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Articles 721 - 750 of 1378
Full-Text Articles in Computer Engineering
Mean-Shift Object Tracking Algorithm With Systematic Sampling Technique, Yoanes Bandung, Aris Ardiansyah
Mean-Shift Object Tracking Algorithm With Systematic Sampling Technique, Yoanes Bandung, Aris Ardiansyah
Makara Journal of Technology
Mean shift is a fast object tracking algorithm that only considers pixels in an object area, hence its relatively small computational load. This algorithm is suitable for use in real-time conditions in terms of execution time. The use of histograms causes this algorithm to be relatively resistant to rotation and changes in object size. However, its resistance to lighting changes is not optimal. This study aims to improve the performance of the algorithm under lighting changes and reduce its processing time. The proposed technique involves the use of sampling techniques to reduce the number of iterations, optimization of candidate search …
Analysis Of Correlation And Mapping Of Chlorophyll-A Concentrations And Sea Surface Temperatures In Coastal Areas Based On Terra Modis Satellite Image Data, Hendrata Wibisana, Bangun Muljo Sukotjo, Umboro Lasminto
Analysis Of Correlation And Mapping Of Chlorophyll-A Concentrations And Sea Surface Temperatures In Coastal Areas Based On Terra Modis Satellite Image Data, Hendrata Wibisana, Bangun Muljo Sukotjo, Umboro Lasminto
Makara Journal of Technology
Ecosystems in aquatic environments are distinct from ecosystems on land. Changes that occur in ecosystems in aquatic environments affect the lives of biota in these waters, including the fish used as a food source in fishing communities in coastal areas. This study aims to determine the role of remote sensing in mapping and analyzing the relationship between the parameters of sea surface temperature and chlorophyll-a concentrations on the coast. The correlation of sea surface temperature with chlorophyll-a concentrations is modeled via linear regression. An analysis of variance test is performed to establish the suitability of the temperature data for the …
Dycuckoo: Dynamic Hash Tables On Gpus, Yuchen Li, Qiwei Zhu, Zheng Lyu, Zhongdong Huang, Jianling Sun
Dycuckoo: Dynamic Hash Tables On Gpus, Yuchen Li, Qiwei Zhu, Zheng Lyu, Zhongdong Huang, Jianling Sun
Research Collection School Of Computing and Information Systems
The hash table is a fundamental structure that has been implemented on graphics processing units (GPUs) to accelerate a wide range of analytics workloads. Most existing works have focused on static scenarios and occupy large GPU memory to maximize the insertion efficiency. In many cases, data stored in hash tables get updated dynamically, and existing approaches use unnecessarily large memory resources. One naïve solution is to rebuild a hash table (known as rehashing) whenever it is either filled or mostly empty. However, this approach renders significant overheads for rehashing. In this paper, we propose a novel dynamic cuckoo hash table …
Dram Failure Prediction In Aiops: Empirical Evaluation, Challenges And Opportunities, Zhiyue Wu, Hongzuo Xu, Guansong Pang, Fengyuan Yu, Yijie Wang, Songlei Jian, Yongjun Wang
Dram Failure Prediction In Aiops: Empirical Evaluation, Challenges And Opportunities, Zhiyue Wu, Hongzuo Xu, Guansong Pang, Fengyuan Yu, Yijie Wang, Songlei Jian, Yongjun Wang
Research Collection School Of Computing and Information Systems
DRAM failure prediction is a vital task in AIOps, which is crucial to maintain the reliability and sustainable service of large-scale data centers. However, limited work has been done on DRAM failure prediction mainly due to the lack of public available datasets. This paper presents a comprehensive empirical evaluation of diverse machine learning techniques for DRAM failure prediction using a large-scale multisource dataset, including more than three millions of records of kernel, address, and mcelog data, provided by Alibaba Cloud through PAKDD 2021 competition. Particularly, we first formulate the problem as a multiclass classification task and exhaustively evaluate seven popular/stateof-the-art …
Boundary Precedence Image Inpainting Method Based On Self-Organizing Maps, Haibo Pen, Quan Wang, Zhaoxia Wang
Boundary Precedence Image Inpainting Method Based On Self-Organizing Maps, Haibo Pen, Quan Wang, Zhaoxia Wang
Research Collection School Of Computing and Information Systems
