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Design space exploration (DSE) of cyber-physical production systems (CPPS) is a search problem in the space of potential compositional configurations. Current design methodologies follow the separated design paradigm in which the architecture, control, and scheduling are separately designed. Optimization of each part considers only the corresponding goals of interest and overlooks other aspects by adopting gross assumptions, which makes it difficult to determine the global optimal solution for a given system. To address this problem, we propose a codesign method that considers the design spaces of architecture, control and scheduling as monolithic, mixed discrete-continuous spaces. We formulate DSE as an optimization problem and propose a generic iterative algorithm scheme involving simulation in-the-loop to solve the above new problem. To illustrate the effectiveness of the proposed method, a real single-stage reducer CPPS is considered. The design results demonstrate that our method provides better solutions than does the separated design method.
Guangxi Wan; Peng Zeng. Codesign of Architecture, Control and Scheduling of Modular Cyber-Physical Production Systems for Design Space Exploration. IEEE Transactions on Industrial Informatics 2021, PP, 1 -1.
AMA StyleGuangxi Wan, Peng Zeng. Codesign of Architecture, Control and Scheduling of Modular Cyber-Physical Production Systems for Design Space Exploration. IEEE Transactions on Industrial Informatics. 2021; PP (99):1-1.
Chicago/Turabian StyleGuangxi Wan; Peng Zeng. 2021. "Codesign of Architecture, Control and Scheduling of Modular Cyber-Physical Production Systems for Design Space Exploration." IEEE Transactions on Industrial Informatics PP, no. 99: 1-1.
The Internet of vehicles (IoV) is a large information interaction network that collects information on vehicles, roads and pedestrians. One of the important uses of vehicle networks is to meet the entertainment needs of driving users through communication between vehicles and roadside units (RSUs). Due to the limited storage space of RSUs, determining the content cached in each RSU is a key challenge. With the development of 5G and video editing technology, short video systems have become increasingly popular. Current widely used cache update methods, such as partial file precaching and content popularity- and user interest-based determination, are inefficient for such systems. To solve this problem, this paper proposes a QoE-driven edge caching method for the IoV based on deep reinforcement learning. First, a class-based user interest model is established. Compared with the traditional file popularity- and user interest distribution-based cache update methods, the proposed method is more suitable for systems with a large number of small files. Second, a quality of experience (QoE)-driven RSU cache model is established based on the proposed class-based user interest model. Third, a deep reinforcement learning method is designed to address the QoE-driven RSU cache update issue effectively. The experimental results verify the effectiveness of the proposed algorithm.
Chunhe Song; Wenxiang Xu; Tingting Wu; Shimao Yu; Peng Zeng; Ning Zhang. QoE-Driven Edge Caching in Vehicle Networks Based on Deep Reinforcement Learning. IEEE Transactions on Vehicular Technology 2021, 70, 5286 -5295.
AMA StyleChunhe Song, Wenxiang Xu, Tingting Wu, Shimao Yu, Peng Zeng, Ning Zhang. QoE-Driven Edge Caching in Vehicle Networks Based on Deep Reinforcement Learning. IEEE Transactions on Vehicular Technology. 2021; 70 (6):5286-5295.
Chicago/Turabian StyleChunhe Song; Wenxiang Xu; Tingting Wu; Shimao Yu; Peng Zeng; Ning Zhang. 2021. "QoE-Driven Edge Caching in Vehicle Networks Based on Deep Reinforcement Learning." IEEE Transactions on Vehicular Technology 70, no. 6: 5286-5295.
Time-Sensitive Networking (TSN) provides end-to-end data transmission with extremely low delay and high reliability on the basis of Ethernet. It is suitable for time-sensitive applications and will be widely used in scenarios such as autonomous driving and industrial Internet. IEEE 802.1Qbv proposes a time-aware shaper mechanism, which enables switches to control the forwarding of traffic in port queues according to pre-defined Gate Control List (GCL). The length of the GCL is limited, and the previous method of scheduling cycle with a hyper period may result in a larger GCL. Based on Satisfiability Modulo Theories (SMT), we propose a TSN scheduling method for industrial scenarios and develops a series of scheduling constraints. Different from the previous scheduling methods, the method proposed in this paper adopts the base period cycle to update GCL regularly, which can effectively reduce the number of time slots in GCL and make the configuration of GCL simpler and more efficient. In addition, compared with the traditional hyper period method, the method proposed in this paper can calculate the scheduling results faster while ensuring low latency and reducing the runtime effectively.
Qing Li; Dong Li; Xi Jin; Qizhao Wang; Peng Zeng. A Simple and Efficient Time-Sensitive Networking Traffic Scheduling Method for Industrial Scenarios. Electronics 2020, 9, 2131 .
