O. Fapojuwo;Diwakar Krishnamurthy","doi":"10.1109/COMST.2024.3410295","DOIUrl":"10.1109/COMST.2024.3410295","url":null,"abstract":"Beyond fifth generation (B5G) is expected to tremendously improve network capabilities by using a higher frequency band compared to 5G, capable of delivering higher network capacity with much lower latency. It is expected that there will be around 30 billion connected objects by 2030, approximately 3.5 times the population then which underscores the pressing need for advanced network capabilities to support diverse applications ranging from smart transportation and energy management to healthcare and public safety. Network slicing enables sharing of network resources by transforming the physical network into logically independent networks, each specifically tailored to meet the requirements of heterogeneous services (e.g., Internet of Things applications, gaming services, holographic communication). Each slice is an end-to-end logical network comprising network, compute, and storage resources. Softwarization and virtualization are the main drivers for innovation in B5G, enabling network developers and operators to develop network-aware applications to match customer demands. Smart cities vertical offers unique service characteristics, performance requirements, and technical challenges in B5G network slicing. Therefore, this paper provides a comprehensive survey on B5G network slicing use cases, synergies, practical implementations and applications based on their quality of service parameters for smart cities applications. The paper gives a detailed taxonomy of the B5G network slicing framework requirements, design, dynamic intra-slice and inter-slice resource allocation techniques, management and orchestration, artificial intelligence/machine learning-empowered network slicing designs, implementation testbeds, 3GPP specifications and projects/standards for B5G network slicing. Furthermore, the paper provides a thorough discussion on the technical challenges that can arise when implementing B5G network slicing for smart cities applications and offers potential solutions. Finally, the paper discusses B5G network slicing current and future research directions for smart cities applications.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"27 1","pages":"595-628"},"PeriodicalIF":34.4,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10551400","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141944599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Toward 6G Optical Fronthaul: A Survey on Enabling Technologies and Research Perspectives","authors":"Abdulhalim Fayad;Tibor Cinkler;Jacek Rak","doi":"10.1109/COMST.2024.3408090","DOIUrl":"10.1109/COMST.2024.3408090","url":null,"abstract":"The anticipated launch of the Sixth Generation (6G) of mobile technology by 2030 will mark a significant milestone in the evolution of wireless communication, ushering in a new era with advancements in technology and applications. 6G is expected to deliver ultra-high data rates and almost instantaneous communications, with three-dimensional coverage for everything, everywhere, and at any time. In the 6G Radio Access Networks (RANs) architecture, the Fronthaul connects geographically distributed Remote Units (RUs) to Distributed/Digital Units (DUs) pool. Among all possible solutions for implementing 6G fronthaul, optical technologies will remain crucial in supporting the 6G fronthaul, as they offer high-speed, low-latency, and reliable transmission capabilities to meet the 6G strict requirements. This survey provides an explanation of the 5G and future 6G optical fronthaul concept and presents a comprehensive overview of the current state of the art and future research directions in 6G optical fronthaul, highlighting the key technologies and research perspectives fundamental in designing fronthaul networks for 5G and future 6G. Additionally, it examines the benefits and drawbacks of each optical technology and its potential applications in 6G fronthaul networks. This paper aims to serve as a comprehensive resource for researchers and industry professionals about the current state and future prospects of 6G optical fronthaul technologies, facilitating the development of robust and efficient wireless networks of the future.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"27 1","pages":"629-666"},"PeriodicalIF":34.4,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141276523","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cybersecurity of Satellite Communications Systems: A Comprehensive Survey of the Space, Ground, and Links Segments","authors":"Sara Salim;Nour Moustafa;Martin Reisslein","doi":"10.1109/COMST.2024.3408277","DOIUrl":"10.1109/COMST.2024.3408277","url":null,"abstract":"Satellite communications (Satcoms) systems have become an integral part of modern society, providing critical infrastructure for a wide range of applications. However, as the reliance on Satcoms has increased, cyberattacks on Satcoms systems have emerged as a severe concern, with the potential to cause significant disruption, economic losses, and even loss of life. We first give a tutorial-style overview of the architecture of a Satcoms system, which typically consists of a space segment, a ground segment (encompassing the terrestrial ground stations and users), and a links segment. Following the taxonomy provided by this segment structure, we provide—to the best of our knowledge—the first comprehensive survey of the state-of-the-art cyberattacks (cyberthreats) on all three segments of Satcoms systems. For each Satcoms system segment, we organize the cyberattacks according to categories of Satcoms-specific cyberattacks, which we relate to the threat classifications in the general STRIDE cyberthreat model. Also, for all three segments of Satcoms systems, we comprehensively survey the general cybersecurity strategies and the specific cybersecurity mechanisms (techniques) that defend Satcoms systems against cyberattacks. We distill the critical learned lessons associated with Satcoms cybersecurity strategies, such as the need to balance security with cost-effectiveness. Finally, we outline the open challenges and future research directions in Satcoms systems cybersecurity.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"27 1","pages":"372-425"},"PeriodicalIF":34.4,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141944601","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}