IEEE Communications Surveys and Tutorials最新文献

{"title":"Editorial: Fourth Quarter 2024 IEEE Communications Surveys and Tutorials","authors":"Dusit Niyato","doi":"10.1109/COMST.2024.3464708","DOIUrl":"https://doi.org/10.1109/COMST.2024.3464708","url":null,"abstract":"I welcome you to the fourth issue of the IEEE Communications Surveys and Tutorials in 2024. This issue includes 19 papers covering different aspects of communication networks. In particular, these articles survey and tutor various issues in “Wireless Communications”, “Cyber Security”, “IoT and M2M”, “Vehicular and Sensor Communications”, “Internet Technologies”, “Network and Service Management and Green Communications”, “Network Virtualization”, “Optical Communications”, and “Multimedia Communications”. A brief account of each of these papers is given below.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"26 4","pages":"i-vi"},"PeriodicalIF":34.4,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10762798","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142679407","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":"Editorial: Third Quarter 2024 IEEE Communications Surveys and Tutorials","authors":"Dusit Niyato","doi":"10.1109/COMST.2024.3430588","DOIUrl":"https://doi.org/10.1109/COMST.2024.3430588","url":null,"abstract":"I welcome you to the third issue of the IEEE Communications Surveys and Tutorials in 2024. This issue includes 19 papers covering different aspects of communication networks. In particular, these articles survey and tutor various issues in “Wireless Communications”, “Cyber Security”, “Network Virtualization”, “Vehicular and Sensor Communications”, “Multimedia Communications”, “Network and Service Management and Green Communications”, and “Internet Technologies”. A brief account of each of these papers is given below.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"26 3","pages":"i-vii"},"PeriodicalIF":34.4,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10643728","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142041438","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":"Machine Learning in FCAPS: Toward Enhanced Beyond 5G Network Management","authors":"Abdelkader Mekrache;Adlen Ksentini;Christos Verikoukis","doi":"10.1109/COMST.2024.3395414","DOIUrl":"10.1109/COMST.2024.3395414","url":null,"abstract":"The increasing complexity of telecommunication networks has highlighted the need for robust network management frameworks. One such framework is FCAPS, which encompasses a wide range of functionalities, including fault management, configuration management, accounting management, performance management, and security management. To effectively address the complexities of modern networks, the integration of Artificial Intelligence (AI) techniques, particularly Machine Learning (ML) and Machine Reasoning (MR), has emerged as a pivotal strategy within FCAPS. ML provides networks with data-driven algorithms to recognize patterns and make informed predictions, while MR focuses on developing understandable AI systems that draw conclusions based on explicit knowledge. In this paper, we explore the field of MR and its usage within FCAPS. First, we present an overview of the FCAPS framework, including a categorization of FCAPS levels. Then, we provide a novel taxonomy of MR approaches, presenting both traditional and advanced MR. Next, we review MR techniques to address emerging concerns within FCAPS. Finally, we discuss open issues and future directions for further study toward 6G networks.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"26 4","pages":"2769-2797"},"PeriodicalIF":34.4,"publicationDate":"2024-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140817907","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":"RIS-Empowered Satellite-Aerial-Terrestrial Networks With PD-NOMA","authors":"Rui Liu;Kefeng Guo;Xingwang Li;Kapal Dev;Sunder Ali Khowaja;Theodoros A. Tsiftsis;Houbing Song","doi":"10.1109/COMST.2024.3393612","DOIUrl":"10.1109/COMST.2024.3393612","url":null,"abstract":"Satellite-aerial-terrestrial network (SATN) is considered as a promising architecture for sixth-generation (6G) wireless communication networks to achieve seamless coverage, flexible wireless access, and high data rate. Moreover, non-orthogonal multiple access (NOMA), and reconfigurable intelligent surface (RIS) can significantly increase spectrum and energy efficiency. Recently, the integration of these two technologies and SATN has attracted a lot of attention both in academia and industry. This survey provides a comprehensive overview of RIS-empowered SATN with NOMA. In particular, the rudimentary knowledge of SATN, NOMA scheme, and RIS technology is presented. Then, the motivations for investigating the NOMA-RIS-assisted SATN are discussed. In addition, we introduce the three usage modes of RIS, two scenarios of NOMA-RIS, and the path loss model of NOMA-RIS-assisted SATN. Next, the system performance is analyzed for a case study. Besides, a comprehensive overview of resource allocation in NOMA-RIS-assisted SATN is provided, where theoretical and artificial intelligence-based methods are compared and analyzed. Moreover, physical layer security and covert communication are selected as two representative security techniques to be discussed in NOMA-RIS-aided SATN. Furthermore, the combination of other emerging technologies with NOMA-RIS-assisted SATN is investigated. Finally, this survey provides a detailed discussion of the main challenges and open issues that need to be deeply investigated from a practical point of view, including channel modeling, channel estimation, deployment strategies, and backhaul control.