AMA StyleQing Li, Dong Li, Xi Jin, Qizhao Wang, Peng Zeng. A Simple and Efficient Time-Sensitive Networking Traffic Scheduling Method for Industrial Scenarios. Electronics. 2020; 9 (12):2131.
Chicago/Turabian StyleQing Li; Dong Li; Xi Jin; Qizhao Wang; Peng Zeng. 2020. "A Simple and Efficient Time-Sensitive Networking Traffic Scheduling Method for Industrial Scenarios." Electronics 9, no. 12: 2131.
With the increasing complexities, such as massive computing devices and strict requirements for collaboration, of industrial production systems, the concept of the cyber-physical production system (CPPS) is considered as a promising approach for addressing these challenges. However, programmability is a challenge in CPPSs. The traditional chimney style of programming requires considerable design effort from engineers to handle the spatiotemporal heterogeneity of cyber-physical model that encompasses computing, temporal, and geometric semantics along with physical dynamics. Thus, an easy-to-use programming model and an integrated programming framework that are suited to this context are required. However, the existing programming models typically fully consider only computing while only partially considering temporal characteristics, and they rarely consider geometric semantics. To solve this problem, this paper proposes a novel event-based programming model, GePro, considering the geometric spatial semantics to realize integrated programming and reduce design effort, especially the reconfiguration of adding new physical devices into the exist system. A prototype of GePro is implemented and verified based on IEC 61499 by the implementation of design and reconfigure assembly CPPS . The results show that using GePro results in a programming time savings of an development life cycle time compared to traditional models for reconfiguration.
Guangxi Wan; Peng Zeng. An Event-Based Programming Model with Geometric Spatial Semantics For Cyber-Physical Production Systems. Applied Sciences 2020, 10, 7651 .
AMA StyleGuangxi Wan, Peng Zeng. An Event-Based Programming Model with Geometric Spatial Semantics For Cyber-Physical Production Systems. Applied Sciences. 2020; 10 (21):7651.
Chicago/Turabian StyleGuangxi Wan; Peng Zeng. 2020. "An Event-Based Programming Model with Geometric Spatial Semantics For Cyber-Physical Production Systems." Applied Sciences 10, no. 21: 7651.
Data-driven bearing-fault diagnosis methods have become a research hotspot recently. These methods have to meet two premises: (1) the distributions of the data to be tested and the training data are the same; (2) there are a large number of high-quality labeled data. However, machines usually work under different working conditions in practice, which challenges these prerequisites due to the fact that the data distributions under different working conditions are different. In this paper, the one-dimensional Multi-Scale Domain Adaptive Network (1D-MSDAN) is proposed to address this issue. The 1D-MSDAN is a kind of deep transfer model, which uses both feature adaptation and classifier adaptation to guide the multi-scale convolutional neural network to perform bearing-fault diagnosis under varying working conditions. Feature adaptation is performed by both multi-scale feature adaptation and multi-level feature adaptation, which helps in finding domain-invariant features by minimizing the distribution discrepancy between different working conditions by using the Multi-kernel Maximum Mean Discrepancy (MK-MMD). Furthermore, classifier adaptation is performed by entropy minimization in the target domain to bridge the source classifier and target classifier to further eliminate domain discrepancy. The Case Western Reserve University (CWRU) bearing database is used to validate the proposed 1D-MSDAN. The experimental results show that the diagnostic accuracy for the 12 transfer tasks performed by 1D-MSDAN was superior to that of the mainstream transfer learning models for bearing-fault diagnosis under variable working conditions. In addition, the transfer learning performance of 1D-MSDAN for multi-target domain adaptation and real industrial scenarios was also verified.
Kai Wang; Wei Zhao; Aidong Xu; Peng Zeng; Shunkun Yang. One-Dimensional Multi-Scale Domain Adaptive Network for Bearing-Fault Diagnosis under Varying Working Conditions. Sensors 2020, 20, 6039 .
AMA StyleKai Wang, Wei Zhao, Aidong Xu, Peng Zeng, Shunkun Yang. One-Dimensional Multi-Scale Domain Adaptive Network for Bearing-Fault Diagnosis under Varying Working Conditions. Sensors. 2020; 20 (21):6039.
Chicago/Turabian StyleKai Wang; Wei Zhao; Aidong Xu; Peng Zeng; Shunkun Yang. 2020. "One-Dimensional Multi-Scale Domain Adaptive Network for Bearing-Fault Diagnosis under Varying Working Conditions." Sensors 20, no. 21: 6039.
