Pub Date : 2024-01-17DOI: 10.1109/COMST.2024.3355168
André Cirne;Patrícia R. Sousa;João S. Resende;Luís Antunes
With the proliferation of Internet of Things (IoT) devices, there is an increasing need to prioritize their security, especially in the context of identity and authentication mechanisms. However, IoT devices have unique limitations in terms of computational capabilities and susceptibility to hardware attacks, which pose significant challenges to establishing strong identity and authentication systems. Paradoxically, the very hardware constraints responsible for these challenges can also offer potential solutions. By incorporating hardware-based identity implementations, it is possible to overcome computational and energy limitations, while bolstering resistance against both hardware and software attacks. This research addresses these challenges by investigating the vulnerabilities and obstacles faced by identity and authentication systems in the IoT context, while also exploring potential technologies to address these issues. Each identified technology underwent meticulous investigation, considering known security attacks, implemented countermeasures, and an assessment of their pros and cons. Furthermore, an extensive literature survey was conducted to identify instances where these technologies have effectively supported device identity. The research also includes a demonstration that evaluates the effectiveness of hardware trust anchors in mitigating various attacks on IoT identity. This empirical evaluation provides valuable insights into the challenges developers encounter when implementing hardware-based identity solutions. Moreover, it underscores the substantial value of these solutions in terms of mitigating attacks and developing robust identity frameworks. By thoroughly examining vulnerabilities, exploring technologies, and conducting empirical evaluations, this research contributes to understanding and promoting the adoption of hardware-based identity and authentication systems in secure IoT environments. The findings emphasize the challenges faced by developers and highlight the significance of hardware trust anchors in enhancing security and facilitating effective identity solutions.
{"title":"Hardware Security for Internet of Things Identity Assurance","authors":"André Cirne;Patrícia R. Sousa;João S. Resende;Luís Antunes","doi":"10.1109/COMST.2024.3355168","DOIUrl":"10.1109/COMST.2024.3355168","url":null,"abstract":"With the proliferation of Internet of Things (IoT) devices, there is an increasing need to prioritize their security, especially in the context of identity and authentication mechanisms. However, IoT devices have unique limitations in terms of computational capabilities and susceptibility to hardware attacks, which pose significant challenges to establishing strong identity and authentication systems. Paradoxically, the very hardware constraints responsible for these challenges can also offer potential solutions. By incorporating hardware-based identity implementations, it is possible to overcome computational and energy limitations, while bolstering resistance against both hardware and software attacks. This research addresses these challenges by investigating the vulnerabilities and obstacles faced by identity and authentication systems in the IoT context, while also exploring potential technologies to address these issues. Each identified technology underwent meticulous investigation, considering known security attacks, implemented countermeasures, and an assessment of their pros and cons. Furthermore, an extensive literature survey was conducted to identify instances where these technologies have effectively supported device identity. The research also includes a demonstration that evaluates the effectiveness of hardware trust anchors in mitigating various attacks on IoT identity. This empirical evaluation provides valuable insights into the challenges developers encounter when implementing hardware-based identity solutions. Moreover, it underscores the substantial value of these solutions in terms of mitigating attacks and developing robust identity frameworks. By thoroughly examining vulnerabilities, exploring technologies, and conducting empirical evaluations, this research contributes to understanding and promoting the adoption of hardware-based identity and authentication systems in secure IoT environments. The findings emphasize the challenges faced by developers and highlight the significance of hardware trust anchors in enhancing security and facilitating effective identity solutions.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":null,"pages":null},"PeriodicalIF":35.6,"publicationDate":"2024-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139953599","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 : 2024-01-17DOI: 10.1109/COMST.2024.3355222
Hadi Gharavi;Jorge Granjal;Edmundo Monteiro
Blockchain is becoming increasingly popular in the business and academic communities because it can provide security for a wide range of applications. Therefore, researchers have been motivated to exploit blockchain characteristics, such as data immutability, transparency, and resistance to single-point failures in the Internet of Things (IoT), to increase the security of the IoT ecosystem. However, many existing blockchains rely on classical cryptosystems such as the Elliptic Curve Digital Signature Algorithm (ECDSA) and SHA-256 to validate transactions, which will be compromised by Shor and Grover’s algorithms running on quantum computers in the foreseeable future. Post-Quantum Cryptosystems (PQC) are an innovative solution for resisting quantum attacks that can be applied to blockchains, resulting in the creation of a new type of blockchain known as Post-Quantum Blockchains (PQB). In this survey, we will look at the different types of PQC and their recent standard primitives to determine whether they can enable security for blockchain-based IoT applications. It also briefly introduces blockchain and outlines recent blockchain-IoT application proposals. To the best of our knowledge, this is the first study to examine how post-quantum blockchains are being developed and how they can be used to create security mechanisms for different IoT applications. Finally, this study explores the main challenges and potential research directions that arise from integrating quantum-resistance blockchains into IoT ecosystems.
