Recently, the use of ubiquitous sensor network technology has spread vastly. The ubiquitous sensor networks are widely de- ployed in factory auttxnation as they provide effective measuring solution for instruments. Th...Recently, the use of ubiquitous sensor network technology has spread vastly. The ubiquitous sensor networks are widely de- ployed in factory auttxnation as they provide effective measuring solution for instruments. The wired/wireless network module, which provides the interface to connect to the u-sensor network, is needed but there is no perfect standardization about the interface. In this situation, the interface compatibility between measuring instrument can be maintained using the IEEEI451 international standard. In this paper, the Wireless Transducer Interface Mcduie （WTIM） based on IEEE1451.5 was designed. It coxnects to the measuring instnmnt, like the muiti-meter, power meter, and etc., to support the RS232 interface. As these devices cannot connect to network without a mod- ule, we use the WTIM to help these devices connect to network sys- ton. Its ftmction was verified through the ubiquitous network connection and data transfer between monitoring PC and measuring instrument. This technology is expected to reduce cost in order to construct the wireless industry automation system using existing devices.展开更多
Non-orthogonal multiple access (NOMA) technology has recently been widely integrated into multi-access edge computing (MEC) to support task offloading in industrial wireless networks (IWNs) with limited radio resource...Non-orthogonal multiple access (NOMA) technology has recently been widely integrated into multi-access edge computing (MEC) to support task offloading in industrial wireless networks (IWNs) with limited radio resources. This paper minimizes the system overhead regarding task processing delay and energy consumption for the IWN with hybrid NOMA and orthogonal multiple access (OMA) schemes. Specifically, we formulate the system overhead minimization (SOM) problem by considering the limited computation and communication resources and NOMA efficiency. To solve the complex mixed-integer nonconvex problem, we combine the multi-agent twin delayed deep deterministic policy gradient (MATD3) and convex optimization, namely MATD3-CO, for iterative optimization. Specifically, we first decouple SOM into two sub-problems, i.e., joint sub-channel allocation and task offloading sub-problem, and computation resource allocation sub-problem. Then, we propose MATD3 to optimize the sub-channel allocation and task offloading ratio, and employ the convex optimization to allocate the computation resource with a closed-form expression derived by the Karush-Kuhn-Tucker (KKT) conditions. The solution is obtained by iteratively solving these two sub-problems. The experimental results indicate that the MATD3-CO scheme, when compared to the benchmark schemes, significantly decreases system overhead with respect to both delay and energy consumption.展开更多
In industrial wireless networks,data transmitted from source to destination are highly repetitive.This often leads to the queuing of the data,and poor management of the queued data results in excessive delays,increase...In industrial wireless networks,data transmitted from source to destination are highly repetitive.This often leads to the queuing of the data,and poor management of the queued data results in excessive delays,increased energy consumption,and packet loss.Therefore,a nature-inspired-based Dragonfly Interaction Optimization Algorithm(DMOA)is proposed for optimization of the queue delay in industrial wireless networks.The term“interaction”herein used is the characterization of the“flying movement”of the dragonfly towards damselflies(female dragonflies)for mating.As a result,interaction is represented as the flow of transmitted data packets,or traffic,from the source to the base station.This includes each and every feature of dragonfly movement as well as awareness of the rival dragonflies,predators,and damselflies for the desired optimization of the queue delay.These features are juxtaposed as noise and interference,which are further used in the calculation of industrial wireless metrics:latency,error rate(reliability),throughput,energy efficiency,and fairness for the optimization of the queue delay.Statistical analysis,convergence analysis,the Wilcoxon test,the Friedman test,and the classical as well as the 2014 IEEE Congress of Evolutionary Computation(CEC)on the benchmark functions are also used for the evaluation of DMOA in terms of its robustness and efficiency.The results demonstrate the robustness of the proposed algorithm for both classical and benchmarking functions of the IEEE CEC 2014.Furthermore,the accuracy and efficacy of DMOA were demonstrated by means of the convergence rate,Wilcoxon testing,and ANOVA.Moreover,fairness using Jain’s index in queue delay optimization in terms of throughput and latency,along with computational complexity,is also evaluated and compared with other algorithms.Simulation results show that DMOA exceeds other bio-inspired optimization algorithms in terms of fairness in queue delay management and average packet loss.The proposed algorithm is also evaluated for the conflicting objectives at Pareto Front,and its analysis reveals that DMOA finds a compromising solution between the objectives,thereby optimizing queue delay.In addition,DMOA on the Pareto front delivers much greater performance when it comes to optimizing the queuing delay for industry wireless networks.展开更多
As industrialization and informatization becomemore deeply intertwined,industrial control networks have entered an era of intelligence.The connection between industrial control networks and the external internet is be...As industrialization and informatization becomemore deeply intertwined,industrial control networks have entered an era of intelligence.The connection between industrial control networks and the external internet is becoming increasingly close,which leads to frequent security accidents.This paper proposes a model for the industrial control network.It includes a malware containment strategy that integrates intrusion detection,quarantine,and monitoring.Basedonthismodel,the role of keynodes in the spreadofmalware is studied,a comparisonexperiment is conducted to validate the impact of the containment strategy.In addition,the dynamic behavior of the model is analyzed,the basic reproduction number is computed,and the disease-free and endemic equilibrium of the model is also obtained by the basic reproduction number.Moreover,through simulation experiments,the effectiveness of the containment strategy is validated,the influence of the relevant parameters is analyzed,and the containment strategy is optimized.In otherwords,selective immunity to key nodes can effectively suppress the spread ofmalware andmaintain the stability of industrial control systems.The earlier the immunization of key nodes,the better.Once the time exceeds the threshold,immunizing key nodes is almost ineffective.The analysis provides a better way to contain the malware in the industrial control network.展开更多
Several excellent works have been done on the industrial Internet;however,some problems are still ahead,such as reliable security,heterogeneous compatibility,and system efficiency.Information-Centric Networking(ICN),a...Several excellent works have been done on the industrial Internet;however,some problems are still ahead,such as reliable security,heterogeneous compatibility,and system efficiency.Information-Centric Networking(ICN),an emerging paradigm for the future Internet,is expected to address the challenges of the industrial Internet to some extent.An integrated architecture for industrial network and identity resolution in the industrial Internet is proposed in this paper.A framework is also designed for the ICN-based industrial Network And Named Data Networking(NDN)based factory extranet with Software-Defined Networking(SDN).Moreover,an identity resolution architecture in the industrial Internet is proposed based on ICN paradigms with separate resolution nodes or with merging resolution and routing.展开更多
