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Edge Computing Technology: Development and Countermeasures
Hong Xuehai and Wang Yang
Strategic Study of CAE 2018, Volume 20, Issue 2, Pages 20-26 doi: 10.15302/J-SSCAE-2018.02.004
Edge computing is an emerging technology that reduces transmission delays and bandwidth consumption by placing computing, storage, bandwidth, applications, and other resources on the edge of the network. Moreover, application developers and content providers can provide perceptible services based on real-time network information. Mobile terminals, Internet of things, and other devices provide the necessary front-end support for computing sensitive applications, such as image recognition and network games, to share the cloud work load with the processing capability of edge computing. This paper discusses the concept of edge computing, key problems that require solutions, main advances in edge computing, influence of edge computing developments, and opportunities and development countermeasures of edge calculation.
Keywords： cloud computing edge computing fog computing mobile edge computing internet of things front-end intelligence
Development and Prospect of Edge Intelligence for Industrial Internet
Ren Yaodanjun, Qi Zhengwei, Guan Haibing, Chen Lei
Strategic Study of CAE 2021, Volume 23, Issue 2, Pages 104-111 doi: 10.15302/J-SSCAE-2021.02.014
As the industrial Internet deeply integrated with manufacturing, the drive capability of industrial intelligence becomes prominent regarding the digitization and informatization of the manufacturing industry. Meanwhile, new applications propose higher requirements for service quality. Edge intelligence, a product of edge computing and artificial intelligence, completes intelligent tasks using computing resources near the data origin. It can alleviate bandwidth transmission pressure, shorten service response delay, and protect the security of private data. Hence, edge intelligence provides a possible approach to satisfy the performance requirements in industrial intelligence applications. This study reviews the research status of cooperative computing, resource isolation, privacy protection, and other key technologies in edge intelligence. Then the typical applications of edge intelligence in equipment management services, production process automation, and manufacturing assistance in the industrial Internet are analyzed in detail. Moreover, the development trend of edge intelligence for the industrial Internet is analyzed in terms of business driving mode, industrial ecology composition, alliance role, and business model. Furthermore, relevant policy suggestions are proposed. We suggest that superior resources should be integrated to establish industry standards; investment increased in basic common resources to deepen the application of the industrial Internet; a good industrial ecology created in the subdivided fields; and university–enterprise cooperation promoted to cultivate interdisciplinary personnel.
Keywords： industrial Internet，edge computing，edge intelligence，cooperative computing，resource isolation
Cost-effective resource segmentation in hierarchical mobile edge clouds Special Feature on Future Network-Research Article
Ming-shuang JIN, Shuai GAO, Hong-bin LUO, Hong-ke ZHANG
Frontiers of Information Technology & Electronic Engineering 2019, Volume 20, Issue 9, Pages 1209-1220 doi: 10.1631/FITEE.1800203
Keywords： Edge clouds Edge computing Edge caching Resource segmentation Virtual machine (VM) allocation
Weiyong Yang, Wei Liu, Xingshen Wei, Zixin Guo, Kangle Yang, Hao Huang, Longyun Qi,yangkangle@sgepri.sgcc.com.cn
Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 3, Pages 287-436 doi: 10.1631/FITEE.1900636
Keywords： 物联网；泛在电力物联网；边缘计算；可信计算；网络安全
Flexible Resource Scheduling for Software-Defined Cloud Manufacturing with Edge Computing Article
Chen Yang,Fangyin Liao,Shulin Lan,Lihui Wang,Weiming Shen,George Q. Huang
Engineering 2023, Volume 22, Issue 3, Pages 60-70 doi: 10.1016/j.eng.2021.08.022
This research focuses on the realization of rapid reconfiguration in a cloud manufacturing environment to enable flexible resource scheduling, fulfill the resource potential and respond to various changes. Therefore, this paper first proposes a new cloud and software-defined networking (SDN)-based manufacturing model named software-defined cloud manufacturing (SDCM), which transfers the control logic from automation hard resources to the software. This shift is of significance because the software can function as the “brain” of the manufacturing system and can be easily changed or updated to support fast system reconfiguration, operation, and evolution. Subsequently, edge computing is introduced to complement the cloud with computation and storage capabilities near the end things. Another key issue is to manage the critical network congestion caused by the transmission of a large amount of Internet of Things (IoT) data with different quality of service (QoS) values such as latency. Based on the virtualization and flexible networking ability of the SDCM, we formalize the time-sensitive data traffic control problem of a set of complex manufacturing tasks, considering subtask allocation and data routing path selection. To solve this optimization problem, an approach integrating the genetic algorithm (GA), Dijkstra’s shortest path algorithm, and a queuing algorithm is proposed. Results of experiments show that the proposed method can efficiently prevent network congestion and reduce the total communication latency in the SDCM.