{"title":"Post-Quantum Blockchain Security for the Internet of Things: Survey and Research Directions","authors":"Hadi Gharavi;Jorge Granjal;Edmundo Monteiro","doi":"10.1109/COMST.2024.3355222","DOIUrl":"10.1109/COMST.2024.3355222","url":null,"abstract":"Blockchain is becoming increasingly popular in the business and academic communities because it can provide security for a wide range of applications. Therefore, researchers have been motivated to exploit blockchain characteristics, such as data immutability, transparency, and resistance to single-point failures in the Internet of Things (IoT), to increase the security of the IoT ecosystem. However, many existing blockchains rely on classical cryptosystems such as the Elliptic Curve Digital Signature Algorithm (ECDSA) and SHA-256 to validate transactions, which will be compromised by Shor and Grover’s algorithms running on quantum computers in the foreseeable future. Post-Quantum Cryptosystems (PQC) are an innovative solution for resisting quantum attacks that can be applied to blockchains, resulting in the creation of a new type of blockchain known as Post-Quantum Blockchains (PQB). In this survey, we will look at the different types of PQC and their recent standard primitives to determine whether they can enable security for blockchain-based IoT applications. It also briefly introduces blockchain and outlines recent blockchain-IoT application proposals. To the best of our knowledge, this is the first study to examine how post-quantum blockchains are being developed and how they can be used to create security mechanisms for different IoT applications. Finally, this study explores the main challenges and potential research directions that arise from integrating quantum-resistance blockchains into IoT ecosystems.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":null,"pages":null},"PeriodicalIF":34.4,"publicationDate":"2024-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139953601","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 : 2024-01-16DOI: 10.1109/COMST.2024.3352910
Joohyung Lee;Faranaksadat Solat;Tae Yeon Kim;H. Vincent Poor
The fifth generation (5G) and beyond wireless networks are envisioned to provide an integrated communication and computing platform that will enable multipurpose and intelligent networks driven by a growing demand for both traditional end users and industry verticals. This evolution will be realized by innovations in both core and access capabilities, mainly from virtualization technologies and ultra-dense networks, e.g., software-defined networking (SDN), network slicing, network function virtualization (NFV), multi-access edge computing (MEC), terahertz (THz) communications, etc. However, those technologies require increased complexity of resource management and large configurations of network slices. In this new milieu, with the help of artificial intelligence (AI), network operators will strive to enable AI-empowered network management by automating radio and computing resource management and orchestration processes in a data-driven manner. In this regard, most of the previous AI-empowered network management approaches adopt a traditional centralized training paradigm where diverse training data generated at network functions over distributed base stations associated with MEC servers are transferred to a central training server. On the other hand, to exploit distributed and parallel processing capabilities of distributed network entities in a fast and secure manner, federated learning (FL) has emerged as a distributed AI approach that can enable many AI-empowered network management approaches by allowing for AI training at distributed network entities without the need for data transmission to a centralized server. This article comprehensively surveys the field of FL-empowered mobile network management for 5G and beyond networks from access to the core. Specifically, we begin with an introduction to the state-of-the-art of FL by exploring and analyzing recent advances in FL in general. Then, we provide an extensive survey of AI-empowered network management, including background on 5G network functions, mobile traffic prediction, and core/access network management regarding standardization and research activities. We then present an extensive survey of FL-empowered network management by highlighting how FL is adopted in AI-empowered network management. Important lessons learned from this review of AI and FL-empowered network management are also provided. Finally, we complement this survey by discussing open issues and possible directions for future research in this important emerging area.