The IEEE 802.15.4a standard provides a framework for low-data-rate communication systems,typically sensor networks.In this paper,we established a realistic environment for the time delay characteristic of industrial n...The IEEE 802.15.4a standard provides a framework for low-data-rate communication systems,typically sensor networks.In this paper,we established a realistic environment for the time delay characteristic of industrial network based on IEEE 802.15.4a.Several sets of practical experiments are conducted to study its various features,including the effects of 1） numeral wireless nodes,2） numeral data packets,3） data transmissions with different upper-layer protocols,4） physical distance between nodes,and 5） adding and reducing the number of the wireless nodes.The results show that IEEE 802.15.4a is suitable for some industrial applications that have more relaxed throughput requirements and time-delay.Some issues that could degrade the network performance are also discussed.展开更多
Ultra-reliable and low-latency communications(URLLC) has become a fundamental focus of future industrial wireless sensor net-works(IWSNs). With the evolution of automation and process control in industrial environment...Ultra-reliable and low-latency communications(URLLC) has become a fundamental focus of future industrial wireless sensor net-works(IWSNs). With the evolution of automation and process control in industrial environments, the need for increased reliabilityand reduced latencies in wireless communications is even pronounced. Furthermore, the 5G systems specifically target the URLLCin selected areas and industrial automation might turn into a suitable venue for future IWSNs, running 5G as a high speed inter-process linking technology. In this paper, a hybrid multi-channel scheme for performance and throughput enhancement of IWSNsis proposed. The scheme utilizes the multiple frequency channels to increase the overall throughput of the system along with theincrease in reliability. A special purpose frequency channel is defined, which facilitates the failed communications by retransmis-sions where the retransmission slots are allocated according to the priority level of failed communications of different nodes. Ascheduler is used to formulate priority based scheduling for retransmission in TDMA based communication slots of this channel.Furthermore, in carrier-sense multiple access with collision avoidance(CSMA/CA) based slots, a frequency polling is introducedto limit the collisions. Mathematical modelling for performance metrics is also presented. The performance of the proposed schemeis compared with that of IEEE802.15.4e, where the performance is evaluated on the basis of throughput, reliability and the num-ber of nodes accommodated in a cluster. The proposed scheme offers a notable increase in the reliability and throughput over theexisting IEEE802.15.4e Low Latency Deterministic Networks(LLDN) standard.展开更多
ISA100.11 a industrial wireless network standard is based on a deterministic scheduling mechanism.For the timeslot delay caused by deterministic scheduling,a routing algorithm is presented for industrial environments....ISA100.11 a industrial wireless network standard is based on a deterministic scheduling mechanism.For the timeslot delay caused by deterministic scheduling,a routing algorithm is presented for industrial environments.According to timeslot,superframe,links,channel and data retransmission of deterministic scheduling mechanisms that affect the design of the routing algorithm,the algorithm selects the link quality,timeslot delay and retransmission delay as the routing criteria and finds the optimum communication path by k shortest paths algorithm.Theoretical analysis and experimental verification show that the optimal paths selected by the algorithm not only have high link quality and low retransmission delay,but also meet the requirements of the deterministic scheduling.The algorithm can effectively solve the problem of packet loss and transmission delay during data transmission,and provide a valuable solution for efficient data transmission based on determinacy.展开更多
As an Industrial Wireless Sensor Network(IWSN)is usually deployed in a harsh or unattended environment,the privacy security of data aggregation is facing more and more challenges.Currently,the data aggregation protoco...As an Industrial Wireless Sensor Network(IWSN)is usually deployed in a harsh or unattended environment,the privacy security of data aggregation is facing more and more challenges.Currently,the data aggregation protocols mainly focus on improving the efficiency of data transmitting and aggregating,alternately,the aim at enhancing the security of data.The performances of the secure data aggregation protocols are the trade-off of several metrics,which involves the transmission/fusion,the energy efficiency and the security in Wireless Sensor Network(WSN).Unfortunately,there is no paper in systematic analysis about the performance of the secure data aggregation protocols whether in IWSN or in WSN.In consideration of IWSN,we firstly review the security requirements and techniques in WSN data aggregation in this paper.Then,we give a holistic overview of the classical secure data aggregation protocols,which are divided into three categories:hop-by-hop encrypted data aggregation,end-to-end encrypted data aggregation and unencrypted secure data aggregation.Along this way,combining with the characteristics of industrial applications,we analyze the pros and cons of the existing security schemes in each category qualitatively,and realize that the security and the energy efficiency are suitable for IWSN.Finally,we make the conclusion about the techniques and approach in these categories,and highlight the future research directions of privacy preserving data aggregation in IWSN.展开更多
Industrial wireless sensor networks adopt a hierarchical structure with large numbers of sensors and routers. Time Division Multiple Access (TDMA) is regarded as an efficient method to reduce the probability of confli...Industrial wireless sensor networks adopt a hierarchical structure with large numbers of sensors and routers. Time Division Multiple Access (TDMA) is regarded as an efficient method to reduce the probability of confliction. In the intra-cluster part, the random color selection method is effective in reducing the retry times in an application. In the inter-cluster part, a quick assign algorithm and a dynamic maximum link algorithm are proposed to meet the quick networking or minimum frame size requirements. In the simulation, the dynamic maximum link algorithm produces higher reductions in the frame length than the quick assign algorithm. When the number of routers is 140, the total number of time slots is reduced by 25%. However, the first algorithm needs more control messages, and the average difference in the number of control messages is 3 410. Consequently, the dynamic maximum link algorithm is utilized for adjusting the link schedule to the minimum delay with a relatively high throughput rate, and the quick assign algorithm is utilized for speeding up the networking process.展开更多
Energy supply is one of the most critical challenges of wireless sensor networks(WSNs)and industrial wireless sensor networks(IWSNs).While research on coverage optimization problem(COP)centers on the network’s monito...Energy supply is one of the most critical challenges of wireless sensor networks(WSNs)and industrial wireless sensor networks(IWSNs).While research on coverage optimization problem(COP)centers on the network’s monitoring coverage,this research focuses on the power banks’energy supply coverage.The study of 2-D and 3-D spaces is typical in IWSN,with the realistic environment being more complex with obstacles(i.e.,machines).A 3-D surface is the field of interest(FOI)in this work with the established hybrid power bank deployment model for the energy supply COP optimization of IWSN.The hybrid power bank deployment model is highly adaptive and flexible for new or existing plants already using the IWSN system.The model improves the power supply to a more considerable extent with the least number of power bank deployments.The main innovation in this work is the utilization of a more practical surface model with obstacles and training while improving the convergence speed and quality of the heuristic algorithm.An overall probabilistic coverage rate analysis of every point on the FOI is provided,not limiting the scope to target points or areas.Bresenham’s algorithm is extended from 2-D to 3-D surface to enhance the probabilistic covering model for coverage measurement.A dynamic search strategy(DSS)is proposed to modify the artificial bee colony(ABC)and balance the exploration and exploitation ability for better convergence toward eliminating NP-hard deployment problems.Further,the cellular automata(CA)is utilized to enhance the convergence speed.The case study based on two typical FOI in the IWSN shows that the CA scheme effectively speeds up the optimization process.Comparative experiments are conducted on four benchmark functions to validate the effectiveness of the proposed method.The experimental results show that the proposed algorithm outperforms the ABC and gbest-guided ABC(GABC)algorithms.The results show that the proposed energy coverage optimization method based on the hybrid power bank deployment model generates more accurate results than the results obtained by similar algorithms(i.e.,ABC,GABC).The proposed model is,therefore,effective and efficient for optimization in the IWSN.展开更多