Sucker-rod pumping systems are the most widely applied artificial lift equipment in the oil and gas industry. Accurate and intelligent working condition recognition of pumping systems imposes major impacts on oilfield production benefits and efficiency. The shape of dynamometer card reflects the working conditions of sucker-rod pumping systems, and different conditions can be indicated by their typical card characteristics. In traditional identification methods, however, features are manually extracted based on specialist experience and domain knowledge. In this paper, an automatic fault diagnosis method is proposed to recognize the working conditions of sucker-rod pumping systems with massive dynamometer card data collected by sensors. Firstly, AlexNet-based transfer learning is adopted to automatically extract representative features from various dynamometer cards. Secondly, with the extracted features, error-correcting output codes model-based SVM is designed to identify the working conditions and improve the fault diagnosis accuracy and efficiency. The proposed AlexNet-SVM algorithm is validated against a real dataset from an oilfield. The results reveal that the proposed method reduces the need for human labor and improves the recognition accuracy.
Haibo Cheng; Haibin Yu; Peng Zeng; Evgeny Osipov; Shichao Li; Valeriy Vyatkin. Automatic Recognition of Sucker-Rod Pumping System Working Conditions Using Dynamometer Cards with Transfer Learning and SVM. Sensors 2020, 20, 5659 .
AMA StyleHaibo Cheng, Haibin Yu, Peng Zeng, Evgeny Osipov, Shichao Li, Valeriy Vyatkin. Automatic Recognition of Sucker-Rod Pumping System Working Conditions Using Dynamometer Cards with Transfer Learning and SVM. Sensors. 2020; 20 (19):5659.
Chicago/Turabian StyleHaibo Cheng; Haibin Yu; Peng Zeng; Evgeny Osipov; Shichao Li; Valeriy Vyatkin. 2020. "Automatic Recognition of Sucker-Rod Pumping System Working Conditions Using Dynamometer Cards with Transfer Learning and SVM." Sensors 20, no. 19: 5659.
Non‐dominated sorting, used to find pareto solutions or assign solutions to different fronts, is a key but time‐consuming process in multi‐objective evolutionary algorithms (MOEAs). The best‐case and worst‐case time complexity of non‐dominated sorting algorithms currently known are O(MNlogN) and O(MN2); M and N represent the number of objectives and the population size, respectively. In this paper, a more efficient SET‐based non‐dominated sorting algorithm, shorted to SETNDS, is proposed. The proposed algorithm can greatly reduce the number of comparisons on the promise of ensuring a shorter running time. In SETNDS, the rank of a solution to be sorted is determined by only comparing with the one with the highest rank degree in its dominant set. This algorithm is compared with six generally existing non‐dominated sorting algorithms—fast non‐dominated sorting, the arena’s principle sort, the deductive sort, the corner sort, the efficient non‐dominated sort and the best order sort on several kinds of datasets. The compared results show that the proposed algorithm is feasible and effective and its computational efficiency outperforms other existing algorithms.
Lingling Xue; Peng Zeng; Haibin Yu. SETNDS: A SET‐Based Non‐Dominated Sorting Algorithm for Multi‐Objective Optimization Problems. Applied Sciences 2020, 10, 6858 .
AMA StyleLingling Xue, Peng Zeng, Haibin Yu. SETNDS: A SET‐Based Non‐Dominated Sorting Algorithm for Multi‐Objective Optimization Problems. Applied Sciences. 2020; 10 (19):6858.
Chicago/Turabian StyleLingling Xue; Peng Zeng; Haibin Yu. 2020. "SETNDS: A SET‐Based Non‐Dominated Sorting Algorithm for Multi‐Objective Optimization Problems." Applied Sciences 10, no. 19: 6858.
Software Defined Networking (SDN) is a new type of network architecture, which provides an important way to implement automated network deployment and flexible management. However, security problems in SDN are also inevitable. DDoS attack belongs to one of the most serious attack types, which is fairly common for today’s Internet. In SDN security fields, DDoS attack detection research has been received more and more attention. In this paper, a DDoS attack detection method based on one-class SVM in SDN is proposed, which provides a better detection accuracy. Furthermore, two new feature vectors, including middle value of flow table item’s duration and protocol data traffic percentage, are extracted to integrate into the item of 11 feature vectors. Additionally, basing on selection and construction method of the 11 feature vectors, a DDoS attack behavior model is established by using one-class SVM algorithm, and the self-adaptation genetic algorithm is designed to optimize the corresponding parameters of the Gaussian kernel of one-class SVM. The experimental results in SDN show that, the proposed new feature vectors are shown to more better detection accuracy, and the proposed method is more feasible by comparing with the BP neural network and RBF neural network algorithms under the same 11 features vectors.