{"title":"Federated Learning-Empowered Mobile Network Management for 5G and Beyond Networks: From Access to Core","authors":"Joohyung Lee;Faranaksadat Solat;Tae Yeon Kim;H. Vincent Poor","doi":"10.1109/COMST.2024.3352910","DOIUrl":"10.1109/COMST.2024.3352910","url":null,"abstract":"The fifth generation (5G) and beyond wireless networks are envisioned to provide an integrated communication and computing platform that will enable multipurpose and intelligent networks driven by a growing demand for both traditional end users and industry verticals. This evolution will be realized by innovations in both core and access capabilities, mainly from virtualization technologies and ultra-dense networks, e.g., software-defined networking (SDN), network slicing, network function virtualization (NFV), multi-access edge computing (MEC), terahertz (THz) communications, etc. However, those technologies require increased complexity of resource management and large configurations of network slices. In this new milieu, with the help of artificial intelligence (AI), network operators will strive to enable AI-empowered network management by automating radio and computing resource management and orchestration processes in a data-driven manner. In this regard, most of the previous AI-empowered network management approaches adopt a traditional centralized training paradigm where diverse training data generated at network functions over distributed base stations associated with MEC servers are transferred to a central training server. On the other hand, to exploit distributed and parallel processing capabilities of distributed network entities in a fast and secure manner, federated learning (FL) has emerged as a distributed AI approach that can enable many AI-empowered network management approaches by allowing for AI training at distributed network entities without the need for data transmission to a centralized server. This article comprehensively surveys the field of FL-empowered mobile network management for 5G and beyond networks from access to the core. Specifically, we begin with an introduction to the state-of-the-art of FL by exploring and analyzing recent advances in FL in general. Then, we provide an extensive survey of AI-empowered network management, including background on 5G network functions, mobile traffic prediction, and core/access network management regarding standardization and research activities. We then present an extensive survey of FL-empowered network management by highlighting how FL is adopted in AI-empowered network management. Important lessons learned from this review of AI and FL-empowered network management are also provided. Finally, we complement this survey by discussing open issues and possible directions for future research in this important emerging area.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":null,"pages":null},"PeriodicalIF":34.4,"publicationDate":"2024-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139947841","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 : 2024-01-12DOI: 10.1109/COMST.2024.3353265
Minrui Xu;Hongyang Du;Dusit Niyato;Jiawen Kang;Zehui Xiong;Shiwen Mao;Zhu Han;Abbas Jamalipour;Dong In Kim;Xuemin Shen;Victor C. M. Leung;H. Vincent Poor
Artificial Intelligence-Generated Content (AIGC) is an automated method for generating, manipulating, and modifying valuable and diverse data using AI algorithms creatively. This survey paper focuses on the deployment of AIGC applications, e.g., ChatGPT and Dall-E, at mobile edge networks, namely mobile AIGC networks, that provide personalized and customized AIGC services in real time while maintaining user privacy. We begin by introducing the background and fundamentals of generative models and the lifecycle of AIGC services at mobile AIGC networks, which includes data collection, training, fine-tuning, inference, and product management. We then discuss the collaborative cloud-edge-mobile infrastructure and technologies required to support AIGC services and enable users to access AIGC at mobile edge networks. Furthermore, we explore AIGC-driven creative applications and use cases for mobile AIGC networks. Additionally, we discuss the implementation, security, and privacy challenges of deploying mobile AIGC networks. Finally, we highlight some future research directions and open issues for the full realization of mobile AIGC networks.