In this paper,we propose a intrusion detection algorithm based on auto-encoder and three-way decisions(AE-3WD)for industrial control networks,aiming at the security problem of industrial control network.The ideology o...In this paper,we propose a intrusion detection algorithm based on auto-encoder and three-way decisions(AE-3WD)for industrial control networks,aiming at the security problem of industrial control network.The ideology of deep learning is similar to the idea of intrusion detection.Deep learning is a kind of intelligent algorithm and has the ability of automatically learning.It uses self-learning to enhance the experience and dynamic classification capabilities.We use deep learning to improve the intrusion detection rate and reduce the false alarm rate through learning,a denoising AutoEncoder and three-way decisions intrusion detection method AE-3WD is proposed to improve intrusion detection accuracy.In the processing,deep learning AutoEncoder is used to extract the features of high-dimensional data by combining the coefficient penalty and reconstruction loss function of the encode layer during the training mode.A multi-feature space can be constructed by multiple feature extractions from AutoEncoder,and then a decision for intrusion behavior or normal behavior is made by three-way decisions.NSL-KDD data sets are used to the experiments.The experiment results prove that our proposed method can extract meaningful features and effectively improve the performance of intrusion detection.展开更多
Demand response has recently become an essential means for businesses to reduce production costs in industrial chains.Meanwhile,the current industrial chain structure has also become increasingly complex,forming new c...Demand response has recently become an essential means for businesses to reduce production costs in industrial chains.Meanwhile,the current industrial chain structure has also become increasingly complex,forming new characteristics of multiplex networked industrial chains.Fluctuations in real-time electricity prices in demand response propagate through the coupling and cascading relationships within and among these network layers,resulting in negative impacts on the overall energy management cost.However,existing demand response methods based on reinforcement learning typically focus only on individual agents without considering the influence of dynamic factors on intra and inter-network relationships.This paper proposes a Layered Temporal Spatial Graph Attention(LTSGA)reinforcement learning algorithm suitable for demand response in multiplex networked industrial chains to address this issue.The algorithm first uses Long Short-Term Memory(LSTM)to learn the dynamic temporal characteristics of electricity prices for decision-making.Then,LTSGA incorporates a layered spatial graph attention model to evaluate the impact of dynamic factors on the complex multiplex networked industrial chain structure.Experiments demonstrate that the proposed LTSGA approach effectively characterizes the influence of dynamic factors on intra-and inter-network relationships within the multiplex industrial chain,enhancing convergence speed and algorithm performance compared with existing state-of-the-art algorithms.展开更多
With the advancement of electronic information technology and the growth of the intelligent industry,the industrial sector has undergone a shift from simplex,linear,and vertical chains to complex,multi-level,and multi...With the advancement of electronic information technology and the growth of the intelligent industry,the industrial sector has undergone a shift from simplex,linear,and vertical chains to complex,multi-level,and multi-dimensional networked industrial chains.In order to enhance energy efficiency in multiplex networked industrial chains under time-of-use price,a coarse time granularity task scheduling approach has been adopted.This approach adjusts the distribution of electricity supply based on task deadlines,dividing it into longer periods to facilitate batch access to task information.However,traditional simplex-network task assignment optimization methods are unable to achieve a globally optimal solution for cross-layer links in multiplex networked industrial chains.Existing solutions struggle to balance execution costs and completion efficiency in time-of-use price scenarios.Therefore,this paper presents a mixed-integer linear programming model for solving the problem scenario and two algorithms:an exact algorithm based on the branch-and-bound method and a multi-objective heuristic algorithm based on cross-layer policy propagation.These algorithms are designed to adapt to small-scale and large-scale problem scenarios under coarse time granularity.Through extensive simulation experiments and theoretical analysis,the proposed methods effectively optimize the energy and time costs associated with the task execution.展开更多
Based on the data of listed companies in the core industry chain of China's new energy vehicles in 2015 and 2021,this paper constructs their industrial network from the perspective of the value chain,and uses meth...Based on the data of listed companies in the core industry chain of China's new energy vehicles in 2015 and 2021,this paper constructs their industrial network from the perspective of the value chain,and uses methods such as social network and negative binomial regression model to study the characteristics,evolution,differences,and formation mechanisms of different value chain networks.The results show that:(1)R&D-oriented,production-oriented,and service-oriented networks share several common features:These networks are simultaneously expanding in scale and transitioning towards more efficient“small world”network;The degree distribution in these networks follows a power-law distribution,indicating a scale-free network structure;There is a decrease in the power-law exponent of network's degree distribution,indicating an increase in network heterogeneity.Furthermore,there is a significant positive correlation between the degrees of nodes in networks with diverse value chains,suggesting that the same node holds a similar level of significance across different networks.(2)The number of power-prestige,power and prestige nodes increases in the networks of all value chain segments,except in the service-oriented network,where there are no power nodes.In each value chain network,these nodes have different agglomeration directions:In R&D-oriented network,the nodes tend to cluster around headquarters and high-level cities.In contrast,service-oriented network shows a concentration of nodes in municipalities,sub-provincial and provincial capitals.Similarly,production-oriented network demonstrates a clustering of nodes in traditional production bases.(3)Different value-added segments of industry form different types of agglomeration in pursuit of different factor endowments and agglomeration effect,and form the spatial structure of the strongest connection industrial network with different characteristics.The R&D-oriented networks have always been an integrated and closely connected multiple core-periphery structure community with the influence of social,technological and geographical proximities;Transformation of service-oriented network from an integrated and closely connected multiple core-periphery structure community to a multiple core-semi-periphery-periphery structure community with the influence of social,geographical and institutional proximities;Transformation of production-oriented network from the partially integrated and localized core-periphery structure community to the more decentralized multiple independent core-periphery structure community with the influence of the social,institutional of administrative boundaries and geographical proximities.展开更多