Keywords： Cloud manufacturing Edge computing Software-defined networks Industrial internet of things Industry 4.0
MEC-Empowered Non-Terrestrial Network for 6G Wide-Area Time-Sensitive Internet of Things Article
Chengxiao Liu, Wei Feng, Xiaoming Tao, Ning Ge
Engineering 2022, Volume 8, Issue 1, Pages 96-107 doi: 10.1016/j.eng.2021.11.002
In the upcoming sixth-generation (6G) era, the demand for constructing a wide-area time-sensitive Internet of Things (IoT) continues to increase. As conventional cellular technologies are difficult to directly use for wide-area time-sensitive IoT, it is beneficial to use non-terrestrial infrastructures, including satellites and unmanned aerial vehicles (UAVs). Thus, we can build a non-terrestrial network (NTN) using a cell-free architecture. Driven by the time-sensitive requirements and uneven distribution of IoT devices, the NTN must be empowered using mobile edge computing (MEC) while providing oasisoriented on-demand coverage for devices. Nevertheless, communication and MEC systems are coupled with each other under the influence of a complex propagation environment in the MEC-empowered NTN, which makes it difficult to coordinate the resources. In this study, we propose a process-oriented framework to design communication and MEC systems in a time-division manner. In this framework, large-scale channel state information (CSI) is used to characterize the complex propagation environment at an affordable cost, where a nonconvex latency minimization problem is formulated. Subsequently, the approximated problem is provided, and it can be decomposed into sub-problems. These sub-problems are then solved iteratively. The simulation results demonstrated the superiority of the proposed process-oriented scheme over other algorithms, implied that the payload deployments of UAVs should be appropriately predesigned to improve the efficiency of using resources, and confirmed that it is advantageous to integrate NTN with MEC for wide-area time-sensitive IoT.
Keywords： Cell-free Mobile edge computing Non-terrestrial networks Sixth-generation Wide-area time-sensitive IoT
Edge Detection Based on a Uniform B-Spline With Shape Parameter by Modifying Profit and Loss Data
Zhao Yanli ,Wang Zhan ,Guo Chenghao ,Liu Fengyu
Strategic Study of CAE 2007, Volume 9, Issue 7, Pages 65-70
This paper puts forward a novel image edge detection method based on uniform B-spline with shape parameter by modifying profit and loss data. The original image intensity is modified for decreasing the residual error between smooth image and original image. A smooth surface of the digital image is presented by the new modified data. The edge point is detected by either computing the local extreme of the directional derivative or computing zero crossing of the second order directional derivative of the smooth surface. Experiments demonstrate that this algorithm is simple, accurate and reliable. It can wipe off the bogus edge commendably and process the digital image in real time.