{"title":"Unleashing the Power of Edge-Cloud Generative AI in Mobile Networks: A Survey of AIGC Services","authors":"Minrui Xu;Hongyang Du;Dusit Niyato;Jiawen Kang;Zehui Xiong;Shiwen Mao;Zhu Han;Abbas Jamalipour;Dong In Kim;Xuemin Shen;Victor C. M. Leung;H. Vincent Poor","doi":"10.1109/COMST.2024.3353265","DOIUrl":"10.1109/COMST.2024.3353265","url":null,"abstract":"Artificial Intelligence-Generated Content (AIGC) is an automated method for generating, manipulating, and modifying valuable and diverse data using AI algorithms creatively. This survey paper focuses on the deployment of AIGC applications, e.g., ChatGPT and Dall-E, at mobile edge networks, namely mobile AIGC networks, that provide personalized and customized AIGC services in real time while maintaining user privacy. We begin by introducing the background and fundamentals of generative models and the lifecycle of AIGC services at mobile AIGC networks, which includes data collection, training, fine-tuning, inference, and product management. We then discuss the collaborative cloud-edge-mobile infrastructure and technologies required to support AIGC services and enable users to access AIGC at mobile edge networks. Furthermore, we explore AIGC-driven creative applications and use cases for mobile AIGC networks. Additionally, we discuss the implementation, security, and privacy challenges of deploying mobile AIGC networks. Finally, we highlight some future research directions and open issues for the full realization of mobile AIGC networks.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":null,"pages":null},"PeriodicalIF":35.6,"publicationDate":"2024-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139947827","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 importance of safeguarding individuals’ privacy rights in online activities is unmistakable in today’s anonymity networks. Since the introduction of Mixnet by Chaum, numerous anonymity networks with different objectives and design principles have emerged, providing a diverse range of applications for privacy-conscious users. However, security issues in anonymity networks have persistently existed and continue to impact their survival and development. Each anonymity network presents distinct security challenges, making it more challenging for researchers to achieve a comprehensive and systematic understanding of their security. The current literature exhibits some unavoidable gaps, including the lack of vulnerability perspectives, a unified understanding of diverse attack types, defense perspectives, and theoretical perspectives. To address these gaps, we investigate prevailing attacks targeting anonymity networks from the viewpoint of network designers and operators. We use Tor, I2P, and Freenet (arguably the three most popular anonymity networks) as case studies. Starting with these attacks, we conduct an in-depth analysis of the vulnerabilities underlying them and explore related defense mechanisms and formal security. Specifically, we classify vulnerabilities into external and internal categories, utilizing the protocol stack of an anonymity network to guide the categorization of internal vulnerabilities. Furthermore, we examine their root causes. In addition to these aspects, we emphasize the importance of formal security in researching the security of anonymity networks by integrating the investigated vulnerabilities, attacks, and defenses. Through this comprehensive, thorough, and unified approach, this paper aims to provide insights into the security of anonymity networks and offer general research findings. Finally, we discuss ongoing challenges and future directions in this specific area.
{"title":"A Systematic Survey on Security in Anonymity Networks: Vulnerabilities, Attacks, Defenses, and Formalization","authors":"Daichong Chao;Dawei Xu;Feng Gao;Chuan Zhang;Weiting Zhang;Liehuang Zhu","doi":"10.1109/COMST.2024.3350006","DOIUrl":"10.1109/COMST.2024.3350006","url":null,"abstract":"The importance of safeguarding individuals’ privacy rights in online activities is unmistakable in today’s anonymity networks. Since the introduction of Mixnet by Chaum, numerous anonymity networks with different objectives and design principles have emerged, providing a diverse range of applications for privacy-conscious users. However, security issues in anonymity networks have persistently existed and continue to impact their survival and development. Each anonymity network presents distinct security challenges, making it more challenging for researchers to achieve a comprehensive and systematic understanding of their security. The current literature exhibits some unavoidable gaps, including the lack of vulnerability perspectives, a unified understanding of diverse attack types, defense perspectives, and theoretical perspectives. To address these gaps, we investigate prevailing attacks targeting anonymity networks from the viewpoint of network designers and operators. We use Tor, I2P, and Freenet (arguably the three most popular anonymity networks) as case studies. Starting with these attacks, we conduct an in-depth analysis of the vulnerabilities underlying them and explore related defense mechanisms and formal security. Specifically, we classify vulnerabilities into external and internal categories, utilizing the protocol stack of an anonymity network to guide the categorization of internal vulnerabilities. Furthermore, we examine their root causes. In addition to these aspects, we emphasize the importance of formal security in researching the security of anonymity networks by integrating the investigated vulnerabilities, attacks, and defenses. Through this comprehensive, thorough, and unified approach, this paper aims to provide insights into the security of anonymity networks and offer general research findings. Finally, we discuss ongoing challenges and future directions in this specific area.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":null,"pages":null},"PeriodicalIF":34.4,"publicationDate":"2024-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139947840","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 : 2024-01-02DOI: 10.1109/COMST.2023.3349276
