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
Underwater Wireless Sensor Networks(UWSNs)are widely used in many fields,such as regular marine monitoring and disaster warning.However,UWSNs are still subject to various limitations and challenges:ocean interferences...Underwater Wireless Sensor Networks(UWSNs)are widely used in many fields,such as regular marine monitoring and disaster warning.However,UWSNs are still subject to various limitations and challenges:ocean interferences and noises are high,bandwidths are narrow,and propagation delays are high.Sensor batteries have limited energy and are difficult to be replaced or recharged.Accordingly,the design of routing protocols is one of the solutions to these problems.Aiming at reducing and balancing network energy consumption and effectively extending the life cycle of UWSNs,this paper proposes a Hierarchical Adaptive Energy-efficient Clustering Routing(HAECR)strategy.First,this strategy divides hierarchical regions based on the depth of the sensor node in a three-dimensional(3D)space.Second,sensor nodes form different competition radii based on their own relevant attributes and remaining energy.Nodes in the same layer compete freely to form clusters of different sizes.Finally,the transmission path between clusters is determined according to comprehensive factors,such as link quality,and then the optimal route is planned.The simulation experiment is conducted in the monitoring range of the 3D space.The simulation results prove that the HAECR clustering strategy is superior to LEACH and UCUBB in terms of balancing and reducing energy consumption,extending the network lifetime,and increasing the number of data transmissions.展开更多
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.
文摘Underwater Wireless Sensor Networks(UWSNs)are widely used in many fields,such as regular marine monitoring and disaster warning.However,UWSNs are still subject to various limitations and challenges:ocean interferences and noises are high,bandwidths are narrow,and propagation delays are high.Sensor batteries have limited energy and are difficult to be replaced or recharged.Accordingly,the design of routing protocols is one of the solutions to these problems.Aiming at reducing and balancing network energy consumption and effectively extending the life cycle of UWSNs,this paper proposes a Hierarchical Adaptive Energy-efficient Clustering Routing(HAECR)strategy.First,this strategy divides hierarchical regions based on the depth of the sensor node in a three-dimensional(3D)space.Second,sensor nodes form different competition radii based on their own relevant attributes and remaining energy.Nodes in the same layer compete freely to form clusters of different sizes.Finally,the transmission path between clusters is determined according to comprehensive factors,such as link quality,and then the optimal route is planned.The simulation experiment is conducted in the monitoring range of the 3D space.The simulation results prove that the HAECR clustering strategy is superior to LEACH and UCUBB in terms of balancing and reducing energy consumption,extending the network lifetime,and increasing the number of data transmissions.
