IEEE Communications Surveys and Tutorials最新文献

{"title":"Multibeam High Throughput Satellite: Hardware Foundation, Resource Allocation, and Precoding","authors":"Rui Chen;Wen-Xuan Long;Bingqian Wang;Yuan He;Ruijin Sun;Nan Cheng;Gan Zheng;Dusit Niyato","doi":"10.1109/COMST.2026.3673850","DOIUrl":"10.1109/COMST.2026.3673850","url":null,"abstract":"With its wide coverage and uninterrupted service, satellite communication is a critical technology for next-generation 6G communications. High throughput satellite (HTS) systems, utilizing multipoint beam and frequency multiplexing techniques, enable satellite communication capacity of up to Tbps to meet the growing traffic demand. Therefore, it is imperative to review the-state-of-the-art of multibeam HTS systems and identify their associated challenges and perspectives. Firstly, we summarize the multibeam HTS hardware foundations, including ground station systems, on-board payloads, and user terminals. Subsequently, we review the flexible on-board radio resource allocation approaches of bandwidth, power, time slot, and joint allocation schemes of HTS systems to optimize resource utilization and cater to non-uniform service demand. Additionally, we survey multibeam precoding methods for the HTS system to achieve full-frequency reuse and interference cancellation, which are classified according to different deployments such as single gateway precoding, multiple gateway precoding, on-board precoding, and hybrid on-board/on-ground precoding. Finally, we discuss the challenges related to Q/V band link outage, time and frequency synchronization of gateways, the accuracy of channel state information (CSI), payload light-weight development, and the application of deep learning (DL). Research on these topics will contribute to enhancing the performance of HTS systems and finally delivering high-speed data to areas underserved by terrestrial networks.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"28 ","pages":"5379-5415"},"PeriodicalIF":34.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147454470","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":"Intelligent Reflecting Surfaces for Integrated Sensing and Communications: From System Coexistence to Networked Mutualism","authors":"Qingqing Wu;Qiaoyan Peng;Ziheng Zhang;Xiaodan Shao;Yang Liu;Yifan Jiang;Yapeng Zhao;Yanze Zhu;Yilong Chen;Zixiang Ren;Jie Xu;Wen Chen;Rui Zhang","doi":"10.1109/COMST.2026.3686910","DOIUrl":"10.1109/COMST.2026.3686910","url":null,"abstract":"The rapid development of sixth-generation (6G) wireless networks requires seamless integration of communication and sensing to support ubiquitous intelligence and real-time, high-reliability applications. Integrated sensing and communication (ISAC) has emerged as a key solution for achieving this convergence, offering joint utilization of spectral, hardware, and computing resources. However, realizing high-performance ISAC remains challenging due to environmental line-of-sight (LoS) blockage, limited spatial resolution, and the inherent coverage asymmetry and resource coupling between sensing and communication. Intelligent reflecting surfaces (IRSs), featuring low-cost, energy-efficient, and programmable electromagnetic reconfiguration, provide a promising solution to overcome these limitations. This paper presents a comprehensive overview of IRS-aided wireless sensing and ISAC technologies, including IRS architectures, target detection and estimation techniques, beamforming designs, and performance metrics. It further explores IRS-enabled new opportunities for more efficient performance balancing, coexistence, and networking in ISAC systems, focuses on current design bottlenecks, and outlines future research directions. This paper aims to offer a unified design framework that guides the development of practical and scalable IRS-aided ISAC systems for the next-generation wireless network.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"28 ","pages":"6057-6100"},"PeriodicalIF":34.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147735738","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":"When Simultaneous Localization and Mapping Meets Wireless Communications: A Survey","authors":"Konstantinos Gounis;Sotiris A. Tegos;Dimitrios Tyrovolas;Panagiotis D. Diamantoulakis;George K. Karagiannidis","doi":"10.1109/COMST.2026.3707294","DOIUrl":"10.1109/COMST.2026.3707294","url":null,"abstract":"The availability of commercial wireless communication and sensing equipment combined with the advancements in intelligent autonomous systems scontribute to robust joint communications and simultaneous localization and mapping (SLAM). Autonomous vehicles are one of the several applications that directly benefit from millimeter-wave (mmWave) access, facilitating improved communications and accurate localization in the interest of control and navigation. This paper surveys the state-of-the-art in the intersection of SLAM and Wireless Communications, attributing the bidirectional impact of each with a focus on visual SLAM (V-SLAM) integration. We provide an overview of key concepts related to geometric channel modeling, and radio frequency (RF)-based localization and sensing. Several research directions are considered, including the interpretation of SLAM as a unified perception-estimation framework driven by wireless communications-based positioning and visual information, the integration of communication-aware objectives in active perception, and multi-modal odometry through the fusion of wireless measurements and complementary sensing modalities. We analyze estimation and control approaches such as Bayesian filters, feature-based pose estimation, perception-aware motion control, spatial methods for signal processing such as vector fields, and key