The Internet of Things plays a predominant role in automating all real-time applications.One such application is the Internet of Vehicles which monitors the roadside traffic for automating traffic rules.As vehicles ar...The Internet of Things plays a predominant role in automating all real-time applications.One such application is the Internet of Vehicles which monitors the roadside traffic for automating traffic rules.As vehicles are connected to the internet through wireless communication technologies,the Internet of Vehicles network infrastructure is susceptible to flooding attacks.Reconfiguring the network infrastructure is difficult as network customization is not possible.As Software Defined Network provide a flexible programming environment for network customization,detecting flooding attacks on the Internet of Vehicles is integrated on top of it.The basic methodology used is crypto-fuzzy rules,in which cryptographic standard is incorporated in the traditional fuzzy rules.In this research work,an intelligent framework for secure transportation is proposed with the basic ideas of security attacks on the Internet of Vehicles integrated with software-defined networking.The intelligent framework is proposed to apply for the smart city application.The proposed cognitive framework is integrated with traditional fuzzy,cryptofuzzy and Restricted Boltzmann Machine algorithm to detect malicious traffic flows in Software-Defined-Internet of Vehicles.It is inferred from the result interpretations that an intelligent framework for secure transportation system achieves better attack detection accuracy with less delay and also prevents buffer overflow attacks.The proposed intelligent framework for secure transportation system is not compared with existing methods;instead,it is tested with crypto and machine learning algorithms.展开更多
It is foreseen that the Internet of Things (IoT) will comprise billions of connected devices, and this will make the provi?sioning and operation of some IoT connectivity services more challenging. Indeed, IoT services...It is foreseen that the Internet of Things (IoT) will comprise billions of connected devices, and this will make the provi?sioning and operation of some IoT connectivity services more challenging. Indeed, IoT services are very different from lega?cy Internet services because of their dimensioning figures and also because IoT services differ dramatically in terms of na?ture and constraints. For example, IoT services often rely on energy and CPU?constrained sensor technologies, regardless of whether the service is for home automation, smart building, e?health, or power or water metering on a regional or national scale. Also, some IoT services, such as dynamic monitoring of biometric data, manipulation of sensitive information, and pri?vacy needs to be safeguarded whenever this information is for?warded over the underlying IoT network infrastructure. This paper discusses how software?defined networking (SDN) can facilitate the deployment and operation of some advanced IoT services regardless of their nature or scope. SDN introduces a high degree of automation in service delivery and operation-from dynamic IoT service parameter exposure and negotiation to resource allocation, service fulfillment, and assurance. This paper does not argue that all IoT services must adopt SDN. Rather, it is left to the discretion of operators to decide which IoT services can best leverage SDN capabilities. This paper only discusses managed IoT services, i.e., services that are op?erated by a service provider.展开更多
For the past few decades,the internet of underwater things(IoUT)otained a lot of attention in mobile aquatic applications such as oceanography,diver network monitoring,unmanned underwater exploration,underwater survei...For the past few decades,the internet of underwater things(IoUT)otained a lot of attention in mobile aquatic applications such as oceanography,diver network monitoring,unmanned underwater exploration,underwater surveillance,location tracking system,etc.Most of the IoUT applications rely on acoustic medium.The current IoUT applications face difficulty in delivering a reliable communication system due to the various technical limitations of IoUT environment such as low data rate,attenuation,limited bandwidth,limited battery,limited memory,connectivity problem,etc.One of the significant applications of IoUT include monitoring underwater diver networks.In order to perform a reliable and energy-efficient communication system in the underwater diver networks,a smart underwater hybrid softwaredefined modem(UHSDM)for the mobile ad-hoc network was developed that is used for selecting the best channel/medium among acoustic,visible light communication(VLC),and infrared(IR)based on the criteria established within the system.However,due to the mobility of underwater divers,the developed UHSDMmeets the challenges such as connectivity errors,frequent link failure,transmission delay caused by re-routing,etc.During emergency,the divers are most at the risk of survival.To deal with diver mobility,connectivity,energy efficiency,and reducing the latency in ADN,a handover mechanism based on pre-built UHSDM is proposed in this paper.This paper focuses on(1)design of UHSDM for ADN(2)propose the channel selection mechanism in UHSDM for selecting the best medium for handover and(3)propose handover protocol inADN.The implementation result shows that the proposed mechanism can be used to find the new route for divers in advance and the latency can be reduced significantly.Additionally,this paper shows the real field experiment of air tests and underwater tests with various distances.This research will contribute much to the profit of researchers in underwater diver networks and underwater networks,for improving the quality of services(QoS)of underwater applications.展开更多
