Pub Date : 2024-06-03DOI: 10.1109/COMST.2024.3408090
Abdulhalim Fayad;Tibor Cinkler;Jacek Rak
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.
{"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}
Pub Date : 2024-06-03DOI: 10.1109/COMST.2024.3408277
Sara Salim;Nour Moustafa;Martin Reisslein
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.
{"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}
With recent advancements, the wireless local area network (WLAN) or wireless fidelity (Wi-Fi) technology has been successfully utilized to realize sensing functionalities such as detection, localization, and recognition. However, the WLANs standards are developed mainly for the purpose of communication, and thus may not be able to meet the stringent requirements for emerging sensing applications. To resolve this issue, a new Task Group (TG), namely IEEE 802.11bf, has been established by the IEEE 802.11 working group, with the objective of creating a new amendment to the WLAN standard to meet advanced sensing requirements while minimizing the effect on communications. This paper provides a comprehensive overview on the up-to-date efforts in the IEEE 802.11bf TG. First, we introduce the definition of the 802.11bf amendment as well as its formation and standardization timeline. Next, we discuss the WLAN sensing use cases with the corresponding key performance indicator (KPI) requirements. After reviewing previous WLAN sensing research based on communication-oriented WLAN standards, we identify their limitations and underscore the practical need for the new sensing-oriented amendment in 802.11bf. Furthermore, we discuss the WLAN sensing framework and procedure used for measurement acquisition, by considering both sensing at sub-7GHz and directional multi-gigabit (DMG) sensing at 60 GHz, respectively, and address their shared features, similarities, and differences. In addition, we present various candidate technical features for IEEE 802.11bf, including waveform/sequence design, feedback types, as well as quantization and compression techniques. We also describe the methodologies and the channel modeling used by the IEEE 802.11bf TG to evaluate the alternative performance. Finally, we discuss the challenges and future research directions to motivate more research endeavors towards this field in detail.
{"title":"An Overview on IEEE 802.11bf: WLAN Sensing","authors":"Rui Du;Haocheng Hua;Hailiang Xie;Xianxin Song;Zhonghao Lyu;Mengshi Hu;Narengerile;Yan Xin;Stephen McCann;Michael Montemurro;Tony Xiao Han;Jie Xu","doi":"10.1109/COMST.2024.3408899","DOIUrl":"https://doi.org/10.1109/COMST.2024.3408899","url":null,"abstract":"With recent advancements, the wireless local area network (WLAN) or wireless fidelity (Wi-Fi) technology has been successfully utilized to realize sensing functionalities such as detection, localization, and recognition. However, the WLANs standards are developed mainly for the purpose of communication, and thus may not be able to meet the stringent requirements for emerging sensing applications. To resolve this issue, a new Task Group (TG), namely IEEE 802.11bf, has been established by the IEEE 802.11 working group, with the objective of creating a new amendment to the WLAN standard to meet advanced sensing requirements while minimizing the effect on communications. This paper provides a comprehensive overview on the up-to-date efforts in the IEEE 802.11bf TG. First, we introduce the definition of the 802.11bf amendment as well as its formation and standardization timeline. Next, we discuss the WLAN sensing use cases with the corresponding key performance indicator (KPI) requirements. After reviewing previous WLAN sensing research based on communication-oriented WLAN standards, we identify their limitations and underscore the practical need for the new sensing-oriented amendment in 802.11bf. Furthermore, we discuss the WLAN sensing framework and procedure used for measurement acquisition, by considering both sensing at sub-7GHz and directional multi-gigabit (DMG) sensing at 60 GHz, respectively, and address their shared features, similarities, and differences. In addition, we present various candidate technical features for IEEE 802.11bf, including waveform/sequence design, feedback types, as well as quantization and compression techniques. We also describe the methodologies and the channel modeling used by the IEEE 802.11bf TG to evaluate the alternative performance. Finally, we discuss the challenges and future research directions to motivate more research endeavors towards this field in detail.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"27 1","pages":"184-217"},"PeriodicalIF":34.4,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143422793","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}
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.
{"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}
Pub Date : 2024-04-25DOI: 10.1109/COMST.2024.3393612
Rui Liu;Kefeng Guo;Xingwang Li;Kapal Dev;Sunder Ali Khowaja;Theodoros A. Tsiftsis;Houbing Song
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.
{"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}
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.
{"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}
Pub Date : 2024-04-24DOI: 10.1109/COMST.2024.3393369
Yao Wang;Chungang Yang;Tong Li;Xinru Mi;Lixin Li;Zhu Han
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.
{"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}
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.
{"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}
Pub Date : 2024-04-22DOI: 10.1109/COMST.2024.3392253
Zhiyi Zhang;Guorui Xiao;Sichen Song;R. Can Aygun;Angelos Stavrou;Lixia Zhang;Eric Osterweil
Distributed Denial of Service (DDoS) attacks have plagued the Internet for decades. Despite the ever-increasing investments into mitigation solution development, DDoS attacks continue to grow with ever-increasing frequency and magnitude. To identify the root cause of the above-observed trend, in this paper, we conduct a systematic and architectural evaluation of volumetric DDoS detection and mitigation efforts over 24,000 papers, articles, and RFCs over 30+ years. To that end, we introduce a novel approach for systematizing comparisons of DDoS research, resulting in a comprehensive examination of the DDoS literature. Our analysis illustrates a small set of common design patterns across seemingly disparate solutions, and reveals insights into deployment traction and success of DDoS solutions. Furthermore, we discuss economic incentives and the lack of harmony between synergistic but independent approaches for detection and mitigation. As expected, defenses with a clear cost/benefit rationale are more prevalent than those that require extensive infrastructure changes. Finally, we discuss the lessons learned which we hope can shed light on future directions that can potentially turn the tide of the war against DDoS.
{"title":"Revealing Protocol Architecture’s Design Patterns in the Volumetric DDoS Defense Design Space","authors":"Zhiyi Zhang;Guorui Xiao;Sichen Song;R. Can Aygun;Angelos Stavrou;Lixia Zhang;Eric Osterweil","doi":"10.1109/COMST.2024.3392253","DOIUrl":"10.1109/COMST.2024.3392253","url":null,"abstract":"Distributed Denial of Service (DDoS) attacks have plagued the Internet for decades. Despite the ever-increasing investments into mitigation solution development, DDoS attacks continue to grow with ever-increasing frequency and magnitude. To identify the root cause of the above-observed trend, in this paper, we conduct a systematic and architectural evaluation of volumetric DDoS detection and mitigation efforts over 24,000 papers, articles, and RFCs over 30+ years. To that end, we introduce a novel approach for systematizing comparisons of DDoS research, resulting in a comprehensive examination of the DDoS literature. Our analysis illustrates a small set of common design patterns across seemingly disparate solutions, and reveals insights into deployment traction and success of DDoS solutions. Furthermore, we discuss economic incentives and the lack of harmony between synergistic but independent approaches for detection and mitigation. As expected, defenses with a clear cost/benefit rationale are more prevalent than those that require extensive infrastructure changes. Finally, we discuss the lessons learned which we hope can shed light on future directions that can potentially turn the tide of the war against DDoS.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"27 1","pages":"353-371"},"PeriodicalIF":34.4,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140634301","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}
Pub Date : 2024-04-17DOI: 10.1109/COMST.2024.3390613
Sina Ebrahimi;Faouzi Bouali;Olivier C. L. Haas
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.
{"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}
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