technological aspects. Among other interesting findings, we observe that monocular V-SLAM might greatly benefit from RF/mmWave signals, as the latter can serve as a proxy for scale ambiguity resolution. Conversely, we find that wireless communications in the context of 5G and beyond can potentially benefit from visual odometry and landmark detection methods in the context of optimal geometric path prediction for wireless channels. Moreover, we examine other perception sources besides monocular vision for SLAM such as Radio SLAM, wireless fidelity (WiFi) SLAM, and light detection and ranging (LiDAR) SLAM, and describe a twofold relation with wireless communications. Finally, integrated solutions performing joint communications and localization appear to be in their infancy: theoretical and practical advancements could add higher-level localization and semantic perception capabilities to RF/mmWave and multi-antenna technologies.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"28 ","pages":"6481-6511"},"PeriodicalIF":50.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148341971","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":"Graph Neural Networks for Next-Generation-IoT: Recent Advances and Open Challenges","authors":"Nguyen Xuan Tung;Le Tung Giang;Bui Duc Son;Seon Geun-Jeong;Trinh Van Chien;Lajos Hanzo;Won-Joo Hwang","doi":"10.1109/COMST.2025.3613845","DOIUrl":"10.1109/COMST.2025.3613845","url":null,"abstract":"Graph Neural Networks (GNNs) have emerged as a powerful framework for modeling complex interconnected systems, hence making them particularly well-suited to address the growing challenges of next-generation Internet of Things (NG-IoT) networks. Despite increasing interest in this area, existing studies remain fragmented, and there is a lack of comprehensive guidance on how GNNs can be systematically applied to NG-IoT systems. As NG-IoT systems evolve toward 6G, they incorporate diverse technologies such as massive MIMO, reconfigurable intelligent surfaces (RIS), terahertz (THz) communication, satellite systems, mobile edge computing (MEC), and ultra-reliable low-latency communication (URLLC). These advances promise unprecedented connectivity, sensing, and automation but also introduce significant complexity, requiring new approaches for scalable learning, dynamic optimization, and secure, decentralized decision-making. This survey provides a comprehensive and forward-looking exploration of how GNNs can empower NG-IoT environments structured as ten open research questions that span the relevant theoretical foundations, practical deployments, and emerging integration pathways. We commence by exploring the fundamental paradigms of GNNs and articulating the motivation for their use in NG-IoT networks. Besides, to further justify their suitability, we intrinsically connect GNNs for the first time with the family of low-density parity-check (LDPC) codes, modeling the NG-IoT as dynamic constrainted graphs where GNNs harness belief propagation for convergence and interpretability through density evolution and EXIT charts. We highlight the distinct roles of node-, edge-, and graph-level tasks in tackling key challenges and demonstrate the GNNs’ ability to overcome the limitations of traditional optimization methods. Following this, we examine the application of GNNs across core NG-enabling technologies and their integration with distributed frameworks to support privacy preservation and distributed intelligence. We then delve into the challenges posed by adversarial attacks, offering insights into defense mechanisms to secure GNN-based NG-IoT networks. Lastly, we examine how GNNs can be integrated with emerging technologies like integrated sensing and communication (ISAC), satellite-air-ground-sea integrated networks (SAGSIN), and quantum computing. Our findings highlight the transformative potential of GNNs in improving efficiency, scalability, and security within NG-IoT systems, paving the way for future advances. Finally, we summarize the key lessons learned throughout the paper and outline promising future research directions, along with a set of design guidelines aimed at facilitating the development of efficient, scalable, and secure GNN models tailored for NG-IoT applications.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"28 ","pages":"2226-2262"},"PeriodicalIF":50.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145133706","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":"Unsourced Random Access: A Comprehensive Survey","authors":"Mert Ozates;Mohammad Javad Ahmadi;Mohammad Kazemi;Deniz Gündüz;Tolga M. Duman","doi":"10.1109/COMST.2025.3637685","DOIUrl":"10.1109/COMST.2025.3637685","url":null,"abstract":"Multiple access communication systems enable numerous users to share common communication resources, playing a crucial role in wireless networks. With the emergence of the sixth generation (6G) and beyond communication networks, supporting massive machine-type communications with sporadic activity patterns is expected to become a critical challenge. Unsourced random access (URA) has emerged as a promising paradigm to address this challenge by decoupling user identification from data transmission through the use of a common codebook. This survey offers a comprehensive overview of URA solutions, encompassing both theoretical foundations and practical applications. We present a systematic classification of URA solutions across three primary channel models: Gaussian multiple access channels (GMACs), single-antenna fading channels, and multiple-input multiple-output (MIMO) fading channels. For each category, we analyze and compare state-of-the-art solutions in terms of performance, complexity, and practical feasibility. Additionally, we discuss critical challenges such as interference management, computational complexity, and synchronization. The survey concludes with promising future research directions and potential methods to address existing limitations, providing a roadmap for researchers and practitioners in this rapidly evolving field.