Zhe Wang;Jiayi Zhang;Hongyang Du;Dusit Niyato;Shuguang Cui;Bo Ai;Mérouane Debbah;Khaled B. Letaief;H. Vincent Poor
Extremely large-scale multiple-input-multiple-output (XL-MIMO), which offers vast spatial degrees of freedom, has emerged as a potentially pivotal enabling technology for the sixth generation (6G) of wireless mobile networks. With its growing significance, both opportunities and challenges are concurrently manifesting. This paper presents a comprehensive survey of research on XL-MIMO wireless systems. In particular, we introduce four XL-MIMO hardware architectures: uniform linear array (ULA)-based XL-MIMO, uniform planar array (UPA)-based XL-MIMO utilizing either patch antennas or point antennas, and continuous aperture (CAP)-based XL-MIMO. We comprehensively analyze and discuss their characteristics and interrelationships. Following this, we introduce several electromagnetic characteristics and general distance boundaries in XL-MIMO. Given the distinct electromagnetic properties of near-field communications, we present a range of channel models to demonstrate the benefits of XL-MIMO. We further discuss and summarize signal processing schemes for XL-MIMO. It is worth noting that the low-complexity signal processing schemes and deep learning empowered signal processing schemes are reviewed and highlighted to promote the practical implementation of XL-MIMO. Furthermore, we explore the interplay between XL-MIMO and other emergent 6G technologies. Finally, we outline several compelling research directions for future XL-MIMO wireless communication systems.
{"title":"A Tutorial on Extremely Large-Scale MIMO for 6G: Fundamentals, Signal Processing, and Applications","authors":"Zhe Wang;Jiayi Zhang;Hongyang Du;Dusit Niyato;Shuguang Cui;Bo Ai;Mérouane Debbah;Khaled B. Letaief;H. Vincent Poor","doi":"10.1109/COMST.2023.3349276","DOIUrl":"10.1109/COMST.2023.3349276","url":null,"abstract":"Extremely large-scale multiple-input-multiple-output (XL-MIMO), which offers vast spatial degrees of freedom, has emerged as a potentially pivotal enabling technology for the sixth generation (6G) of wireless mobile networks. With its growing significance, both opportunities and challenges are concurrently manifesting. This paper presents a comprehensive survey of research on XL-MIMO wireless systems. In particular, we introduce four XL-MIMO hardware architectures: uniform linear array (ULA)-based XL-MIMO, uniform planar array (UPA)-based XL-MIMO utilizing either patch antennas or point antennas, and continuous aperture (CAP)-based XL-MIMO. We comprehensively analyze and discuss their characteristics and interrelationships. Following this, we introduce several electromagnetic characteristics and general distance boundaries in XL-MIMO. Given the distinct electromagnetic properties of near-field communications, we present a range of channel models to demonstrate the benefits of XL-MIMO. We further discuss and summarize signal processing schemes for XL-MIMO. It is worth noting that the low-complexity signal processing schemes and deep learning empowered signal processing schemes are reviewed and highlighted to promote the practical implementation of XL-MIMO. Furthermore, we explore the interplay between XL-MIMO and other emergent 6G technologies. Finally, we outline several compelling research directions for future XL-MIMO wireless communication systems.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":null,"pages":null},"PeriodicalIF":34.4,"publicationDate":"2024-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139947839","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}
Building complex entities like Network Slices and their Subnets requires proper models and methods to allow their convenient design and deployment. Despite significant progress in the standardization of the basic Network Slicing concepts, for many it still remains unclear how to organize a Network Slice/Subnet design process that would be aligned to the currently standardized, declarative style of their provisioning. How to reflect the high-level, abstract service requirements into a technical description of a Network Slice/Subnet capable of fulfilling them? In what form should such a description be provided? What details should it cover and how to conduct a design process leading to the production of a concretized description of the desired Network Slice Instance (NSI) and/or Network Slice Subnet Instance (NSSI)? Unfortunately, the current standardization scope does not cover these challenging design-time aspects, leaving the telco community without clear guidelines in this complicated area. Also, the state-of-the-art research does not tackle the corresponding challenges in a generic and holistic way. We contribute to fill in this void by complementing the up-to-date standards with original concepts and systematizations compiled into a comprehensive tutorial on the Network Slicing design-time aspects. To this end, we deliver a broad study of the evolution of Network Slice/Subnet provisioning approaches and offering modes, explaining their impact on the design phase. Next, we provide a generic taxonomy of building blocks out of which an NSI/NSSI may be designed, followed by proposing precise definitions of the design process and its expected outcomes. Then, by elaborating on those definitions, we explain, in a technology-agnostic manner, the activities comprising the design process and the results it shall produce. Based on these fundamentals, we describe the opportunities for automating the design process, essential to support the declarative provisioning style and to offer the “dynamic slicing” capabilities by the Slicing orchestrators. All of the elaborated systematizations and concepts are vendor-agnostic and fully standards-aligned which makes them practically usable in a wide range of solutions.