Industries with network characteristics always have some special features, which differ from the ordinary business companies. Some scholars hold the theoretical viewpoint that these industries bear the characteristics...Industries with network characteristics always have some special features, which differ from the ordinary business companies. Some scholars hold the theoretical viewpoint that these industries bear the characteristics of natural monopoly, externality, measurement difficulty, etc. However, all these theories can explain why the network industries, especially prominent in transportation industries, are confronted with many difficulties in their process of reform and reorganization. But, there is something deep-seated that can explain why network industries such as railway, highway, aviation, telecommunication, water, gas, etc. have the characteristics of natural monopoly. The paper holds that： （1） Shared property in transportation industries such as the network infrastructure, station and marshalling yard, dispatch and control right, serves more than two enterprises or even hundreds of relative enterprises. （2） Shared property makes it possible for great amount of product quantity to share the sunken cost. Therefore, economy of scale and economy of scope thus exist in transportation sectors, which is called network economy. （3） From the input and output relationships in transportation industries with network features, there exists a law of increasing returns to scale, which is opposite to the classic economy theory that diminishing returns to scale will appear finally. Why？ It is because of the existence of shared property. Not only production cost, but also the transaction cost among transportation enterprises can be reduced. （4） We establish a quantitative model to testify the theory. The implication is that, the lack of incentive allocation is, if not all, one reason causing the usage inefficiency of the rights concerned. The low efficiency manifests in two aspects： the first one is the organization boundary, that is, transportation enterprises are not real enterprises at present. The second one is the so-called mixed task equilibrium of railway affairs. We haven＇t separated the shared property from the private ones.展开更多
Universal service obligation of network industries, such as telecommunication, electric power, post, railway, and aviation, has greatly hampered the progress of their marketization reform. Establishing universal servi...Universal service obligation of network industries, such as telecommunication, electric power, post, railway, and aviation, has greatly hampered the progress of their marketization reform. Establishing universal service fund could be an efficient solution. This paper provides a method to calculate the charging rate, imposing and allowancing range of universal service fund for network industries, it also proves the feasibility of accomplishing universal service through universal service fund in network industries.展开更多
Smart specialization is a regional development strategy that identifies regional innovation advantages through the analysis of cluster networks,while strengthening both intra-cluster and inter-cluster technological li...Smart specialization is a regional development strategy that identifies regional innovation advantages through the analysis of cluster networks,while strengthening both intra-cluster and inter-cluster technological linkages to promote coordinated regional development.Drawing on branch office flow and patent cooperation data,and employing methods such as the Expectation-Maximization(EM)clustering algorithm and the‘Product Space’approach,this study investigates innovation and technological linkages both within and across industrial clusters.The key findings are as follows.First,Jiangsu’s clusters demonstrate two patterns:closely integrated industrial networks in southern cities like Suzhou,fostering strong industrial resilience,and distinct technological boundaries in northern and central cities like Yancheng,resulting in weaker integration.Second,the cluster network exhibits a single-core structure at the municipal level,centered around Nanjing,with a multi-tiered hierarchy at the district level.Third,innovation linkages between clusters follow a dual-core structure,with Nanjing and Suzhou as central hubs.In this structure,large enterprises in Nanjing and small and medium-sized enterprises(SMEs)in Suzhou reflect complementary industrial characteristics.Finally,both technology-intensive and low-tech manufacturing industries show a higher propensity for cross-regional innovation,with some cities demonstrating significant advantages in high-tech industries.Grounded in the framework of smart specialization,this study conducts an in-depth analysis of innovation and technological linkages within cluster networks at the industrial level,offering scientific insights to support the localized implementation of smart specialization strategies in the Chinese context.展开更多
In many IIoT architectures,various devices connect to the edge cloud via gateway systems.For data processing,numerous data are delivered to the edge cloud.Delivering data to an appropriate edge cloud is critical to im...In many IIoT architectures,various devices connect to the edge cloud via gateway systems.For data processing,numerous data are delivered to the edge cloud.Delivering data to an appropriate edge cloud is critical to improve IIoT service efficiency.There are two types of costs for this kind of IoT network:a communication cost and a computing cost.For service efficiency,the communication cost of data transmission should be minimized,and the computing cost in the edge cloud should be also minimized.Therefore,in this paper,the communication cost for data transmission is defined as the delay factor,and the computing cost in the edge cloud is defined as the waiting time of the computing intensity.The proposed method selects an edge cloud that minimizes the total cost of the communication and computing costs.That is,a device chooses a routing path to the selected edge cloud based on the costs.The proposed method controls the data flows in a mesh-structured network and appropriately distributes the data processing load.The performance of the proposed method is validated through extensive computer simulation.When the transition probability from good to bad is 0.3 and the transition probability from bad to good is 0.7 in wireless and edge cloud states,the proposed method reduced both the average delay and the service pause counts to about 25%of the existing method.展开更多
基金supported by the GRRC program of Gyeong-gi province:[GRRC Hanyang2009-B01,Building/Home USN Technology for Smart Grid]
文摘Recently, the use of ubiquitous sensor network technology has spread vastly. The ubiquitous sensor networks are widely de- ployed in factory auttxnation as they provide effective measuring solution for instruments. The wired/wireless network module, which provides the interface to connect to the u-sensor network, is needed but there is no perfect standardization about the interface. In this situation, the interface compatibility between measuring instrument can be maintained using the IEEEI451 international standard. In this paper, the Wireless Transducer Interface Mcduie （WTIM） based on IEEE1451.5 was designed. It coxnects to the measuring instnmnt, like the muiti-meter, power meter, and etc., to support the RS232 interface. As these devices cannot connect to network without a mod- ule, we use the WTIM to help these devices connect to network sys- ton. Its ftmction was verified through the ubiquitous network connection and data transfer between monitoring PC and measuring instrument. This technology is expected to reduce cost in order to construct the wireless industry automation system using existing devices.