In the context of an increasingly severe cybersecurity landscape and the growing complexity of offensive and defen-sive techniques,Zero Trust Networks(ZTN)have emerged as a widely recognized technology.Zero Trust not ...In the context of an increasingly severe cybersecurity landscape and the growing complexity of offensive and defen-sive techniques,Zero Trust Networks(ZTN)have emerged as a widely recognized technology.Zero Trust not only addresses the shortcomings of traditional perimeter security models but also consistently follows the fundamental principle of“never trust,always verify.”Initially proposed by John Cortez in 2010 and subsequently promoted by Google,the Zero Trust model has become a key approach to addressing the ever-growing security threats in complex network environments.This paper systematically compares the current mainstream cybersecurity models,thoroughly explores the advantages and limitations of the Zero Trust model,and provides an in-depth review of its components and key technologies.Additionally,it analyzes the latest research achievements in the application of Zero Trust technology across various fields,including network security,6G networks,the Internet of Things(IoT),and cloud computing,in the context of specific use cases.The paper also discusses the innovative contributions of the Zero Trust model in these fields,the challenges it faces,and proposes corresponding solutions and future research directions.展开更多
Emerging technologies and the Internet of Things(IoT)are integrating for the growth and development of heterogeneous networks.These systems are providing real-time devices to end users to deliver dynamic services and ...Emerging technologies and the Internet of Things(IoT)are integrating for the growth and development of heterogeneous networks.These systems are providing real-time devices to end users to deliver dynamic services and improve human lives.Most existing approaches have been proposed to improve energy efficiency and ensure reliable routing;however,trustworthiness and network scalability remain significant research challenges.In this research work,we introduce an AI-enabled Software-Defined Network(SDN)-driven framework to provide secure communication,trusted behavior,and effective route maintenance.By considering multiple parameters in the forwarder selection process,the proposed framework enhances network stability and optimizes decision-making.In addition,the involvement of the blockchain consensus algorithm and the intelligence of the SDN controller enables a proposed framework for robust authentication and a verifiable process of data blocks.Ultimately,only trusted devices are selected for routing,and malicious threats are prevented as data is forwarded to the cloud system.The extensive experimental analysis demonstrated that the proposed framework significantly improved energy consumption by 48%,packet loss by 49%,response time by 46%,and data transfer rate by 45%compared with existing techniques.展开更多
Software-Defined Networking(SDN)represents a significant paradigm shift in network architecture,separating network logic from the underlying forwarding devices to enhance flexibility and centralize deployment.Concur-r...Software-Defined Networking(SDN)represents a significant paradigm shift in network architecture,separating network logic from the underlying forwarding devices to enhance flexibility and centralize deployment.Concur-rently,the Internet of Things(IoT)connects numerous devices to the Internet,enabling autonomous interactions with minimal human intervention.However,implementing and managing an SDN-IoT system is inherently complex,particularly for those with limited resources,as the dynamic and distributed nature of IoT infrastructures creates security and privacy challenges during SDN integration.The findings of this study underscore the primary security and privacy challenges across application,control,and data planes.A comprehensive review evaluates the root causes of these challenges and the defense techniques employed in prior works to establish sufficient secrecy and privacy protection.Recent investigations have explored cutting-edge methods,such as leveraging blockchain for transaction recording to enhance security and privacy,along with applying machine learning and deep learning approaches to identify and mitigate the impacts of Denial of Service(DoS)and Distributed DoS(DDoS)attacks.Moreover,the analysis indicates that encryption and hashing techniques are prevalent in the data plane,whereas access control and certificate authorization are prominently considered in the control plane,and authentication is commonly employed within the application plane.Additionally,this paper outlines future directions,offering insights into potential strategies and technological advancements aimed at fostering a more secure and privacy-conscious SDN-based IoT ecosystem.展开更多