Jianming Zhao; Peng Zeng; Wenli Shang; Guoyu Tong. DDoS Attack Detection Based on One-Class SVM in SDN. Communications in Computer and Information Science 2020, 189 -200.
AMA StyleJianming Zhao, Peng Zeng, Wenli Shang, Guoyu Tong. DDoS Attack Detection Based on One-Class SVM in SDN. Communications in Computer and Information Science. 2020; ():189-200.
Chicago/Turabian StyleJianming Zhao; Peng Zeng; Wenli Shang; Guoyu Tong. 2020. "DDoS Attack Detection Based on One-Class SVM in SDN." Communications in Computer and Information Science , no. : 189-200.
Industrial Internet of Things (IIoT) provide a promising opportunity for building efficient industrial wireless systems by leveraging the growing ubiquity of sensor nodes. However, IIoT exhibits strict reliability and has a high requirement for real-time communications. Furthermore, different criticality level flows are coexisted in many IIoT. The system must guarantee the reliability and real-time performance of high-criticality flows to avoid disasters. To address this issue, this paper first proposes a heterogeneous routing model in which both source and graph routing coexist. Then, we propose Relative-execution Deadline First (RDF) scheduling and prove it has a better performance than the fixed priority (FP) and earliest deadline first (EDF) methods. By extending RDF in mixed-criticality IIoT, a Mixed-Criticality Relative-execution Deadline scheduling algorithm (MCRD) has proposed, which can further improve system schedulability by making a trade-off between reliability and real-time performance. Simulation and experiment results show that our approach outperforms the existing methods.
Changqing Xia; Xi Jin; Chi Xu; Yan Wang; Peng Zeng. Real-time scheduling under heterogeneous routing for industrial Internet of Things. Computers & Electrical Engineering 2020, 86, 106740 .
AMA StyleChangqing Xia, Xi Jin, Chi Xu, Yan Wang, Peng Zeng. Real-time scheduling under heterogeneous routing for industrial Internet of Things. Computers & Electrical Engineering. 2020; 86 ():106740.
Chicago/Turabian StyleChangqing Xia; Xi Jin; Chi Xu; Yan Wang; Peng Zeng. 2020. "Real-time scheduling under heterogeneous routing for industrial Internet of Things." Computers & Electrical Engineering 86, no. : 106740.
With the decentralization of the electricity market and the plea for a carbon-neutral ecosystem, more and more distributed generation (DG) has been incorporated in the power distribution grid, which is then known as active distribution network (ADN). The addition of DGs causes numerous control and protection confronts to the traditional distribution network. For instance, two-way power flow, small fault current, persistent fluctuation of generation and demand, and uncertainty of renewable energy sources (RESs). These problems are more challenging when the distribution network hosts many converter-coupled DGs. Hence, the traditional protection schemes and relaying methods are inadequate to protect ADNs against short-circuit faults and disturbances. We propose a robust communication-assisted fault protection technique for safely operating ADNs with high penetration of converter-coupled DGs. The proposed technique is realizable by employing digital relays available in the recent market and it aims to protect low-voltage (LV) ADNs. It also includes secondary protection that can be enabled when the communication facility or protection equipment fails to operate. In addition, this study provides the detail configuration of the digital relay that enables the devised protection technique. Several enhancements are derived, as alternative technique for the traditional overcurrent protection approach, to detect small fault current and high-impedance fault (HIF). A number of simulations are performed with the complete model of a real ADN, in Shenyang, China, employing the PSCAD software platform. Various cases, fault types and locations are considered for verifying the efficacy of the devised technique and the enabling digital relay. The obtained simulation findings verify the proposed protection technique is effective and reliable in protecting ADNs against various fault types that can occur at different locations.
Shijie Cui; Peng Zeng; Chunhe Song; Zhongfeng Wang. Robust Fault Protection Technique for Low-Voltage Active Distribution Networks Containing High Penetration of Converter-Interfaced Renewable Energy Resources. Processes 2019, 8, 34 .
AMA StyleShijie Cui, Peng Zeng, Chunhe Song, Zhongfeng Wang. Robust Fault Protection Technique for Low-Voltage Active Distribution Networks Containing High Penetration of Converter-Interfaced Renewable Energy Resources. Processes. 2019; 8 (1):34.
Chicago/Turabian StyleShijie Cui; Peng Zeng; Chunhe Song; Zhongfeng Wang. 2019. "Robust Fault Protection Technique for Low-Voltage Active Distribution Networks Containing High Penetration of Converter-Interfaced Renewable Energy Resources." Processes 8, no. 1: 34.