基金supported by the National Natural Science Foundation of China under Grants 92267108,62173322 and 61821005the Science and Technology Program of Liaoning Province under Grants 2023JH3/10200004 and 2022JH25/10100005.
文摘Non-orthogonal multiple access (NOMA) technology has recently been widely integrated into multi-access edge computing (MEC) to support task offloading in industrial wireless networks (IWNs) with limited radio resources. This paper minimizes the system overhead regarding task processing delay and energy consumption for the IWN with hybrid NOMA and orthogonal multiple access (OMA) schemes. Specifically, we formulate the system overhead minimization (SOM) problem by considering the limited computation and communication resources and NOMA efficiency. To solve the complex mixed-integer nonconvex problem, we combine the multi-agent twin delayed deep deterministic policy gradient (MATD3) and convex optimization, namely MATD3-CO, for iterative optimization. Specifically, we first decouple SOM into two sub-problems, i.e., joint sub-channel allocation and task offloading sub-problem, and computation resource allocation sub-problem. Then, we propose MATD3 to optimize the sub-channel allocation and task offloading ratio, and employ the convex optimization to allocate the computation resource with a closed-form expression derived by the Karush-Kuhn-Tucker (KKT) conditions. The solution is obtained by iteratively solving these two sub-problems. The experimental results indicate that the MATD3-CO scheme, when compared to the benchmark schemes, significantly decreases system overhead with respect to both delay and energy consumption.
基金supported by Priority Research Centers Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education,Science and Technology(2018R1A6A1A03024003)the MSIT(Ministry of Science and ICT),Korea,under the Innovative Human Resource Development for Local Intellectualization support program(IITP-2023-2020-0-01612)supervised by the IITP(Institute for Information&communications TechnologyPlanning&Evaluation).
文摘In industrial wireless networks,data transmitted from source to destination are highly repetitive.This often leads to the queuing of the data,and poor management of the queued data results in excessive delays,increased energy consumption,and packet loss.Therefore,a nature-inspired-based Dragonfly Interaction Optimization Algorithm(DMOA)is proposed for optimization of the queue delay in industrial wireless networks.The term“interaction”herein used is the characterization of the“flying movement”of the dragonfly towards damselflies(female dragonflies)for mating.As a result,interaction is represented as the flow of transmitted data packets,or traffic,from the source to the base station.This includes each and every feature of dragonfly movement as well as awareness of the rival dragonflies,predators,and damselflies for the desired optimization of the queue delay.These features are juxtaposed as noise and interference,which are further used in the calculation of industrial wireless metrics:latency,error rate(reliability),throughput,energy efficiency,and fairness for the optimization of the queue delay.Statistical analysis,convergence analysis,the Wilcoxon test,the Friedman test,and the classical as well as the 2014 IEEE Congress of Evolutionary Computation(CEC)on the benchmark functions are also used for the evaluation of DMOA in terms of its robustness and efficiency.The results demonstrate the robustness of the proposed algorithm for both classical and benchmarking functions of the IEEE CEC 2014.Furthermore,the accuracy and efficacy of DMOA were demonstrated by means of the convergence rate,Wilcoxon testing,and ANOVA.Moreover,fairness using Jain’s index in queue delay optimization in terms of throughput and latency,along with computational complexity,is also evaluated and compared with other algorithms.Simulation results show that DMOA exceeds other bio-inspired optimization algorithms in terms of fairness in queue delay management and average packet loss.The proposed algorithm is also evaluated for the conflicting objectives at Pareto Front,and its analysis reveals that DMOA finds a compromising solution between the objectives,thereby optimizing queue delay.In addition,DMOA on the Pareto front delivers much greater performance when it comes to optimizing the queuing delay for industry wireless networks.
基金Scientific Research Project of Liaoning Province Education Department,Code:LJKQZ20222457&LJKMZ20220781Liaoning Province Nature Fund Project,Code:No.2022-MS-291.
文摘As industrialization and informatization becomemore deeply intertwined,industrial control networks have entered an era of intelligence.The connection between industrial control networks and the external internet is becoming increasingly close,which leads to frequent security accidents.This paper proposes a model for the industrial control network.It includes a malware containment strategy that integrates intrusion detection,quarantine,and monitoring.Basedonthismodel,the role of keynodes in the spreadofmalware is studied,a comparisonexperiment is conducted to validate the impact of the containment strategy.In addition,the dynamic behavior of the model is analyzed,the basic reproduction number is computed,and the disease-free and endemic equilibrium of the model is also obtained by the basic reproduction number.Moreover,through simulation experiments,the effectiveness of the containment strategy is validated,the influence of the relevant parameters is analyzed,and the containment strategy is optimized.In otherwords,selective immunity to key nodes can effectively suppress the spread ofmalware andmaintain the stability of industrial control systems.The earlier the immunization of key nodes,the better.Once the time exceeds the threshold,immunizing key nodes is almost ineffective.The analysis provides a better way to contain the malware in the industrial control network.
基金supported in part by National Key Research&Development Project(Grant No.2019YFB1804400)the MIIT of China 2019(Innovative Identification and Resolution System for Industrial Internet of Things).
文摘Several excellent works have been done on the industrial Internet;however,some problems are still ahead,such as reliable security,heterogeneous compatibility,and system efficiency.Information-Centric Networking(ICN),an emerging paradigm for the future Internet,is expected to address the challenges of the industrial Internet to some extent.An integrated architecture for industrial network and identity resolution in the industrial Internet is proposed in this paper.A framework is also designed for the ICN-based industrial Network And Named Data Networking(NDN)based factory extranet with Software-Defined Networking(SDN).Moreover,an identity resolution architecture in the industrial Internet is proposed based on ICN paradigms with separate resolution nodes or with merging resolution and routing.