The data being generated by the Internet of Things needs to be stored,monitored,and analyzed for maximum IoT resource utilization.Software Defined Networking has been extensively utilized to address issues such as het...The data being generated by the Internet of Things needs to be stored,monitored,and analyzed for maximum IoT resource utilization.Software Defined Networking has been extensively utilized to address issues such as heterogeneity and scalability.However,for small-scale IoT application,sometimes it is considered an inefficient approach.This paper proposes an alternate lightweight mechanism to the design and implementation of a dynamic virtual network based on user requirements.The key idea is to provide users a virtual interface that enables them to reconfigure the communication flow between the sensors and actuators at runtime.The throughput of the communication flow depends on the data traffic load and optimal routing.Users can reconfigure the communication flow,and virtual agents find the optimal route to handle the traffic load.The virtual network provides a user-friendly interface to allow physical devices to be mapped with the corresponding virtual agents.The proposed network is applicable for all systems that lie in the Internet of Things domain.Results conclude that the proposed network is efficient,reliable,and responsive to network reconfiguration at runtime.展开更多
Since World Health Organization(WHO)has declared the Coronavirus disease(COVID-19)a global pandemic,the world has changed.All life’s fields and daily habits have moved to adapt to this new situation.According to WHO,...Since World Health Organization(WHO)has declared the Coronavirus disease(COVID-19)a global pandemic,the world has changed.All life’s fields and daily habits have moved to adapt to this new situation.According to WHO,the probability of such virus pandemics in the future is high,and recommends preparing for worse situations.To this end,this work provides a framework for monitoring,tracking,and fighting COVID-19 and future pandemics.The proposed framework deploys unmanned aerial vehicles(UAVs),e.g.;quadcopter and drone,integrated with artificial intelligence(AI)and Internet of Things(IoT)to monitor and fight COVID-19.It consists of two main systems;AI/IoT for COVID-19 monitoring and drone-based IoT system for sterilizing.The two systems are integrated with the IoT paradigm and the developed algorithms are implemented on distributed fog units connected to the IoT network and controlled by software-defined networking(SDN).The proposed work is built based on a thermal camera mounted in a face-shield,or on a helmet that can be used by people during pandemics.The detected images,thermal images,are processed by the developed AI algorithm that is built based on the convolutional neural network(CNN).The drone system can be called,by the IoT system connected to the helmet,once infected cases are detected.The drone is used for sterilizing the area that contains multiple infected people.The proposed framework employs a single centralized SDN controller to control the network operations.The developed system is experimentally evaluated,and the results are introduced.Results indicate that the developed framework provides a novel,efficient scheme for monitoring and fighting COVID-19 and other future pandemics.展开更多
The ongoing expansion of the Industrial Internet of Things(IIoT)is enabling the possibility of effective Industry 4.0,where massive sensing devices in heterogeneous environments are connected through dedicated communi...The ongoing expansion of the Industrial Internet of Things(IIoT)is enabling the possibility of effective Industry 4.0,where massive sensing devices in heterogeneous environments are connected through dedicated communication protocols.This brings forth new methods and models to fuse the information yielded by the various industrial plant elements and generates emerging security challenges that we have to face,providing ad-hoc functions for scheduling and guaranteeing the network operations.Recently,the large development of SoftwareDefined Networking(SDN)and Artificial Intelligence(AI)technologies have made feasible the design and control of scalable and secure IIoT networks.This paper studies how AI and SDN technologies combined can be leveraged towards improving the security and functionality of these IIoT networks.After surveying the state-of-the-art research efforts in the subject,the paper introduces a candidate architecture for AI-enabled Software-Defined IIoT Network(AI-SDIN)that divides the traditional industrial networks into three functional layers.And with this aim in mind,key technologies(Blockchain-based Data Sharing,Intelligent Wireless Data Sensing,Edge Intelligence,Time-Sensitive Networks,Integrating SDN&TSN,Distributed AI)and improve applications based on AISDIN are also discussed.Further,the paper also highlights new opportunities and potential research challenges in control and automation of IIoT networks.展开更多