Real-time performance and reliability are two critical indicators in an industrial wireless sensor network (IWSN). Several time-division multiple-address (TDMA)-based industrial standards such as WirelessHART and ISA100 are widely used in IWSNs. However, to simplify the analysis, standard TDMA supports only one or two slot types in each frame, and each slot is usually 10 ms, which severely limits transmissibility and real-time responses in TDMA-based IWSNs where the number of transmissions is large but the length of most packets is small. In this paper, we propose a TDMA frame containing slots of different lengths to address this issue. The key ideas are to waste fewer slot resources and achieve on-demand slot allocation. First, we study the matching problem in a TDMA frame; then, we propose two scheduling methods, the split scheduling algorithm (SSA) and the double plug-in algorithm (DPA), under our TDMA frame. Extensive simulations and real testbed results show that the proposed solution DPA can significantly improve network performance and reliability. Real-time comparisons with other existing scheduling schemes show that the proposed solution improves the acceptance ratio by 48.8% compared to the rate-monotonic scheme.
Changqing Xia; Xi Jin; Linghe Kong; Chi Xu; Peng Zeng. Heterogeneous slot scheduling for real-time industrial wireless sensor networks. Computer Networks 2019, 157, 68 -77.
AMA StyleChangqing Xia, Xi Jin, Linghe Kong, Chi Xu, Peng Zeng. Heterogeneous slot scheduling for real-time industrial wireless sensor networks. Computer Networks. 2019; 157 ():68-77.
Chicago/Turabian StyleChangqing Xia; Xi Jin; Linghe Kong; Chi Xu; Peng Zeng. 2019. "Heterogeneous slot scheduling for real-time industrial wireless sensor networks." Computer Networks 157, no. : 68-77.
The IEC standard WIA-PA is a communication protocol for industrial wireless sensor networks. Its special features, including a hierarchical topology, hybrid centralized-distributed management and packet aggregation make it suitable for large-scale industrial wireless sensor networks. Industrial systems place large real-time requirements on wireless sensor networks. However, the WIA-PA standard does not specify the transmission methods, which are vital to the real-time performance of wireless networks, and little work has been done to address this problem. In this article, we propose a real-time aggregation scheduling method for WIA-PA networks. First, to satisfy the real-time constraints on dataflows, we propose a method that combines the real-time theory with the classical bin-packing method to aggregate original packets into the minimum number of aggregated packets. The simulation results indicate that our method outperforms the traditional bin-packing method, aggregating up to 35% fewer packets, and improves the real-time performance by up to 10%. Second, to make it possible to solve the scheduling problem of WIA-PA networks using the classical scheduling algorithms, we transform the ragged time slots of WIA-PA networks to a universal model. In the simulation, a large number of WIA-PA networks are randomly generated to evaluate the performances of several real-time scheduling algorithms. By comparing the results, we obtain that the earliest deadline first real-time scheduling algorithm is the preferred method for WIA-PA networks.
Xi Jin; Nan Guan; Changqing Xia; Jintao Wang; Peng Zeng. Packet Aggregation Real-Time Scheduling for Large-Scale WIA-PA Industrial Wireless Sensor Networks. ACM Transactions on Embedded Computing Systems 2018, 17, 1 -19.
AMA StyleXi Jin, Nan Guan, Changqing Xia, Jintao Wang, Peng Zeng. Packet Aggregation Real-Time Scheduling for Large-Scale WIA-PA Industrial Wireless Sensor Networks. ACM Transactions on Embedded Computing Systems. 2018; 17 (5):1-19.
Chicago/Turabian StyleXi Jin; Nan Guan; Changqing Xia; Jintao Wang; Peng Zeng. 2018. "Packet Aggregation Real-Time Scheduling for Large-Scale WIA-PA Industrial Wireless Sensor Networks." ACM Transactions on Embedded Computing Systems 17, no. 5: 1-19.
Density information plays an important role in intelligent transportation systems for not only traffic control but also information sharing. Existing products have been able to provide coarsegrained density services. For example, Google Maps can illustrate the traffic conditions by different colors via Internet connection. Vehicle-to-vehicle wireless communications can locally acquire the density by information exchange and neighbor counting. However, either the Internet access or one-by-one counting leads to a sub-second-level delay, which cannot satisfy real-time vehicular applications such as autonomous navigation and data dissemination. To speed up density acquisition, we propose an RDD system. Leveraging the frequency resource, RDD divides the wireless channel into fine-grained subchannels and detects the neighbors in a parallel manner. We establish a testbed using software defined radios and experimentally validate RDD. Moreover, to evaluate RDD in high-density scenarios, extensive simulations are conducted based on real collected data. Both the experiment and simulation results demonstrate that RDD achieves 100 ms level density detection, while the state-of-the-art time-domain acceleration method is at the 10 ms level.