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"28 ","pages":"955-984"},"PeriodicalIF":50.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145609357","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":"Hardware Security Modules for Secure Communications in the Industrial Internet of Things","authors":"Shahid Latif;Djamel Djenouri;Zeba Idrees;Jawad Ahmad;Qurat-Ul-Ain Mastoi;Zhuo Zou","doi":"10.1109/COMST.2025.3600161","DOIUrl":"10.1109/COMST.2025.3600161","url":null,"abstract":"The Industrial Internet of Things (IIoT) offers transformative potential but introduces critical security risks, including unauthorized access, data breaches, and privacy compromise. Hardware Security Modules (HSMs) have emerged as robust solutions to protect IIoT ecosystems by enabling secure cryptographic operations, providing tamper-resistant hardware and creating trusted execution environments. This work presents the first comprehensive review of HSMs tailored for secure IIoT communications, addressing their architectural foundations, operational mechanisms, and deployment scenarios. It first outlines the IIoT security landscape and HSM deployment architectures, including cloud-based, edge-integrated, and distributed models. Next, cutting-edge HSM implementations are analyzed, emphasizing their effectiveness in authentication, secure communication protocols, and physical tamper resistance. It then explores attack surfaces and vulnerabilities, such as firmware exploits, logical flaws, and network-based threats, along with mitigation strategies. Case studies from smart manufacturing, energy grids, and logistics demonstrate practical HSM applications, while a comparative evaluation assesses commercial and open-source solutions based on performance, compliance, and scalability. Emerging trends such as AI-driven threat detection, post-quantum cryptography, and decentralized HSMs are also discussed. Finally, key challenges are highlighted, including latency in real-time systems, supply chain risks, and regulatory hurdles, and future directions for research and industry adoption are proposed. This work serves as a roadmap for securing IIoT deployments, offering actionable insights for researchers, practitioners, and policymakers.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"28 ","pages":"64-108"},"PeriodicalIF":50.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144898675","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":"Evaluating Transport Layer Congestion Control Algorithms: A Comprehensive Survey","authors":"Christian L. Vielhaus;Caspar von Lengerke;Vincent Latzko;Justus Rischke;Martin Reisslein;Frank H. P. Fitzek","doi":"10.1109/COMST.2025.3533303","DOIUrl":"10.1109/COMST.2025.3533303","url":null,"abstract":"Congestion Control (CC) limits the transmission rate of data packets in the transport layer protocol, e.g., in TCP and QUIC, of a sending endpoint so as to mitigate the congestion in packet-switched communication networks. Numerous studies have developed and evaluated Congestion Control Algorithms (CCAs) for a wide range of network types. Prior surveys have covered the functioning of the existing CCAs and their performance characteristics. In contrast, this survey focuses on the quantitative evaluation of CCAs; specifically, we comprehensively survey the CCA evaluation methodologies, i.e., the why and how of CCA evaluations. We define a CCA evaluation as a combination of a prescribed evaluation scenario with prescribed evaluation metrics. In turn, we define an evaluation scenario as a combination of a prescribed network (e.g., path) model and a particular traffic model. We present comprehensive sets of network and traffic model characteristics (i.e., network scenario characteristics) that can influence the performance of CCAs, as well as a comprehensive set of evaluation metrics for measuring the performance of CCAs. We taxonomize CCA evaluations into the main categories: Steady-state, transient-state, network variation, dynamic (e.g., wireless) network, and competition evaluations. We place and survey the existing CCA evaluation studies in this taxonomy to uncover the main trends and shortcomings of the CCA evaluation field to date. To facilitate the comprehensive rigorous evaluation of CCAs, we have developed the publicly available CCA evaluation framework ccperf, which incorporates the insights from our survey. We also outline future research directions to further advance the comprehensive rigorous evaluation of CCAs.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"28 ","pages":"278-340"},"PeriodicalIF":50.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143026750","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":"Advances and Open Challenges in Federated Foundation Models","authors":"Chao Ren;Han Yu;Hongyi Peng;Xiaoli Tang;Bo Zhao;Liping Yi;Alysa Ziying Tan;Yulan Gao;Anran Li;Xiaoxiao Li;Zengxiang Li;Qiang Yang","doi":"10.1109/COMST.2025.3552524","DOIUrl":"10.1109/COMST.2025.3552524","url":null,"abstract":"The integration of Foundation Models (FMs) with Federated Learning (FL) presents a transformative paradigm in Artificial Intelligence (AI). This integration offers enhanced capabilities, while addressing concerns of privacy, data decentralization and computational efficiency. This paper provides a comprehensive survey of the emerging field of Federated Foundation Models (<monospace>FedFM</monospace>), elucidating their synergistic relationship and exploring novel methodologies, challenges, and