基金supported by National High Technology Research and Development Program of China (863 Program)(No. 2007AA04Z174,No. 2006AA04030405)National Natural Science Foundation of China (No. 61074032,No. 60834002)
文摘The IEEE 802.15.4a standard provides a framework for low-data-rate communication systems,typically sensor networks.In this paper,we established a realistic environment for the time delay characteristic of industrial network based on IEEE 802.15.4a.Several sets of practical experiments are conducted to study its various features,including the effects of 1） numeral wireless nodes,2） numeral data packets,3） data transmissions with different upper-layer protocols,4） physical distance between nodes,and 5） adding and reducing the number of the wireless nodes.The results show that IEEE 802.15.4a is suitable for some industrial applications that have more relaxed throughput requirements and time-delay.Some issues that could degrade the network performance are also discussed.
文摘Ultra-reliable and low-latency communications(URLLC) has become a fundamental focus of future industrial wireless sensor net-works(IWSNs). With the evolution of automation and process control in industrial environments, the need for increased reliabilityand reduced latencies in wireless communications is even pronounced. Furthermore, the 5G systems specifically target the URLLCin selected areas and industrial automation might turn into a suitable venue for future IWSNs, running 5G as a high speed inter-process linking technology. In this paper, a hybrid multi-channel scheme for performance and throughput enhancement of IWSNsis proposed. The scheme utilizes the multiple frequency channels to increase the overall throughput of the system along with theincrease in reliability. A special purpose frequency channel is defined, which facilitates the failed communications by retransmis-sions where the retransmission slots are allocated according to the priority level of failed communications of different nodes. Ascheduler is used to formulate priority based scheduling for retransmission in TDMA based communication slots of this channel.Furthermore, in carrier-sense multiple access with collision avoidance(CSMA/CA) based slots, a frequency polling is introducedto limit the collisions. Mathematical modelling for performance metrics is also presented. The performance of the proposed schemeis compared with that of IEEE802.15.4e, where the performance is evaluated on the basis of throughput, reliability and the num-ber of nodes accommodated in a cluster. The proposed scheme offers a notable increase in the reliability and throughput over theexisting IEEE802.15.4e Low Latency Deterministic Networks(LLDN) standard.
基金Supported by the National Natural Science Foundation of China(No.61301125)the National High Technology Research and Development Programme of China(No.0AA0401028003)+2 种基金National Science and Technology Major Project(No.2013ZX03005005)the Fundamental and Advanced Research Program of Chongqing(No.cstc2013jcyjA40008)the Youth Top-notch Talent Support Program of Chongqing(No.2013-139)
文摘ISA100.11 a industrial wireless network standard is based on a deterministic scheduling mechanism.For the timeslot delay caused by deterministic scheduling,a routing algorithm is presented for industrial environments.According to timeslot,superframe,links,channel and data retransmission of deterministic scheduling mechanisms that affect the design of the routing algorithm,the algorithm selects the link quality,timeslot delay and retransmission delay as the routing criteria and finds the optimum communication path by k shortest paths algorithm.Theoretical analysis and experimental verification show that the optimal paths selected by the algorithm not only have high link quality and low retransmission delay,but also meet the requirements of the deterministic scheduling.The algorithm can effectively solve the problem of packet loss and transmission delay during data transmission,and provide a valuable solution for efficient data transmission based on determinacy.
基金partially supported by the National Natural Science Foundation of China(61571004)the Shanghai Natural Science Foundation(No.17ZR1429100)+1 种基金the National Science and Technology Major Project of China(No.2018ZX03001017-004)the Scientific Instrument Developing Project of the Chinese Academy of Sciences(No.YJKYYQ20170074).
文摘As an Industrial Wireless Sensor Network(IWSN)is usually deployed in a harsh or unattended environment,the privacy security of data aggregation is facing more and more challenges.Currently,the data aggregation protocols mainly focus on improving the efficiency of data transmitting and aggregating,alternately,the aim at enhancing the security of data.The performances of the secure data aggregation protocols are the trade-off of several metrics,which involves the transmission/fusion,the energy efficiency and the security in Wireless Sensor Network(WSN).Unfortunately,there is no paper in systematic analysis about the performance of the secure data aggregation protocols whether in IWSN or in WSN.In consideration of IWSN,we firstly review the security requirements and techniques in WSN data aggregation in this paper.Then,we give a holistic overview of the classical secure data aggregation protocols,which are divided into three categories:hop-by-hop encrypted data aggregation,end-to-end encrypted data aggregation and unencrypted secure data aggregation.Along this way,combining with the characteristics of industrial applications,we analyze the pros and cons of the existing security schemes in each category qualitatively,and realize that the security and the energy efficiency are suitable for IWSN.Finally,we make the conclusion about the techniques and approach in these categories,and highlight the future research directions of privacy preserving data aggregation in IWSN.
基金supported by Beijing Education and Scientific Research Programthe National High Technical Research and Development Program of China (863 Program) under Grant No. 2011AA040101+2 种基金the National Natural Science Foundation of China under Grants No. 61173150, No. 61003251Beijing Science and Technology Program under Grant No. Z111100054011078the State Scholarship Fund
文摘Industrial wireless sensor networks adopt a hierarchical structure with large numbers of sensors and routers. Time Division Multiple Access (TDMA) is regarded as an efficient method to reduce the probability of confliction. In the intra-cluster part, the random color selection method is effective in reducing the retry times in an application. In the inter-cluster part, a quick assign algorithm and a dynamic maximum link algorithm are proposed to meet the quick networking or minimum frame size requirements. In the simulation, the dynamic maximum link algorithm produces higher reductions in the frame length than the quick assign algorithm. When the number of routers is 140, the total number of time slots is reduced by 25%. However, the first algorithm needs more control messages, and the average difference in the number of control messages is 3 410. Consequently, the dynamic maximum link algorithm is utilized for adjusting the link schedule to the minimum delay with a relatively high throughput rate, and the quick assign algorithm is utilized for speeding up the networking process.