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"26 4","pages":"2258-2289"},"PeriodicalIF":34.4,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140648730","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":"End-Edge-Cloud Collaborative Computing for Deep Learning: A Comprehensive Survey","authors":"Yingchao Wang;Chen Yang;Shulin Lan;Liehuang Zhu;Yan Zhang","doi":"10.1109/COMST.2024.3393230","DOIUrl":"10.1109/COMST.2024.3393230","url":null,"abstract":"The booming development of deep learning applications and services heavily relies on large deep learning models and massive data in the cloud. However, cloud-based deep learning encounters challenges in meeting the application requirements of responsiveness, adaptability, and reliability. Edge-based and end-based deep learning enables rapid, near real-time analysis and response, but edge nodes and end devices usually have limited resources to support large models. This necessitates the integration of end, edge, and cloud computing technologies to combine their different advantages. Despite the existence of numerous studies on edge-cloud collaboration, a comprehensive survey for end-edge-cloud computing-enabled deep learning is needed to review the current status and point out future directions. Therefore, this paper: 1) analyzes the collaborative elements within the end-edge-cloud computing system for deep learning, and proposes collaborative training, inference, and updating methods and mechanisms for deep learning models under the end-edge-cloud collaboration framework. 2) provides a systematic investigation of the key enabling technologies for end-edge-cloud collaborative deep learning, including model compression, model partition, and knowledge transfer. 3) highlights six open issues to stimulate continuous research efforts in the field of end-edge-cloud deep learning.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"26 4","pages":"2647-2683"},"PeriodicalIF":34.4,"publicationDate":"2024-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140642243","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 on Mean-Field Game for Dynamic Management and Control in Space-Air-Ground Network","authors":"Yao Wang;Chungang Yang;Tong Li;Xinru Mi;Lixin Li;Zhu Han","doi":"10.1109/COMST.2024.3393369","DOIUrl":"10.1109/COMST.2024.3393369","url":null,"abstract":"The data traffic volume of the 6th generation (6G) mobile communication networks is huge, and there are novel challenges in various communications services and scenarios. This calls for ultra-dense and heterogeneous deployments of network nodes both on the ground and in space, resulting in ultra-dense space-air-ground network. However, conventional models are not available to analyze and design the interactions among heterogeneous network nodes. Game theory can provide an effective mathematical modeling framework for analysis and design. For the 6G space-air-ground networks, the characteristics of stochastic, ultra-dense, and distributed control will cause conventional game theoretical approaches to confront the challenge of the curse of dimensionality. Mean-field game (MFG) can be introduced to decouple dynamic management and control among agents, to decouple their interactions in a high-dimensional regime. Although the MFG finds wide application, there lacks a comprehensive survey to clarify the basics and summarize the state of the art of MFG research status. In this survey, we investigate and provide an overview of the applications of the MFG. First, we discuss diverse 6G space-air-ground networking paradigms, and then introduce the basic concepts of the MFG. Second, various MFG-based optimal control policies together with mean-field equilibrium (MFE) solutions are investigated and surveyed. Moreover, we discuss the effectiveness of combining the MFG with other game-theoretic approaches and machine learning methods, which leads to the improvement of multi-agent system performances. Finally, we outline some open issues, technical challenges, and future research directions based on the current state of the art.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"26 4","pages":"2798-2835"},"PeriodicalIF":34.4,"publicationDate":"2024-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140642142","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":"The Metaverse: Survey, Trends, Novel Pipeline Ecosystem & Future Directions","authors":"H. Sami;A. Hammoud;M. Arafeh;M. Wazzeh;S. Arisdakessian;M. Chahoud;O. Wehbi;M. Ajaj;A. Mourad;H. Otrok;O. Abdel Wahab;R. Mizouni;J. Bentahar;C. Talhi;Z. Dziong;E. Damiani;M. Guizani","doi":"10.1109/COMST.2024.3392642","DOIUrl":"10.1109/COMST.2024.3392642","url":null,"abstract":"The Metaverse offers a second world beyond reality, where boundaries are non-existent, and possibilities are endless through engagement and immersive experiences using the virtual reality (VR) technology. Many disciplines can benefit from the advancement of the Metaverse when accurately developed, including the fields of technology, gaming, education, art & culture, socialization, commerce, and businesses. Nevertheless, developing the Metaverse environment to its full potential is an ambiguous task that needs proper guidance and directions. Existing surveys on the Metaverse focus only on a specific aspect and discipline of the Metaverse and lack a holistic view of the entire process. Moreover, most surveys refrain from providing detailed guidance about the development process of the metaverse, including its impact on technologies, businesses, existing challenges, and potential research directions due to their lack of a macro and micro perception of such a topic. To this end, a more holistic, multi-disciplinary, in-depth, and academic and industry-oriented review is required to provide a thorough study of the Metaverse development pipeline and fill the gap in existing Metaverse surveys. To address these issues, we present in this survey a novel multi-layered pipeline ecosystem composed of (1) the Metaverse computing, networking, communications and hardware infrastructure, (2) environment digitization, and (3) user interactions. For every layer, we discuss the components that detail the steps of its development. Also, for each of these components, we examine the impact of a set of enabling technologies and empowering domains (e.g., Artificial Intelligence, Security & Privacy, Blockchain, Business, Ethics, and Social) on its advancement. In addition, we explain the importance of these technologies to support decentralization, interoperability, user experiences, interactions, and monetization. Our presented study highlights the existing challenges for each component, followed by research directions and potential solutions. To the best of our knowledge, this survey is the most comprehensive and allows users, scholars, and entrepreneurs to get an in-depth understanding of the Metaverse ecosystem to find their opportunities and potentials for contribution.