The rise of the Internet of Things and autonomous systems has made connecting vehicles more critical.Connected autonomous vehicles can create diverse communication networks that can improve the environment and offer c...The rise of the Internet of Things and autonomous systems has made connecting vehicles more critical.Connected autonomous vehicles can create diverse communication networks that can improve the environment and offer contemporary applications.With the advent of Fifth Generation(5G)networks,vehicle-to-everything(V2X)networks are expected to be highly intelligent,reside on superfast,reliable,and low-latency connections.Network slicing,machine learning(ML),and deep learning(DL)are related to network automation and optimization in V2X communication.ML/DL with network slicing aims to optimize the performance,reliability of the V2X networks,personalized services,costs,and scalability,and thus,it enhances the overall driving experience.These advantages can ultimately lead to a safer and more efficient transportation system.However,existing long-term evolution systems and enabling 5G technologies cannot meet such dynamic requirements without adding higher complexity levels.ML algorithms mitigate complexity levels,which can be highly instrumental in such vehicular communication systems.This study aims to review V2X slicing based on a proposed taxonomy that describes the enablers of slicing,a different configuration of slicing,the requirements of slicing,and the ML algorithm used to control and manage to slice.This study also reviews various research works established in network slicing through ML algorithms to enable V2X communication use cases,focusing on V2X network slicing and considering efficient control and management.The enabler technologies are considered in light of the network requirements,particular configurations,and the underlying methods and algorithms,with a review of some critical challenges and possible solutions available.The paper concludes with a future roadmap by discussing some open research issues and future directions.展开更多
文摘The Internet of Things plays a predominant role in automating all real-time applications.One such application is the Internet of Vehicles which monitors the roadside traffic for automating traffic rules.As vehicles are connected to the internet through wireless communication technologies,the Internet of Vehicles network infrastructure is susceptible to flooding attacks.Reconfiguring the network infrastructure is difficult as network customization is not possible.As Software Defined Network provide a flexible programming environment for network customization,detecting flooding attacks on the Internet of Vehicles is integrated on top of it.The basic methodology used is crypto-fuzzy rules,in which cryptographic standard is incorporated in the traditional fuzzy rules.In this research work,an intelligent framework for secure transportation is proposed with the basic ideas of security attacks on the Internet of Vehicles integrated with software-defined networking.The intelligent framework is proposed to apply for the smart city application.The proposed cognitive framework is integrated with traditional fuzzy,cryptofuzzy and Restricted Boltzmann Machine algorithm to detect malicious traffic flows in Software-Defined-Internet of Vehicles.It is inferred from the result interpretations that an intelligent framework for secure transportation system achieves better attack detection accuracy with less delay and also prevents buffer overflow attacks.The proposed intelligent framework for secure transportation system is not compared with existing methods;instead,it is tested with crypto and machine learning algorithms.
文摘It is foreseen that the Internet of Things (IoT) will comprise billions of connected devices, and this will make the provi?sioning and operation of some IoT connectivity services more challenging. Indeed, IoT services are very different from lega?cy Internet services because of their dimensioning figures and also because IoT services differ dramatically in terms of na?ture and constraints. For example, IoT services often rely on energy and CPU?constrained sensor technologies, regardless of whether the service is for home automation, smart building, e?health, or power or water metering on a regional or national scale. Also, some IoT services, such as dynamic monitoring of biometric data, manipulation of sensitive information, and pri?vacy needs to be safeguarded whenever this information is for?warded over the underlying IoT network infrastructure. This paper discusses how software?defined networking (SDN) can facilitate the deployment and operation of some advanced IoT services regardless of their nature or scope. SDN introduces a high degree of automation in service delivery and operation-from dynamic IoT service parameter exposure and negotiation to resource allocation, service fulfillment, and assurance. This paper does not argue that all IoT services must adopt SDN. Rather, it is left to the discretion of operators to decide which IoT services can best leverage SDN capabilities. This paper only discusses managed IoT services, i.e., services that are op?erated by a service provider.