Linghe Kong; Guangtao Xue; Kayhan Zara Ghafoor; Rasheed Hussain; Hao Sheng; Peng Zeng. Real-Time Density Detection in Connected Vehicles: Design and Implementation. IEEE Communications Magazine 2018, 56, 64 -70.
AMA StyleLinghe Kong, Guangtao Xue, Kayhan Zara Ghafoor, Rasheed Hussain, Hao Sheng, Peng Zeng. Real-Time Density Detection in Connected Vehicles: Design and Implementation. IEEE Communications Magazine. 2018; 56 (10):64-70.
Chicago/Turabian StyleLinghe Kong; Guangtao Xue; Kayhan Zara Ghafoor; Rasheed Hussain; Hao Sheng; Peng Zeng. 2018. "Real-Time Density Detection in Connected Vehicles: Design and Implementation." IEEE Communications Magazine 56, no. 10: 64-70.
Time synchronization is critical for wireless sensors networks in industrial automation, e.g., event detection and process control of industrial plants and equipment need a common time reference. However, cyber-physical attacks are enormous threats causing synchronization protocols to fail. This paper studies the algorithm design and analysis in secure time synchronization for resource-constrained industrial wireless sensor networks under Sybil attacks, which cannot be well addressed by existing methods. A node-identification-based secure time synchronization (NiSTS) protocol is proposed. The main idea of this protocol is to utilize the timestamp correlation among different nodes and the uniqueness of a node’s clock skew to detect invalid information rather than isolating suspicious nodes. In the detection process, each node takes the relative skew with respect to its public neighbor as the basis to determine whether the information is reliable and to filter invalid information. The information filtering mechanism renders NiSTS resistant to Sybil attacks and message manipulation attacks. As a completely distributed protocol, NiSTS is not sensitive to the number of Sybil attackers. Extensive simulations were conducted to demonstrate the efficiency of NiSTS and compare it with existing protocols.
Zhaowei Wang; Peng Zeng; Linghe Kong; Dong Li; Xi Jin. Node-Identification-Based Secure Time Synchronization in Industrial Wireless Sensor Networks. Sensors 2018, 18, 2718 .
AMA StyleZhaowei Wang, Peng Zeng, Linghe Kong, Dong Li, Xi Jin. Node-Identification-Based Secure Time Synchronization in Industrial Wireless Sensor Networks. Sensors. 2018; 18 (8):2718.
Chicago/Turabian StyleZhaowei Wang; Peng Zeng; Linghe Kong; Dong Li; Xi Jin. 2018. "Node-Identification-Based Secure Time Synchronization in Industrial Wireless Sensor Networks." Sensors 18, no. 8: 2718.
The valley-to-peak difference in power consumption is a crucial problem in load regulation and control for a power grid. By allowing electric vehicles (EVs) to charge during off-peak hours and feed power back into the grid during peak hours, Vehicle-to-Grid (V2G) technology can help to shave the power peak. Long-distance communication is essential for data exchange between dispersed EVs and charging stations for the realization of V2G systems. However, because of the high mobility of EVs, the highvolume data transmission required and the limitations of the third-party infrastructure, it is challenging to achieve efficient and effective communication. To address these challenges, we propose a new V2G network architecture based on software-defined networking (SDN) technology. (1) We use an IEEE 802.11 WiFibased long-distance (WiLD) network with the TDMA scheme as the backhaul network, and (2) we partially replace the road side units (RSUs) with some of the WiLD nodes to provide access for, and to rapidly broadcast data to, EVs. In addition, we propose: (3) a two-stage flow table mechanism and a double roaming mechanism to address the mobility demands of V2G network terminals; and (4) a rapid data transmission scheme for communication from charging stations to EVs. A testbed was built to validate the proposed network architecture. Experimental results show that the communication time delay is in the order of milliseconds and that the reliability is higher than 99.9%.
Jintao Wang; Peng Zeng; Xi Jin; Fanxin Kong; Zhaowei Wang; Dong Li; Ming Wan. Software Defined Wi-V2G: A V2G Network Architecture. IEEE Intelligent Transportation Systems Magazine 2018, 10, 167 -179.
AMA StyleJintao Wang, Peng Zeng, Xi Jin, Fanxin Kong, Zhaowei Wang, Dong Li, Ming Wan. Software Defined Wi-V2G: A V2G Network Architecture. IEEE Intelligent Transportation Systems Magazine. 2018; 10 (2):167-179.
Chicago/Turabian StyleJintao Wang; Peng Zeng; Xi Jin; Fanxin Kong; Zhaowei Wang; Dong Li; Ming Wan. 2018. "Software Defined Wi-V2G: A V2G Network Architecture." IEEE Intelligent Transportation Systems Magazine 10, no. 2: 167-179.