文摘Energy supply is one of the most critical challenges of wireless sensor networks(WSNs)and industrial wireless sensor networks(IWSNs).While research on coverage optimization problem(COP)centers on the network’s monitoring coverage,this research focuses on the power banks’energy supply coverage.The study of 2-D and 3-D spaces is typical in IWSN,with the realistic environment being more complex with obstacles(i.e.,machines).A 3-D surface is the field of interest(FOI)in this work with the established hybrid power bank deployment model for the energy supply COP optimization of IWSN.The hybrid power bank deployment model is highly adaptive and flexible for new or existing plants already using the IWSN system.The model improves the power supply to a more considerable extent with the least number of power bank deployments.The main innovation in this work is the utilization of a more practical surface model with obstacles and training while improving the convergence speed and quality of the heuristic algorithm.An overall probabilistic coverage rate analysis of every point on the FOI is provided,not limiting the scope to target points or areas.Bresenham’s algorithm is extended from 2-D to 3-D surface to enhance the probabilistic covering model for coverage measurement.A dynamic search strategy(DSS)is proposed to modify the artificial bee colony(ABC)and balance the exploration and exploitation ability for better convergence toward eliminating NP-hard deployment problems.Further,the cellular automata(CA)is utilized to enhance the convergence speed.The case study based on two typical FOI in the IWSN shows that the CA scheme effectively speeds up the optimization process.Comparative experiments are conducted on four benchmark functions to validate the effectiveness of the proposed method.The experimental results show that the proposed algorithm outperforms the ABC and gbest-guided ABC(GABC)algorithms.The results show that the proposed energy coverage optimization method based on the hybrid power bank deployment model generates more accurate results than the results obtained by similar algorithms(i.e.,ABC,GABC).The proposed model is,therefore,effective and efficient for optimization in the IWSN.
基金supported by National Nature Science Foundation of China (Grant No.61471182)Postgraduate Research&Practice Innovation Program of Jiangsu Province (Grant No.KYCX20_2993)Jiangsu postgraduate research innovation project (SJCX18_0784)。
文摘In this paper,we propose a intrusion detection algorithm based on auto-encoder and three-way decisions(AE-3WD)for industrial control networks,aiming at the security problem of industrial control network.The ideology of deep learning is similar to the idea of intrusion detection.Deep learning is a kind of intelligent algorithm and has the ability of automatically learning.It uses self-learning to enhance the experience and dynamic classification capabilities.We use deep learning to improve the intrusion detection rate and reduce the false alarm rate through learning,a denoising AutoEncoder and three-way decisions intrusion detection method AE-3WD is proposed to improve intrusion detection accuracy.In the processing,deep learning AutoEncoder is used to extract the features of high-dimensional data by combining the coefficient penalty and reconstruction loss function of the encode layer during the training mode.A multi-feature space can be constructed by multiple feature extractions from AutoEncoder,and then a decision for intrusion behavior or normal behavior is made by three-way decisions.NSL-KDD data sets are used to the experiments.The experiment results prove that our proposed method can extract meaningful features and effectively improve the performance of intrusion detection.
基金supported by the National Key Research and Development Program of China(No.2022YFB3304400)the National Natural Science Foundation of China(Nos.62303111,62076060,and 61932007)+2 种基金the Key Research and Development Program of Jiangsu Province of China(No.BE2022157)the Defense Industrial Technology Development Program(No.JCKY2021214B002)the Fellowship of China Postdoctoral Science Foundation(No.2022M720715).
文摘Demand response has recently become an essential means for businesses to reduce production costs in industrial chains.Meanwhile,the current industrial chain structure has also become increasingly complex,forming new characteristics of multiplex networked industrial chains.Fluctuations in real-time electricity prices in demand response propagate through the coupling and cascading relationships within and among these network layers,resulting in negative impacts on the overall energy management cost.However,existing demand response methods based on reinforcement learning typically focus only on individual agents without considering the influence of dynamic factors on intra and inter-network relationships.This paper proposes a Layered Temporal Spatial Graph Attention(LTSGA)reinforcement learning algorithm suitable for demand response in multiplex networked industrial chains to address this issue.The algorithm first uses Long Short-Term Memory(LSTM)to learn the dynamic temporal characteristics of electricity prices for decision-making.Then,LTSGA incorporates a layered spatial graph attention model to evaluate the impact of dynamic factors on the complex multiplex networked industrial chain structure.Experiments demonstrate that the proposed LTSGA approach effectively characterizes the influence of dynamic factors on intra-and inter-network relationships within the multiplex industrial chain,enhancing convergence speed and algorithm performance compared with existing state-of-the-art algorithms.
基金supported by the National Key Research and Development Program of China(No.2022YFB3304400)the National Natural Science Foundation of China(Nos.62303111,62076060,and 61932007)+2 种基金the Key Research and Development Program of Jiangsu Province of China(No.BE2022157)the Defense Industrial Technology Development Program(No.JCKY2021214B002)the Fellowship of China Postdoctoral Science Foundation(No.2022M720715).
文摘With the advancement of electronic information technology and the growth of the intelligent industry,the industrial sector has undergone a shift from simplex,linear,and vertical chains to complex,multi-level,and multi-dimensional networked industrial chains.In order to enhance energy efficiency in multiplex networked industrial chains under time-of-use price,a coarse time granularity task scheduling approach has been adopted.This approach adjusts the distribution of electricity supply based on task deadlines,dividing it into longer periods to facilitate batch access to task information.However,traditional simplex-network task assignment optimization methods are unable to achieve a globally optimal solution for cross-layer links in multiplex networked industrial chains.Existing solutions struggle to balance execution costs and completion efficiency in time-of-use price scenarios.Therefore,this paper presents a mixed-integer linear programming model for solving the problem scenario and two algorithms:an exact algorithm based on the branch-and-bound method and a multi-objective heuristic algorithm based on cross-layer policy propagation.These algorithms are designed to adapt to small-scale and large-scale problem scenarios under coarse time granularity.Through extensive simulation experiments and theoretical analysis,the proposed methods effectively optimize the energy and time costs associated with the task execution.