Keywords： uniform B-spline with shape parameter edge detection computer vision profit and loss modifying
Incentive-Aware Blockchain-Assisted Intelligent Edge Caching and Computation Offloading for IoT Article
Qian Wang, Siguang Chen, Meng Wu
Engineering 2023, Volume 31, Issue 12, Pages 127-138 doi: 10.1016/j.eng.2022.10.014
The rapid development of artificial intelligence has pushed the Internet of Things (IoT) into a new stage. Facing with the explosive growth of data and the higher quality of service required by users, edge computing and caching are regarded as promising solutions. However, the resources in edge nodes (ENs) are not inexhaustible. In this paper, we propose an incentive-aware blockchain-assisted intelligent edge caching and computation offloading scheme for IoT, which is dedicated to providing a secure and intelligent solution for collaborative ENs in resource optimization and controls. Specifically, we jointly optimize offloading and caching decisions as well as computing and communication resources allocation to minimize the total cost for tasks completion in the EN. Furthermore, a blockchain incentive and contribution co-aware federated deep reinforcement learning algorithm is designed to solve this optimization problem. In this algorithm, we construct an incentive-aware blockchain-assisted collaboration mechanism which operates during local training, with the aim to strengthen the willingness of ENs to participate in collaboration with security guarantee. Meanwhile, a contribution-based federated aggregation method is developed, in which the aggregation weights of EN gradients are based on their contributions, thereby improving the training effect. Finally, compared with other baseline schemes, the numerical results prove that our scheme has an efficient optimization utility of resources with significant advantages in total cost reduction and caching performance.
Keywords： Computation offloading Caching Incentive Blockchain Federated deep reinforcement learning
The Application of Two Dimensions Wavelet in Image Edges Detection
Zhang Hongyan,Zhang Dengpan
Strategic Study of CAE 2003, Volume 5, Issue 4, Pages 61-64
Edges as the main characterization of image vision have been throught as the main content in obtaining image information. Wavelet transform has the capacity for detecting local signal mutation and detects information using multiscale character, so it is taken as the excellent tool to detect the edges of the image information. This paper analyzes the basic theory using two dimensions wavelet to detect image edges on the basis of wavelet transform and then designs the detecting algorithm of the multi-scale edge matching. On the basis of researching results,the application programme is made to analyse the true examples.
Keywords： wavelet transform multi-scale edges detection
De-scattering and edge-enhancement algorithms for underwater image restoration Research Papers
Pan-wang PAN, Fei YUAN, En CHENG
Frontiers of Information Technology & Electronic Engineering 2019, Volume 20, Issue 6, Pages 862-871 doi: 10.1631/FITEE.1700744
Image restoration is a critical procedure for underwater images, which suffer from serious color deviation and edge blurring. Restoration can be divided into two stages: de-scattering and edge enhancement. First, we introduce a multi-scale iterative framework for underwater image de-scattering, where a convolutional neural network is used to estimate the transmission map and is followed by an adaptive bilateral filter to refine the estimated results. Since there is no available dataset to train the network, a dataset which includes 2000 underwater images is collected to obtain the synthetic data. Second, a strategy based on white balance is proposed to remove color casts of underwater images. Finally, images are converted to a special transform domain for denoising and enhancing the edge using the non-subsampled contourlet transform. Experimental results show that the proposed method significantly outperforms state-of-the-art methods both qualitatively and quantitatively.
Keywords： Image de-scattering Edge enhancement Convolutional neural network Non-subsampled contourlet transform
Progress and Consideration of High Precision Road Navigation Map
Liu Jingnan,Wu Hangbin,Guo Chi,Zhang Hongmin,Zuo Wenwei,Yang Cheng
Strategic Study of CAE 2018, Volume 20, Issue 2, Pages 99-105 doi: 10.15302/J-SSCAE-2018.02.015
With the rapid development of the Internet, an increasing number of new industries such as "Internet Plus" intelligent transportation and unmanned systems based on location-based services have been gradually developed. The development of these industries requires the support of high precision location data, which the 5 m accuracy of traditional navigation maps cannot provide. To overcome the drawbacks of traditional maps, high precision road navigation maps have been proposed. High precision road navigation maps can provide more detailed road information and are thus able to more accurately reflect the real situation of roads. Compared to traditional maps, high precision road navigation maps possess three advantages. First, they include additional map layers. Second, the content of the layers is finer. Third, a new map structure is divided. However, the rich information content of high precision maps leads to the generation of huge amounts of data. Traditional centralized big data processing modes are unable to meet the computing needs required for processing such huge amounts of data. Therefore, in this paper, we propose a big data processing model involving "crowdsourcing + edge computing" to address the problem of high precision map calculation. At present, high precision road navigation maps have kicked into a high gear. Nevertheless, certain problems persist that need to be addressed during the process of development.