基金This research was a part of the project titled“Development of the wide-area underwater mobile communication systems”funded by the Ministry of Oceans and Fisheries,Korea.
文摘For the past few decades,the internet of underwater things(IoUT)otained a lot of attention in mobile aquatic applications such as oceanography,diver network monitoring,unmanned underwater exploration,underwater surveillance,location tracking system,etc.Most of the IoUT applications rely on acoustic medium.The current IoUT applications face difficulty in delivering a reliable communication system due to the various technical limitations of IoUT environment such as low data rate,attenuation,limited bandwidth,limited battery,limited memory,connectivity problem,etc.One of the significant applications of IoUT include monitoring underwater diver networks.In order to perform a reliable and energy-efficient communication system in the underwater diver networks,a smart underwater hybrid softwaredefined modem(UHSDM)for the mobile ad-hoc network was developed that is used for selecting the best channel/medium among acoustic,visible light communication(VLC),and infrared(IR)based on the criteria established within the system.However,due to the mobility of underwater divers,the developed UHSDMmeets the challenges such as connectivity errors,frequent link failure,transmission delay caused by re-routing,etc.During emergency,the divers are most at the risk of survival.To deal with diver mobility,connectivity,energy efficiency,and reducing the latency in ADN,a handover mechanism based on pre-built UHSDM is proposed in this paper.This paper focuses on(1)design of UHSDM for ADN(2)propose the channel selection mechanism in UHSDM for selecting the best medium for handover and(3)propose handover protocol inADN.The implementation result shows that the proposed mechanism can be used to find the new route for divers in advance and the latency can be reduced significantly.Additionally,this paper shows the real field experiment of air tests and underwater tests with various distances.This research will contribute much to the profit of researchers in underwater diver networks and underwater networks,for improving the quality of services(QoS)of underwater applications.
基金supported by the National Natural Science Foundation of China(Grants Nos.62473146,62072249 and 62072056)the National Science Foundation of Hunan Province(Grant No.2024JJ3017)+1 种基金the Hunan Provincial Key Research and Development Program(Grant No.2022GK2019)by the Researchers Supporting Project Number(RSP2024R509),King Saud University,Riyadh,Saudi Arabia.
文摘In the context of an increasingly severe cybersecurity landscape and the growing complexity of offensive and defen-sive techniques,Zero Trust Networks(ZTN)have emerged as a widely recognized technology.Zero Trust not only addresses the shortcomings of traditional perimeter security models but also consistently follows the fundamental principle of“never trust,always verify.”Initially proposed by John Cortez in 2010 and subsequently promoted by Google,the Zero Trust model has become a key approach to addressing the ever-growing security threats in complex network environments.This paper systematically compares the current mainstream cybersecurity models,thoroughly explores the advantages and limitations of the Zero Trust model,and provides an in-depth review of its components and key technologies.Additionally,it analyzes the latest research achievements in the application of Zero Trust technology across various fields,including network security,6G networks,the Internet of Things(IoT),and cloud computing,in the context of specific use cases.The paper also discusses the innovative contributions of the Zero Trust model in these fields,the challenges it faces,and proposes corresponding solutions and future research directions.
基金funded by the Deanship of Graduate Studies and Scientific Research at Jouf University under grant No.DGSSR-2025-02-01669financial support from the Deanship of Graduate Studies and Scientific Research at Jouf University.
文摘Emerging technologies and the Internet of Things(IoT)are integrating for the growth and development of heterogeneous networks.These systems are providing real-time devices to end users to deliver dynamic services and improve human lives.Most existing approaches have been proposed to improve energy efficiency and ensure reliable routing;however,trustworthiness and network scalability remain significant research challenges.In this research work,we introduce an AI-enabled Software-Defined Network(SDN)-driven framework to provide secure communication,trusted behavior,and effective route maintenance.By considering multiple parameters in the forwarder selection process,the proposed framework enhances network stability and optimizes decision-making.In addition,the involvement of the blockchain consensus algorithm and the intelligence of the SDN controller enables a proposed framework for robust authentication and a verifiable process of data blocks.Ultimately,only trusted devices are selected for routing,and malicious threats are prevented as data is forwarded to the cloud system.The extensive experimental analysis demonstrated that the proposed framework significantly improved energy consumption by 48%,packet loss by 49%,response time by 46%,and data transfer rate by 45%compared with existing techniques.