基金National Natural Science Foundation of China,No.41971198The Second Tibetan Plateau Scientific Expedition and Research Program,No.2019QZKK1005。
文摘Based on the data of listed companies in the core industry chain of China's new energy vehicles in 2015 and 2021,this paper constructs their industrial network from the perspective of the value chain,and uses methods such as social network and negative binomial regression model to study the characteristics,evolution,differences,and formation mechanisms of different value chain networks.The results show that:(1)R&D-oriented,production-oriented,and service-oriented networks share several common features:These networks are simultaneously expanding in scale and transitioning towards more efficient“small world”network;The degree distribution in these networks follows a power-law distribution,indicating a scale-free network structure;There is a decrease in the power-law exponent of network's degree distribution,indicating an increase in network heterogeneity.Furthermore,there is a significant positive correlation between the degrees of nodes in networks with diverse value chains,suggesting that the same node holds a similar level of significance across different networks.(2)The number of power-prestige,power and prestige nodes increases in the networks of all value chain segments,except in the service-oriented network,where there are no power nodes.In each value chain network,these nodes have different agglomeration directions:In R&D-oriented network,the nodes tend to cluster around headquarters and high-level cities.In contrast,service-oriented network shows a concentration of nodes in municipalities,sub-provincial and provincial capitals.Similarly,production-oriented network demonstrates a clustering of nodes in traditional production bases.(3)Different value-added segments of industry form different types of agglomeration in pursuit of different factor endowments and agglomeration effect,and form the spatial structure of the strongest connection industrial network with different characteristics.The R&D-oriented networks have always been an integrated and closely connected multiple core-periphery structure community with the influence of social,technological and geographical proximities;Transformation of service-oriented network from an integrated and closely connected multiple core-periphery structure community to a multiple core-semi-periphery-periphery structure community with the influence of social,geographical and institutional proximities;Transformation of production-oriented network from the partially integrated and localized core-periphery structure community to the more decentralized multiple independent core-periphery structure community with the influence of the social,institutional of administrative boundaries and geographical proximities.
文摘Industries with network characteristics always have some special features, which differ from the ordinary business companies. Some scholars hold the theoretical viewpoint that these industries bear the characteristics of natural monopoly, externality, measurement difficulty, etc. However, all these theories can explain why the network industries, especially prominent in transportation industries, are confronted with many difficulties in their process of reform and reorganization. But, there is something deep-seated that can explain why network industries such as railway, highway, aviation, telecommunication, water, gas, etc. have the characteristics of natural monopoly. The paper holds that： （1） Shared property in transportation industries such as the network infrastructure, station and marshalling yard, dispatch and control right, serves more than two enterprises or even hundreds of relative enterprises. （2） Shared property makes it possible for great amount of product quantity to share the sunken cost. Therefore, economy of scale and economy of scope thus exist in transportation sectors, which is called network economy. （3） From the input and output relationships in transportation industries with network features, there exists a law of increasing returns to scale, which is opposite to the classic economy theory that diminishing returns to scale will appear finally. Why？ It is because of the existence of shared property. Not only production cost, but also the transaction cost among transportation enterprises can be reduced. （4） We establish a quantitative model to testify the theory. The implication is that, the lack of incentive allocation is, if not all, one reason causing the usage inefficiency of the rights concerned. The low efficiency manifests in two aspects： the first one is the organization boundary, that is, transportation enterprises are not real enterprises at present. The second one is the so-called mixed task equilibrium of railway affairs. We haven＇t separated the shared property from the private ones.
文摘Universal service obligation of network industries, such as telecommunication, electric power, post, railway, and aviation, has greatly hampered the progress of their marketization reform. Establishing universal service fund could be an efficient solution. This paper provides a method to calculate the charging rate, imposing and allowancing range of universal service fund for network industries, it also proves the feasibility of accomplishing universal service through universal service fund in network industries.
基金Under the auspices of the National Natural Science Foundation of China(No.42330510,41871160,42371262)。
文摘Smart specialization is a regional development strategy that identifies regional innovation advantages through the analysis of cluster networks,while strengthening both intra-cluster and inter-cluster technological linkages to promote coordinated regional development.Drawing on branch office flow and patent cooperation data,and employing methods such as the Expectation-Maximization(EM)clustering algorithm and the‘Product Space’approach,this study investigates innovation and technological linkages both within and across industrial clusters.The key findings are as follows.First,Jiangsu’s clusters demonstrate two patterns:closely integrated industrial networks in southern cities like Suzhou,fostering strong industrial resilience,and distinct technological boundaries in northern and central cities like Yancheng,resulting in weaker integration.Second,the cluster network exhibits a single-core structure at the municipal level,centered around Nanjing,with a multi-tiered hierarchy at the district level.Third,innovation linkages between clusters follow a dual-core structure,with Nanjing and Suzhou as central hubs.In this structure,large enterprises in Nanjing and small and medium-sized enterprises(SMEs)in Suzhou reflect complementary industrial characteristics.Finally,both technology-intensive and low-tech manufacturing industries show a higher propensity for cross-regional innovation,with some cities demonstrating significant advantages in high-tech industries.Grounded in the framework of smart specialization,this study conducts an in-depth analysis of innovation and technological linkages within cluster networks at the industrial level,offering scientific insights to support the localized implementation of smart specialization strategies in the Chinese context.
基金supported by the National Research Foundation of Korea (NRF) grant funded by the Korea Government (MSIT) (No.2021R1C1C1013133)supported by the Institute of Information and Communications Technology Planning and Evaluation (IITP)grant funded by the Korea Government (MSIT) (RS-2022-00167197,Development of Intelligent 5G/6G Infrastructure Technology for The Smart City)supported by the Soonchunhyang University Research Fund.
文摘In many IIoT architectures,various devices connect to the edge cloud via gateway systems.For data processing,numerous data are delivered to the edge cloud.Delivering data to an appropriate edge cloud is critical to improve IIoT service efficiency.There are two types of costs for this kind of IoT network:a communication cost and a computing cost.For service efficiency,the communication cost of data transmission should be minimized,and the computing cost in the edge cloud should be also minimized.Therefore,in this paper,the communication cost for data transmission is defined as the delay factor,and the computing cost in the edge cloud is defined as the waiting time of the computing intensity.The proposed method selects an edge cloud that minimizes the total cost of the communication and computing costs.That is,a device chooses a routing path to the selected edge cloud based on the costs.The proposed method controls the data flows in a mesh-structured network and appropriately distributes the data processing load.The performance of the proposed method is validated through extensive computer simulation.When the transition probability from good to bad is 0.3 and the transition probability from bad to good is 0.7 in wireless and edge cloud states,the proposed method reduced both the average delay and the service pause counts to about 25%of the existing method.