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"26 4","pages":"2914-2960"},"PeriodicalIF":34.4,"publicationDate":"2024-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140639926","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":"Resource Management From Single-Domain 5G to End-to-End 6G Network Slicing: A Survey","authors":"Sina Ebrahimi;Faouzi Bouali;Olivier C. L. Haas","doi":"10.1109/COMST.2024.3390613","DOIUrl":"10.1109/COMST.2024.3390613","url":null,"abstract":"Network Slicing (NS) is one of the pillars of the fifth/sixth generation (5G/6G) of mobile networks. It provides the means for Mobile Network Operators (MNOs) to leverage physical infrastructure across different technological domains to support different applications. This survey analyzes the progress made on NS resource management across these domains, with a focus on the interdependence between domains and unique issues that arise in cross-domain and End-to-End (E2E) settings. Based on a generic problem formulation, NS resource management functionalities (e.g., resource allocation and orchestration) are examined across domains, revealing their limits when applied separately per domain. The appropriateness of different problem-solving methodologies is critically analyzed, and practical insights are provided, explaining how resource management should be rethought in cross-domain and E2E contexts. Furthermore, the latest advancements are reported through a detailed analysis of the most relevant research projects and experimental testbeds. Finally, the core issues facing NS resource management are dissected, and the most pertinent research directions are identified, providing practical guidelines for new researchers.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"26 4","pages":"2836-2866"},"PeriodicalIF":34.4,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140607616","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":"Design Guidelines on Trust Management for Underwater Wireless Sensor Networks","authors":"Rongxin Zhu;Azzedine Boukerche;Libo Long;Qiuling Yang","doi":"10.1109/COMST.2024.3389728","DOIUrl":"10.1109/COMST.2024.3389728","url":null,"abstract":"In recent years, significant advancements in wireless underwater communication and acoustic sensor technology have spurred the exploration and utilization of the ocean’s vast natural resources. underwater wireless sensor networks (UWSNs) are increasingly deployed in unattended and hostile environments, demanding robust security measures. Secure communication environments are essential for a range of UWSN applications, including coastal defense, underwater communication, and marine exploration. Trust models have emerged as effective security mechanisms to assess the reliability of individual nodes in UWSNs during adverse attacks. Unlike Wireless Sensor Networks (WSNs), UWSNs encounter distinct challenges, including constrained resources, harsh underwater conditions, and unreliable acoustic communication, making it crucial to establish a reliable trust-based system. In this paper, we review existing work on UWSN security, discuss security and trust challenges, and explore trust-based applications. Furthermore, we evaluate diverse trust models suited for UWSNs of recent years, categorizing and comparing approaches like weighted sum methods, logic-based techniques, probability and statistics models, and machine learning paradigms. Finally, we discuss contemporary challenges and future directions in UWSN trust management. By offering a systematic overview and classification of trust management approaches, this paper contributes to the understanding and development of effective trust mechanisms for UWSNs, ultimately enhancing their reliability, security, and successful operation in diverse marine applications.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"26 4","pages":"2547-2576"},"PeriodicalIF":34.4,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140603938","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":"Evolution of RAN Architectures Toward 6G: Motivation, Development, and Enabling Technologies","authors":"Jiacheng Chen;Xiaohu Liang;Jianzhe Xue;Yu Sun;Haibo Zhou;Xuemin Shen","doi":"10.1109/COMST.2024.3388511","DOIUrl":"10.1109/COMST.2024.3388511","url":null,"abstract":"In this survey paper, we first provide insights on the evolution of radio access networks (RANs) through investigating the existing paradigms and future trends towards 6G. We then present the fully-decoupled RAN (FD-RAN), which aligns with the trends by integrating existing paradigms and introducing new features such as physical decoupling of uplink and downlink base stations. We also discuss the key technologies enabled by different architectures for further performance improvement and some open issues. We hope that this survey can stimulate more in-depth research on transforming 6G RAN so as to unleash the power of state-of-the-art technologies and meet higher performance requirements in the future.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"26 3","pages":"1950-1988"},"PeriodicalIF":34.4,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140556972","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}