基金This work was supported by National Natural Science Foundation of China(Grant No.62341208)Natural Science Foundation of Zhejiang Province(Grant Nos.LY23F020006 and LR23F020001)Moreover,it has been supported by Islamic Azad University with the Grant No.133713281361.
文摘Software-Defined Networking(SDN)represents a significant paradigm shift in network architecture,separating network logic from the underlying forwarding devices to enhance flexibility and centralize deployment.Concur-rently,the Internet of Things(IoT)connects numerous devices to the Internet,enabling autonomous interactions with minimal human intervention.However,implementing and managing an SDN-IoT system is inherently complex,particularly for those with limited resources,as the dynamic and distributed nature of IoT infrastructures creates security and privacy challenges during SDN integration.The findings of this study underscore the primary security and privacy challenges across application,control,and data planes.A comprehensive review evaluates the root causes of these challenges and the defense techniques employed in prior works to establish sufficient secrecy and privacy protection.Recent investigations have explored cutting-edge methods,such as leveraging blockchain for transaction recording to enhance security and privacy,along with applying machine learning and deep learning approaches to identify and mitigate the impacts of Denial of Service(DoS)and Distributed DoS(DDoS)attacks.Moreover,the analysis indicates that encryption and hashing techniques are prevalent in the data plane,whereas access control and certificate authorization are prominently considered in the control plane,and authentication is commonly employed within the application plane.Additionally,this paper outlines future directions,offering insights into potential strategies and technological advancements aimed at fostering a more secure and privacy-conscious SDN-based IoT ecosystem.
基金the National Key Research and Development Program of China (2021YFB1715700)the National Natural Science Foundation of China (62103046)+2 种基金the Beijing Institute of Technology Research Fund Program for Young Scholarsthe Chinese Academy of Sciences and University of Chinese Academy of Sciences for funding the research (Y92902MED2, E1E90808, and E0E90804)the Fundamental Research Funds for the Central Universities (E1E40805)。
基金This research was supported by Energy Cloud R&D Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Science,ICT(2019M3F2A1073387)this research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(2018R1D1A1A09082919)this research was supported by Institute for Information&communications Technology Planning&Evaluation(IITP)grant funded by the Korea government(MSIT)(No.2018-0-01456,AutoMaTa:Autonomous Management framework based on artificial intelligent Technology for adaptive and disposable IoT).Any correspondence related to this paper should be addressed to Dohyeun Kim.
文摘The data being generated by the Internet of Things needs to be stored,monitored,and analyzed for maximum IoT resource utilization.Software Defined Networking has been extensively utilized to address issues such as heterogeneity and scalability.However,for small-scale IoT application,sometimes it is considered an inefficient approach.This paper proposes an alternate lightweight mechanism to the design and implementation of a dynamic virtual network based on user requirements.The key idea is to provide users a virtual interface that enables them to reconfigure the communication flow between the sensors and actuators at runtime.The throughput of the communication flow depends on the data traffic load and optimal routing.Users can reconfigure the communication flow,and virtual agents find the optimal route to handle the traffic load.The virtual network provides a user-friendly interface to allow physical devices to be mapped with the corresponding virtual agents.The proposed network is applicable for all systems that lie in the Internet of Things domain.Results conclude that the proposed network is efficient,reliable,and responsive to network reconfiguration at runtime.
基金The authors extend their appreciation to the Deputyship for Research&Innova-tion,Ministry of Education in Saudi Arabia for funding this research work through the project number(PNU-DRI-Targeted-20-033).