Wireless sensor networks are widely used in industrial cyber-physical system installations, where high reliability and the need for real-time data are the two main characteristics. A large amount of real-time data can be transmitted to its destination on time using a reasonable periodic allocation of a node’s transmission slots. However, a flow may miss its deadline when flow conflicts occur. When such missed deadlines occur regularly, system performance may degrade, and when the flow is critical, such data losses can result in errors or cause disasters. To address this issue, we introduce multi-user multiple-input and multiple-output technology and a mixed-critical system into an industrial cyber-physical system. When an error occurs or when demand changes, the multi-user multiple-input and multiple-output nodes can switch their transmission mode, changing to a high-criticality configuration to meet the system’s new needs. Hence, we first propose a heterogeneous multi-user multiple-input and multiple-output system model. Based on this model, we propose a slot analyzing algorithm that guarantees system schedulability by reallocating slots for each node after replacing conflict nodes with multi-user multiple-input and multiple-output nodes. By considering both system schedulability and cost, the slot analyzing algorithm also reduces the number of multi-user multiple-input and multiple-output nodes required. Then, to further reduce the number of multi-user multiple-input and multiple-output nodes in an industrial cyber-physical system, we propose a priority inversion algorithm that improves schedulability by adjusting slot allocations before replacing conflict nodes with multi-user multiple-input and multiple-output nodes. By reducing the use of multi-user multiple-input and multiple-output nodes, the priority inversion algorithm achieves better performance than the slot analyzing algorithm when the system is in a high-criticality mode. Evaluation results show the effectiveness and efficacy of our approaches.
Changqing Xia; Xi Jin; Linghe Kong; Jintao Wang; Peng Zeng. Transmission scheduling for mixed-critical multi-user multiple-input and multiple-output industrial cyber-physical systems. International Journal of Distributed Sensor Networks 2017, 13, 1 .
AMA StyleChangqing Xia, Xi Jin, Linghe Kong, Jintao Wang, Peng Zeng. Transmission scheduling for mixed-critical multi-user multiple-input and multiple-output industrial cyber-physical systems. International Journal of Distributed Sensor Networks. 2017; 13 (12):1.
Chicago/Turabian StyleChangqing Xia; Xi Jin; Linghe Kong; Jintao Wang; Peng Zeng. 2017. "Transmission scheduling for mixed-critical multi-user multiple-input and multiple-output industrial cyber-physical systems." International Journal of Distributed Sensor Networks 13, no. 12: 1.
5G wireless communications aim at providing higher data rates, spectral efficiency, and energy efficiency than 4G. To achieve this target, the spectrum resource with low utilization is emptied out for 5G refarming. The refarmed spectrum is of effective propagation nature; however, it leads to extensive competition between PTOs and DTOs. To mitigate such competition, dynamic spectrum sharing should be realized. For this purpose, a spectrum sharing framework of a 5G system is designed in this article, in which the public users and dedicated users can access the sharing spectrum dynamically. In the framework, to ensure the QoE of the secondary users in a spectrum sharing system, the DTO in this case, an advanced dynamic channel access strategy is proposed. The spectrum sharing system states are modeled as a finite state Markov chain, and are used to analyze the system state transition model. Based on the analysis results, the optimal dynamic channel access strategy with minimum queuing time for DTO is derived by a Markov decision process. Extensive simulations show that the proposed dynamic channel access strategy can achieve the optimal queuing time.
Siyu Lin; Linghe Kong; Qian Gao; Muhammad Khurram Khan; Zhangdui Zhong; Xi Jin; Peng Zeng. Advanced Dynamic Channel Access Strategy in Spectrum Sharing 5G Systems. IEEE Wireless Communications 2017, 24, 74 -80.
AMA StyleSiyu Lin, Linghe Kong, Qian Gao, Muhammad Khurram Khan, Zhangdui Zhong, Xi Jin, Peng Zeng. Advanced Dynamic Channel Access Strategy in Spectrum Sharing 5G Systems. IEEE Wireless Communications. 2017; 24 (5):74-80.
Chicago/Turabian StyleSiyu Lin; Linghe Kong; Qian Gao; Muhammad Khurram Khan; Zhangdui Zhong; Xi Jin; Peng Zeng. 2017. "Advanced Dynamic Channel Access Strategy in Spectrum Sharing 5G Systems." IEEE Wireless Communications 24, no. 5: 74-80.