In addition to text data analysis, image analysis is an area that has increasingly gained importance in recent years because more and more image data have spread throughout the internet and real life. As an important segment of image analysis techniques, image restoration has been attracting a lot of researchers’ attention. As one of AI methodologies, Self-organizing Maps (SOMs) have been applied to a great number of useful applications. However, it has rarely been applied to the domain of image restoration. In this paper, we propose a novel image restoration method by leveraging the capability of SOMs, and we name …
Dbl: Efficient Reachability Queries On Dynamic Graphs, Qiuyi Lyu, Yuchen Li, Bingsheng He, Bin Gong
Dbl: Efficient Reachability Queries On Dynamic Graphs, Qiuyi Lyu, Yuchen Li, Bingsheng He, Bin Gong
Research Collection School Of Computing and Information Systems
Reachability query is a fundamental problem on graphs, which has been extensively studied in academia and industry. Since graphs are subject to frequent updates in many applications, it is essential to support efficient graph updates while offering good performance in reachability queries. Existing solutions compress the original graph with the Directed Acyclic Graph (DAG) and propose efficient query processing and index update techniques. However, they focus on optimizing the scenarios where the Strong Connected Components (SCCs) remain unchanged and have overlooked the prohibitively high cost of the DAG maintenance when SCCs are updated. In this paper, we propose DBL, an …
Towards Efficient Motif-Based Graph Partitioning: An Adaptive Sampling Approach, Shixun Huang, Yuchen Li, Zhifeng Bao, Zhao Li
Towards Efficient Motif-Based Graph Partitioning: An Adaptive Sampling Approach, Shixun Huang, Yuchen Li, Zhifeng Bao, Zhao Li
Research Collection School Of Computing and Information Systems
In this paper, we study the problem of efficient motif-based graph partitioning (MGP). We observe that existing methods require to enumerate all motif instances to compute the exact edge weights for partitioning. However, the enumeration is prohibitively expensive against large graphs. We thus propose a sampling-based MGP (SMGP) framework that employs an unbiased sampling mechanism to efficiently estimate the edge weights while trying to preserve the partitioning quality. To further improve the effectiveness, we propose a novel adaptive sampling framework called SMGP+. SMGP+ iteratively partitions the input graph based on up-to-date estimated edge weights, and adaptively adjusts the sampling distribution …
Electrostatic Design And Characterization Of A 200 Kev Photogun And Wien Spin Rotator, Gabriel G. Palacios Serrano
Electrostatic Design And Characterization Of A 200 Kev Photogun And Wien Spin Rotator, Gabriel G. Palacios Serrano
Electrical & Computer Engineering Theses & Dissertations
High-energy nuclear physics experiments at the Jefferson Lab Continuous Electron Beam Accelerator Facility (CEBAF) require high spin-polarization electron beams produced from strained super-lattice GaAs photocathodes activated to negative electron affinity in a high voltage photogun operating at 130 kV dc. A pair of Wien filter spin rotators in the injector provides precise control of the electron beam polarization at the end station target. An upgrade of the CEBAF injector to better support the upcoming Moller experiment requires increasing the electron beam energy to 200 keV, resulting in better transmission through injector apertures and improved photocathode lifetime. In addition, the energy …
Authentication Schemes' Impact On Working Memory, Janine D. Mator
Authentication Schemes' Impact On Working Memory, Janine D. Mator
Psychology Theses & Dissertations
Authentication is the process by which a computing system validates a user’s identity. Although this process is necessary for system security, users view authentication as a frequent disruption to their primary tasks. During this disruption, primary task information must be actively maintained in working memory. As a result, primary task information stored in working memory is at risk of being lost or corrupted while users authenticate. For over two decades, researchers have focused on developing more memorable passwords by replacing alphanumeric text with visual graphics (Biddle et al., 2012). However, very little attention has been given to the impact authentication …
The Design Of Dynamic Probabilistic Caching With Time-Varying Content Popularity, Jie Gao, Shan Zhang, Lian Zhao, Xuemin Shen
The Design Of Dynamic Probabilistic Caching With Time-Varying Content Popularity, Jie Gao, Shan Zhang, Lian Zhao, Xuemin Shen
Electrical and Computer Engineering Faculty Research and Publications