Keywords： high precision road navigation map “Internet Plus” intelligent transportation unmanned systems crowdsourcing edge computing
Research on the Longitudinal End Effect ofSingle Linear Induction Motor
Xu Wei,Sun Guangsheng
Strategic Study of CAE 2007, Volume 9, Issue 3, Pages 21-27
The SLIM has been widely applied in transportation for its simple-firm structure and its directly forward electromagnetic thrust. Because of its discontinuous magnetic circuit, the motor has transverse and longitudinal end effects. There are eddy currents, which become greater as motor spread increases, occurring in both entrance and exit of its secondary side for magnetic flux balance. End effects and eddy currents bring ill impact to air gap magnetic flux which reduce its available magnetic flux of air gap and pull coefficient. This paper describes particular discussions on the SLIM working characters and works out the d-q axis equivalent circuits. The changes of mutual inductance and resistance in d axis indicate both the second longitudinal end effect and the eddy current influences. Then the article establishes SLIM control equations connected with the rotor-flux oriented(RFO)vector control theory in rotary motor. The paper brings forward uds, uqs, iqs online decouple compensation based on the rotor magnetic flux, speed, current regulators, which adjust and accommodate pulsive force, d-q axis voltages, d-q magnetic fluxes, d axis mutual inductance. The result indicates that this method reduces the torque ripple and makes the stator currents flat, speed smooth during the sudden change in motor speed of no load, which provides theory guidance to the SLIM application analysis and achieves some active effects.
Keywords： single linear induction motor(SLIM) rotor-flux oriented(RFO)control end effect decouple control accommodation
A Video Scan Format Conversation Algorithm Based onSpatio-temporal Weight and Edge Direction
Ding Yong,Lu Shengli,Shi Longxing
Strategic Study of CAE 2007, Volume 9, Issue 10, Pages 49-54
De-interlace is to convert interlaced images to progressive ones. In this paper, a de-interlacing algorithm based on spatio-temporal weight and edge direction is presented. It consists of motion detection, low-angle edge detection, and spatio-temporal weight adaptive interpolation. It uses total 4 fields information captured in field storage to detect the presence of motion. And it detects low-angle edge by an adaptive searching radius in which the 6°edge is obtained. The proposed method using spatio-temporal adaptive interpolation can obtain quite good display quality and satisfies real-time process of HDTV sequences.
Keywords： scan format conversation motion estimation edge detection spatio-temporal adaptive interpolation de-interlace
Optical plasma boundary reconstruction based on least squares for EASTTokamak None
Hao LUO, Zheng-ping LUO, Chao XU, Wei JIANG
Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 9, Pages 1124-1134 doi: 10.1631/FITEE.1700041
Reconstructing the shape and position of plasma is an important issue in Tokamaks. Equilibrium and fitting (EFIT) code is generally used for plasma boundary reconstruction in some Tokamaks. However, this magnetic method still has some inevitable disadvantages. In this paper, we present an optical plasma boundary reconstruction algorithm. This method uses EFIT reconstruction results as the standard to create the optimally optical reconstruction. Traditional edge detection methods cannot extract a clear plasma boundary for reconstruction. Based on global contrast, we propose an edge detection algorithm to extract the plasma boundary in the image plane. Illumination in this method is robust. The extracted boundary and the boundary reconstructed by EFIT are fitted by same-order polynomials and the transformation matrix exists. To acquire this matrix without camera calibration, the extracted plasma boundary is transformed from the image plane to the Tokamak poloidal plane by a mathematical model, which is optimally resolved by using least squares to minimize the error between the optically reconstructed result and the EFIT result. Once the transform matrix is acquired, we can optically reconstruct the plasma boundary with only an arbitrary image captured. The error between the method and EFIT is presented and the experimental results of different polynomial orders are discussed.