Wireless sensor networks (WSNs) are widely applied in industrial manufacturing systems. By means of centralized control, the real-time requirement and reliability can be provided by WSNs in industrial production. Furthermore, many approaches reserve resources for situations in which the controller cannot perform centralized resource allocation. The controller assigns these resources as it becomes aware of when and where accidents have occurred. However, the reserved resources are limited, and such incidents are low-probability events. In addition, resource reservation may not be effective since the controller does not know when and where accidents will actually occur. To address this issue, we improve the reliability of scheduling for emergency tasks by proposing a method based on a stealing mechanism. In our method, an emergency task is transmitted by stealing resources allocated to regular flows. The challenges addressed in our work are as follows: (1) emergencies occur only occasionally, but the industrial system must deliver the corresponding flows within their deadlines when they occur; (2) we wish to minimize the impact of emergency flows by reducing the number of stolen flows. The contributions of this work are two-fold: (1) we first define intersections and blocking as new characteristics of flows; and (2) we propose a series of distributed routing algorithms to improve the schedulability and to reduce the impact of emergency flows. We demonstrate that our scheduling algorithm and analysis approach are better than the existing ones by extensive simulations.
Changqing Xia; Xi Jin; Linghe Kong; Peng Zeng. Scheduling for Emergency Tasks in Industrial Wireless Sensor Networks. Sensors 2017, 17, 1674 .
AMA StyleChangqing Xia, Xi Jin, Linghe Kong, Peng Zeng. Scheduling for Emergency Tasks in Industrial Wireless Sensor Networks. Sensors. 2017; 17 (7):1674.
Chicago/Turabian StyleChangqing Xia; Xi Jin; Linghe Kong; Peng Zeng. 2017. "Scheduling for Emergency Tasks in Industrial Wireless Sensor Networks." Sensors 17, no. 7: 1674.
This paper presents an integrative demand response (DR) mechanism for energy management of appliances, an energy storage system and an electric vehicle (EV) within a home. The paper considers vehicle-to-home (V2H) and vehicle-to-grid (V2G) functions for energy management of EVs and the degradation cost of the EV battery caused by the V2H/V2G operation in developing the proposed DR mechanism. An efficient optimization algorithm is developed based on approximate dynamic programming, which overcomes the challenges of solving high dimensional optimization problems for the integrative home energy system. To investigate how the participation of different home appliances affects the DR efficiency, several DR scenarios are designed. Then, a detailed simulation study is conducted to investigate and compare home energy management efficiency under different scenarios.
Hepeng Li; Peng Zeng; Chuanzhi Zang; Haibin Yu; Shuhui Li. An Integrative DR Study for Optimal Home Energy Management Based on Approximate Dynamic Programming. Sustainability 2017, 9, 1248 .
AMA StyleHepeng Li, Peng Zeng, Chuanzhi Zang, Haibin Yu, Shuhui Li. An Integrative DR Study for Optimal Home Energy Management Based on Approximate Dynamic Programming. Sustainability. 2017; 9 (7):1248.
Chicago/Turabian StyleHepeng Li; Peng Zeng; Chuanzhi Zang; Haibin Yu; Shuhui Li. 2017. "An Integrative DR Study for Optimal Home Energy Management Based on Approximate Dynamic Programming." Sustainability 9, no. 7: 1248.
In the deployment of industrial wireless network, nodes can only be deployed in some special regions due to the restriction of the environment in the factory, thus failing to effectively elude occlusions, and restricting the performance of the network. Therefore, optimization should be made for layout of the network. An optimization is made on nodes layout in this paper based on the architecture of IEEE 802.11 WIFI Long-Distance multi-hop mesh networks. The optimization objectives are the network throughput and the network construction cost with the delay of traffics as constraint. For the scene with small network size, a hierarchical traversal method is adopted to get the optimal solution; and for that with large one, a hierarchical heuristic method is proposed to get the approximate solution. Finally, we carried out experiments via simulation and the scene constructed in the actual environment of the factory. The results show that the algorithms proposed in this paper can obtain effective solutions, and the heuristic algorithm has shorter computing time.
Jintao Wang; Xi Jin; Peng Zeng; Zhaowei Wang; Changqing Xia. Layout Optimization for a Long Distance Wireless Mesh Network: An Industrial Case Study. Computer Vision 2017, 865 -870.
AMA StyleJintao Wang, Xi Jin, Peng Zeng, Zhaowei Wang, Changqing Xia. Layout Optimization for a Long Distance Wireless Mesh Network: An Industrial Case Study. Computer Vision. 2017; ():865-870.
Chicago/Turabian StyleJintao Wang; Xi Jin; Peng Zeng; Zhaowei Wang; Changqing Xia. 2017. "Layout Optimization for a Long Distance Wireless Mesh Network: An Industrial Case Study." Computer Vision , no. : 865-870.