{"title":"Comprehensive Tutorial on the Organization of a Standards-Aligned Network Slice/Subnet Design Process and Opportunities for Its Automation","authors":"Przemysław Wyszkowski;Jan Kienig;Krzysztof Zieliński;Łukasz Czekierda;Mateusz Zawadzki","doi":"10.1109/COMST.2023.3341249","DOIUrl":"https://doi.org/10.1109/COMST.2023.3341249","url":null,"abstract":"Building complex entities like Network Slices and their Subnets requires proper models and methods to allow their convenient design and deployment. Despite significant progress in the standardization of the basic Network Slicing concepts, for many it still remains unclear how to organize a Network Slice/Subnet design process that would be aligned to the currently standardized, declarative style of their provisioning. How to reflect the high-level, abstract service requirements into a technical description of a Network Slice/Subnet capable of fulfilling them? In what form should such a description be provided? What details should it cover and how to conduct a design process leading to the production of a concretized description of the desired Network Slice Instance (NSI) and/or Network Slice Subnet Instance (NSSI)? Unfortunately, the current standardization scope does not cover these challenging design-time aspects, leaving the telco community without clear guidelines in this complicated area. Also, the state-of-the-art research does not tackle the corresponding challenges in a generic and holistic way. We contribute to fill in this void by complementing the up-to-date standards with original concepts and systematizations compiled into a comprehensive tutorial on the Network Slicing design-time aspects. To this end, we deliver a broad study of the evolution of Network Slice/Subnet provisioning approaches and offering modes, explaining their impact on the design phase. Next, we provide a generic taxonomy of building blocks out of which an NSI/NSSI may be designed, followed by proposing precise definitions of the design process and its expected outcomes. Then, by elaborating on those definitions, we explain, in a technology-agnostic manner, the activities comprising the design process and the results it shall produce. Based on these fundamentals, we describe the opportunities for automating the design process, essential to support the declarative provisioning style and to offer the “dynamic slicing” capabilities by the Slicing orchestrators. All of the elaborated systematizations and concepts are vendor-agnostic and fully standards-aligned which makes them practically usable in a wide range of solutions.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":null,"pages":null},"PeriodicalIF":35.6,"publicationDate":"2023-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10375939","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141084900","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}
Metaverse is an evolving orchestrator of the next-generation Internet architecture that produces an immersive and self-adapting virtual world in which humans perform activities similar to those in the real world, such as playing sports, doing work, and socializing. It is becoming a reality and is driven by ever-evolving advanced technologies such as extended reality, artificial intelligence, and blockchain. In this context, Metaverse will play an essential role in developing smart cities, which becomes more evident in the post-COVID-19-pandemic metropolitan setting. However, the new paradigm imposes new challenges, such as developing novel privacy and security threats that can emerge in the digital Metaverse ecosystem. Moreover, it requires the convergence of several media types with the capability to quickly process massive amounts of data to keep the residents safe and well-informed, which can raise issues related to scalability and interoperability. In light of this, this research study aims to review the literature on the state of the art of integrating the Metaverse architecture concepts in smart cities. First, this paper presents the theoretical architecture of Metaverse and discusses international companies’ interest in this emerging technology. It also examines the notion of Metaverse relevant to virtual reality, identifies the prevalent threats, and determines the importance of communication infrastructure in information gathering for efficient Metaverse operation. Next, the notion of blockchain technologies is discussed regarding privacy preservation and how it can provide tamper-proof content sharing among Metaverse users. Finally, the application of distributed Metaverse for social good is highlighted. Most importantly, the paper explores the reflections of this cutting-edge technology on the smart city, talks about the role and impact of the Metaverse in the production of urban policies, and eventually identifies the research gaps and the future research directions in this domain.