文摘Since World Health Organization(WHO)has declared the Coronavirus disease(COVID-19)a global pandemic,the world has changed.All life’s fields and daily habits have moved to adapt to this new situation.According to WHO,the probability of such virus pandemics in the future is high,and recommends preparing for worse situations.To this end,this work provides a framework for monitoring,tracking,and fighting COVID-19 and future pandemics.The proposed framework deploys unmanned aerial vehicles(UAVs),e.g.;quadcopter and drone,integrated with artificial intelligence(AI)and Internet of Things(IoT)to monitor and fight COVID-19.It consists of two main systems;AI/IoT for COVID-19 monitoring and drone-based IoT system for sterilizing.The two systems are integrated with the IoT paradigm and the developed algorithms are implemented on distributed fog units connected to the IoT network and controlled by software-defined networking(SDN).The proposed work is built based on a thermal camera mounted in a face-shield,or on a helmet that can be used by people during pandemics.The detected images,thermal images,are processed by the developed AI algorithm that is built based on the convolutional neural network(CNN).The drone system can be called,by the IoT system connected to the helmet,once infected cases are detected.The drone is used for sterilizing the area that contains multiple infected people.The proposed framework employs a single centralized SDN controller to control the network operations.The developed system is experimentally evaluated,and the results are introduced.Results indicate that the developed framework provides a novel,efficient scheme for monitoring and fighting COVID-19 and other future pandemics.
基金This work was supported by the six talent peaks project in Jiangsu Province(No.XYDXX-012)Natural Science Foundation of China(No.62002045),China Postdoctoral Science Foundation(No.2021M690565)Fundamental Research Funds for the Cornell University(No.N2117002).
文摘The ongoing expansion of the Industrial Internet of Things(IIoT)is enabling the possibility of effective Industry 4.0,where massive sensing devices in heterogeneous environments are connected through dedicated communication protocols.This brings forth new methods and models to fuse the information yielded by the various industrial plant elements and generates emerging security challenges that we have to face,providing ad-hoc functions for scheduling and guaranteeing the network operations.Recently,the large development of SoftwareDefined Networking(SDN)and Artificial Intelligence(AI)technologies have made feasible the design and control of scalable and secure IIoT networks.This paper studies how AI and SDN technologies combined can be leveraged towards improving the security and functionality of these IIoT networks.After surveying the state-of-the-art research efforts in the subject,the paper introduces a candidate architecture for AI-enabled Software-Defined IIoT Network(AI-SDIN)that divides the traditional industrial networks into three functional layers.And with this aim in mind,key technologies(Blockchain-based Data Sharing,Intelligent Wireless Data Sensing,Edge Intelligence,Time-Sensitive Networks,Integrating SDN&TSN,Distributed AI)and improve applications based on AISDIN are also discussed.Further,the paper also highlights new opportunities and potential research challenges in control and automation of IIoT networks.
基金This work was supported in part by the National Key Research and Development Program of China under Grant 2020YFB1807900the National Natural Science Foundation of China under Grant 62101306The work was also supported by Datang Linktester Technology Co.Ltd.
文摘The rise of the Internet of Things and autonomous systems has made connecting vehicles more critical.Connected autonomous vehicles can create diverse communication networks that can improve the environment and offer contemporary applications.With the advent of Fifth Generation(5G)networks,vehicle-to-everything(V2X)networks are expected to be highly intelligent,reside on superfast,reliable,and low-latency connections.Network slicing,machine learning(ML),and deep learning(DL)are related to network automation and optimization in V2X communication.ML/DL with network slicing aims to optimize the performance,reliability of the V2X networks,personalized services,costs,and scalability,and thus,it enhances the overall driving experience.These advantages can ultimately lead to a safer and more efficient transportation system.However,existing long-term evolution systems and enabling 5G technologies cannot meet such dynamic requirements without adding higher complexity levels.ML algorithms mitigate complexity levels,which can be highly instrumental in such vehicular communication systems.This study aims to review V2X slicing based on a proposed taxonomy that describes the enablers of slicing,a different configuration of slicing,the requirements of slicing,and the ML algorithm used to control and manage to slice.This study also reviews various research works established in network slicing through ML algorithms to enable V2X communication use cases,focusing on V2X network slicing and considering efficient control and management.The enabler technologies are considered in light of the network requirements,particular configurations,and the underlying methods and algorithms,with a review of some critical challenges and possible solutions available.The paper concludes with a future roadmap by discussing some open research issues and future directions.