Keywords： Optical boundary reconstruction Boundary detection Global contrast Least square EAST Tokamak
High End Computing in China and the Exploration of “Sunway” Computers
Chen Zuoning
Strategic Study of CAE 2004, Volume 6, Issue 9, Pages 23-28
In the beginning of the 21st century, driven by application requirements, the research and development of HEC are getting a new upsurge both in China and abroad. This paper analyses the development status and trends of international HEC, describes the overall development and application status of HEC in China, introduces the major technical features and application achievements of Sunway series high-performance computers; discusses the problems faced by today's HEC technologies, and finally makes some suggestions on how to extend progress in the HEC industry in China.
Keywords： high-end computing grid computing high performance service high productivity computing total cost of ownership Sunway series computers
Title Author Date Type Operation
Edge Computing Technology: Development and Countermeasures
Hong Xuehai and Wang Yang
Journal Article
Development and Prospect of Edge Intelligence for Industrial Internet
Ren Yaodanjun, Qi Zhengwei, Guan Haibing, Chen Lei
Journal Article
Cost-effective resource segmentation in hierarchical mobile edge clouds
Ming-shuang JIN, Shuai GAO, Hong-bin LUO, Hong-ke ZHANG
Journal Article
Generation of noise-like pulses and soliton rains in a graphene mode-locked erbium-doped fiber ring laser
Weiyong Yang, Wei Liu, Xingshen Wei, Zixin Guo, Kangle Yang, Hao Huang, Longyun Qi,yangkangle@sgepri.sgcc.com.cn
Journal Article
Flexible Resource Scheduling for Software-Defined Cloud Manufacturing with Edge Computing
Chen Yang,Fangyin Liao,Shulin Lan,Lihui Wang,Weiming Shen,George Q. Huang
Journal Article
MEC-Empowered Non-Terrestrial Network for 6G Wide-Area Time-Sensitive Internet of Things
Chengxiao Liu, Wei Feng, Xiaoming Tao, Ning Ge
Journal Article
Edge Detection Based on a Uniform B-Spline With Shape Parameter by Modifying Profit and Loss Data
Zhao Yanli ,Wang Zhan ,Guo Chenghao ,Liu Fengyu
Journal Article
Incentive-Aware Blockchain-Assisted Intelligent Edge Caching and Computation Offloading for IoT
Qian Wang, Siguang Chen, Meng Wu
Journal Article
The Application of Two Dimensions Wavelet in Image Edges Detection
Zhang Hongyan,Zhang Dengpan
Journal Article
De-scattering and edge-enhancement algorithms for underwater image restoration
Pan-wang PAN, Fei YUAN, En CHENG
Journal Article
Progress and Consideration of High Precision Road Navigation Map
Liu Jingnan,Wu Hangbin,Guo Chi,Zhang Hongmin,Zuo Wenwei,Yang Cheng
Journal Article
Research on the Longitudinal End Effect ofSingle Linear Induction Motor
Xu Wei,Sun Guangsheng
Journal Article
A Video Scan Format Conversation Algorithm Based onSpatio-temporal Weight and Edge Direction
Ding Yong,Lu Shengli,Shi Longxing
Journal Article
Optical plasma boundary reconstruction based on least squares for EASTTokamak
Hao LUO, Zheng-ping LUO, Chao XU, Wei JIANG
Journal Article
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