{"title":"Metaverse Communications, Networking, Security, and Applications: Research Issues, State-of-the-Art, and Future Directions","authors":"Mansoor Ali;Faisal Naeem;Georges Kaddoum;Ekram Hossain","doi":"10.1109/COMST.2023.3347172","DOIUrl":"https://doi.org/10.1109/COMST.2023.3347172","url":null,"abstract":"Metaverse is an evolving orchestrator of the next-generation Internet architecture that produces an immersive and self-adapting virtual world in which humans perform activities similar to those in the real world, such as playing sports, doing work, and socializing. It is becoming a reality and is driven by ever-evolving advanced technologies such as extended reality, artificial intelligence, and blockchain. In this context, Metaverse will play an essential role in developing smart cities, which becomes more evident in the post-COVID-19-pandemic metropolitan setting. However, the new paradigm imposes new challenges, such as developing novel privacy and security threats that can emerge in the digital Metaverse ecosystem. Moreover, it requires the convergence of several media types with the capability to quickly process massive amounts of data to keep the residents safe and well-informed, which can raise issues related to scalability and interoperability. In light of this, this research study aims to review the literature on the state of the art of integrating the Metaverse architecture concepts in smart cities. First, this paper presents the theoretical architecture of Metaverse and discusses international companies’ interest in this emerging technology. It also examines the notion of Metaverse relevant to virtual reality, identifies the prevalent threats, and determines the importance of communication infrastructure in information gathering for efficient Metaverse operation. Next, the notion of blockchain technologies is discussed regarding privacy preservation and how it can provide tamper-proof content sharing among Metaverse users. Finally, the application of distributed Metaverse for social good is highlighted. Most importantly, the paper explores the reflections of this cutting-edge technology on the smart city, talks about the role and impact of the Metaverse in the production of urban policies, and eventually identifies the research gaps and the future research directions in this domain.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":null,"pages":null},"PeriodicalIF":35.6,"publicationDate":"2023-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141084816","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 : 2023-12-21DOI: 10.1109/COMST.2023.3344671
Hitesh Poddar;Shihao Ju;Dipankar Shakya;Theodore S. Rappaport
With the advancement of wireless communication to sub-terahertz (THz) and millimeter-wave (mmWave) bands, accurate channel models and simulation tools are becoming increasingly important for modeling a wide range of frequencies and scenarios. This paper provides a comprehensive tutorial on generating drop-based and spatial consistency-based channels using the open-source MATLAB-based NYU Channel Model Simulator (NYUSIM). NYUSIM is built on extensive real-world radio propagation measurements for the frequency range of 0.5–150 GHz, covering a variety of scenarios such as Urban Microcell (UMi), Urban Macrocell (UMa), Rural Macrocell (RMa), Indoor Hotspot (InH), and Indoor Factory (InF). Additionally, an overview of the evolution of simulators used to design and analyze wireless systems since the early days of cellular communication is also provided. We introduce the most popular types of simulators used in academia and industry, such as Channel Simulators (CSs), Link Level Simulators (LLSs), System Level Simulators (SLSs), and Network Simulators (NSs), to study wireless communication systems for 5G and beyond. Owing to the widespread adoption of the 3rd Generation Partnership Project (3GPP) Stochastic Channel Model (SCM) for channel generation in various simulators, we conduct a comparative analysis between the 3GPP SCM and NYUSIM channel model to highlight their differences. Moreover, NYUSIM’s versatility extends beyond its MATLAB implementation, as it can be implemented in various LLSs, SLSs, and NSs, enabling researchers to incorporate real-world measurement-based channels into their simulations. To illustrate this capability, we showcase NYUSIM’s implementation in ns-3, a widely used open-source discrete event network simulator. Additionally, we provide several applications of NYUSIM to highlight its potential uses.