future directions that the FL research field needs to focus on in order to thrive in the age of FMs. A systematic multi-tiered taxonomy is proposed, categorizing existing <monospace>FedFM</monospace> approaches for model training, aggregation, trustworthiness, and incentivization. Key challenges, including how to enable FL to deal with high complexity of computational demands, privacy considerations, contribution evaluation, and communication efficiency, are thoroughly discussed. Moreover, this paper explores the intricate challenges of communication, scalability and security inherent in training/fine-tuning FMs via FL. It highlights the potential of quantum computing to revolutionize the processes of training, inference, optimization and security. This survey also introduces the implementation requirement of <monospace>FedFM</monospace> and some practical <monospace>FedFM</monospace> applications. It highlights lessons learned with a clear understanding of our findings for <monospace>FedFM</monospace>. Finally, this survey not only provides insights into the current state and challenges of <monospace>FedFM</monospace>, but also offers a blueprint for future research directions, emphasizing the need for developing trustworthy solutions. It serves as a foundational guide for researchers and practitioners interested in contributing to this interdisciplinary and rapidly advancing field.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"28 ","pages":"2087-2126"},"PeriodicalIF":50.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143661505","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":"Industrial Metaverse: Enabling Technologies, Open Problems, and Future Trends","authors":"Shiying Zhang;Jun Li;Long Shi;Ming Ding;Dinh C. Nguyen;Wen Chen;Zhu Han","doi":"10.1109/COMST.2025.3563919","DOIUrl":"10.1109/COMST.2025.3563919","url":null,"abstract":"As an emerging technology that enables seamless integration between the physical and virtual worlds, the Metaverse has great potential to be deployed in the industrial production field with the development of extended reality (XR) and next-generation communication networks. The Industrial Metaverse is used for product design, production operations, quality inspection, and testing. However, there is limited understanding of the enabling technologies associated with it, including the specific industrial scenarios targeted by each technology and the potential migration of technologies from other domains to the industrial sector. This paper provides a comprehensive survey of the latest literature on the Industrial Metaverse. We first analyze its advantages for industrial production, then review key enabling technologies such as blockchain (BC), privacy-preserving computing (PPC), digital twin (DT), fifth/sixth generation mobile communication technology (5G/6G), XR, and artificial intelligence (AI), and explore how these technologies support different aspects of industrial production. We also present major challenges in the Industrial Metaverse, including privacy and security concerns, resource limitations, and interoperability constraints, along with existing solutions. Finally, we outline several open issues and future research directions.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"28 ","pages":"2771-2804"},"PeriodicalIF":50.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143873060","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":"From Nodes to Roads: Surveying DRL Applications in MEC-Enhanced Terrestrial Wireless Networks","authors":"Syed Asad Ullah;Mehwish Bibi;Syed Ali Hassan;Hatem Abou-Zeid;Hassaan Khaliq Qureshi;Haejoon Jung;Aamir Mahmood;Mikael Gidlund;Ekram Hossain","doi":"10.1109/COMST.2025.3568035","DOIUrl":"10.1109/COMST.2025.3568035","url":null,"abstract":"The rapid evolution of mobile communication technologies has propelled mobile edge computing (MEC) as a pivotal paradigm bringing cloud capabilities and storage resources to the network edges, thereby, enabling the execution of computation-intensive, latency-sensitive applications at the network edge, and addressing limited device resources. However, efficient operation in MEC-assisted systems necessitates proper task executions onto MEC servers. Meanwhile, deep reinforcement learning (DRL) can substantially enhance the performance of MEC-enhanced networks by incorporating decision-making capabilities into individual network entities and edge servers. This paper presents a comprehensive survey of the applications of DRL in MEC ecosystems. More specifically, it explores the applications of DRL in MEC-enabled terrestrial wireless networks (TWNs) including Internet-of-Things (IoT) and vehicular networks (VNs). The article provides a comprehensive roadmap for researchers navigating the complexities of intelligent systems and MEC-enabled networks, offering a meticulous understanding of the continuously evolving landscape in this domain. Beginning with foundational DRL principles, the survey scrutinizes the integration of DRL in MEC-enabled TWNs, showcasing its efficacy in optimizing modern TWNs. In the context of MEC-empowered IoT, the paper highlights the role of DRL in enhancing resource allocation, data management, and scalability enhancements. Extending beyond, the paper discusses MEC-enabled VNs, where DRL transforms its role in traffic signal control, and route optimization, ultimately improving efficiency and safety. Additionally, we highlight significant challenges and outline future research directions in applying DRL in TWNs empowered by the MEC paradigm.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"28 ","pages":"1169-1208"},"PeriodicalIF":50.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143930622","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}