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Pub Date : 2023-12-21DOI: 10.1109/COMST.2023.3345796
Nada Abdel Khalek;Deemah H. Tashman;Walaa Hamouda
The next frontier in wireless connectivity lies at the intersection of cognitive radio (CR) technology and machine learning (ML), where intelligent networks can provide pervasive connectivity for an ever-expanding range of applications. In this regard, this survey provides an in-depth examination of the integration of ML-based CR in a wide range of emerging wireless networks, including the Internet of Things (IoT), mobile communications (vehicular and railway), and unmanned aerial vehicle (UAV) communications. By combining ML-based CR and emerging wireless networks, we can create intelligent, efficient, and ubiquitous wireless communication systems that satisfy spectrum-hungry applications and services of next-generation networks. For each type of wireless network, we highlight the key motivation for using intelligent CR and present a full review of the existing state-of-the-art ML approaches that address pressing challenges, including energy efficiency, interference, throughput, latency, and security. Our goal is to provide researchers and newcomers with a clear understanding of the motivation and methodology behind applying intelligent CR to emerging wireless networks. Moreover, problems and prospective research avenues are outlined, and a future roadmap is offered that explores possibilities for overcoming challenges through trending concepts.
无线连接的下一个前沿领域是认知无线电（CR）技术和机器学习（ML）技术的交汇点，智能网络可为不断扩大的应用提供无处不在的连接。在这方面，本调查报告深入探讨了基于 ML 的 CR 与各种新兴无线网络的整合，包括物联网 (IoT)、移动通信（车载和铁路）和无人机 (UAV) 通信。通过将基于 ML 的 CR 与新兴无线网络相结合，我们可以创建智能、高效和无处不在的无线通信系统，满足下一代网络对频谱的需求。对于每种类型的无线网络，我们都强调了使用智能 CR 的主要动机，并全面回顾了现有的最先进的 ML 方法，这些方法可解决能源效率、干扰、吞吐量、延迟和安全性等紧迫挑战。我们的目标是让研究人员和新手清楚地了解将智能 CR 应用于新兴无线网络背后的动机和方法。此外，我们还概述了存在的问题和前瞻性研究途径，并提供了未来路线图，探讨通过趋势概念克服挑战的可能性。
{"title":"Advances in Machine Learning-Driven Cognitive Radio for Wireless Networks: A Survey","authors":"Nada Abdel Khalek;Deemah H. Tashman;Walaa Hamouda","doi":"10.1109/COMST.2023.3345796","DOIUrl":"https://doi.org/10.1109/COMST.2023.3345796","url":null,"abstract":"The next frontier in wireless connectivity lies at the intersection of cognitive radio (CR) technology and machine learning (ML), where intelligent networks can provide pervasive connectivity for an ever-expanding range of applications. In this regard, this survey provides an in-depth examination of the integration of ML-based CR in a wide range of emerging wireless networks, including the Internet of Things (IoT), mobile communications (vehicular and railway), and unmanned aerial vehicle (UAV) communications. By combining ML-based CR and emerging wireless networks, we can create intelligent, efficient, and ubiquitous wireless communication systems that satisfy spectrum-hungry applications and services of next-generation networks. For each type of wireless network, we highlight the key motivation for using intelligent CR and present a full review of the existing state-of-the-art ML approaches that address pressing challenges, including energy efficiency, interference, throughput, latency, and security. Our goal is to provide researchers and newcomers with a clear understanding of the motivation and methodology behind applying intelligent CR to emerging wireless networks. Moreover, problems and prospective research avenues are outlined, and a future roadmap is offered that explores possibilities for overcoming challenges through trending concepts.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":null,"pages":null},"PeriodicalIF":35.6,"publicationDate":"2023-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141084854","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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