In this paper, we design dynamic probabilistic caching for the scenario when the instantaneous content popularity may vary with time while it is possible to predict the average content popularity over a time window. Based on the average content popularity, optimal content caching probabilities can be found, e.g., from solving optimization problems, and existing results in the literature can implement the optimal caching probabilities via static content placement. The objective of this work is to design dynamic probabilistic caching that: i) converge (in distribution) to the optimal content caching probabilities under time-invariant content popularity, and ii) adapt to the time-varying …
Measurements And Analysis Of Propagation Channels In Vehicle-To-Infrastructure Scenarios, Wei Li, Xiaoya Hu, Jie Gao, Lian Zhao, Xuemin Shen
Measurements And Analysis Of Propagation Channels In Vehicle-To-Infrastructure Scenarios, Wei Li, Xiaoya Hu, Jie Gao, Lian Zhao, Xuemin Shen
Electrical and Computer Engineering Faculty Research and Publications
In this paper, we present measurements and analysis of propagation channels in vehicle-to-infrastructure (V2I) scenarios, which are the basis of designing vehicular communication systems. Firstly, we propose a deterministic geometry-based method to classify V2I links into three types, i.e., line-of-sight beneath (LOS-B), non-LOS (NLOS), and line-of-sight above (LOS-A), based on the environmental features, where roadside row of trees constitute the main obstacles. Secondly, for each link, we investigate the large-scale fading effect on V2I channels, including the path loss exponent and shadowing components. Subsequently, we validate the empirical path loss model using extensive measurements and two classical channel models. The …
Distance-Based Formation Control Using Decentralized Sensing With Infrared Photodiodes, Steven Williams
Distance-Based Formation Control Using Decentralized Sensing With Infrared Photodiodes, Steven Williams
LSU Master's Theses
This study presents an onboard sensor system for determining the relative positions of mobile robots, which is used in decentralized distance-based formation controllers for multi-agent systems. This sensor system uses infrared photodiodes and LEDs; its effective use requires coordination between the emitting and detecting robots. A technique is introduced for calculating the relative positions based on photodiode readings, and an automated calibration system is designed for future maintenance. By measuring the relative positions of their neighbors, each robot is capable of running an onboard formation controller, which is independent of both a centralized controller and a global positioning-like system (e.g., …
How The Power Of Machine – Machine Learning, Data Science And Nlp Can Be Used To Prevent Spoofing And Reduce Financial Risks, Sasibhushan Rao Chanthati
How The Power Of Machine – Machine Learning, Data Science And Nlp Can Be Used To Prevent Spoofing And Reduce Financial Risks, Sasibhushan Rao Chanthati
Harrisburg University Other Works
This paper discusses the potential of machine learning, data science, and natural language processing (NLP) in mitigating the incidence of spoofing and financial risks hinged on cyber threats. Another one is spoofing; it is the act of impersonating legitimate entities to gain unauthorized information and it is indeed a threat to the public and companies to some extent. The research introduces two primary methodologies to combat spoofing: an email filtering system using a machine learning algorithm and an encryption and decryption system using a Caesar Cipher and Python programming language. It distinguishes between approved domains and unapproved domains by using …
Heterogeneous Resources Cost-Aware Geo-Distributed Data Analytics, Minmin Zhang
Heterogeneous Resources Cost-Aware Geo-Distributed Data Analytics, Minmin Zhang
UNO Student Research and Creative Activity Fair
Many popular cloud service providers deploy tens of data centers (DCs) around the world to reduce user-perceived latency for better user experiences, in which a large amount of data is generated and stored in a geo-distributed manner. Geo-distributed Data Analytics (GDA) has gained great popularity in meeting the growing demand to mine meaningful and timely knowledge from such highly dispersed data. Since GDA systems require a large data migration between DCs via a wide area network (WAN), many existing works invested significant effort to optimize data transfer strategies to efficiently use limited WAN by considering the network pricing policies on …
"When They Say Weed Causes Depression, But It's Your Fav Antidepressant": Knowledge-Aware Attention Framework For Relationship Extraction, Shweta Yadav, Usha Lokala, Raminta Daniulaityte, Krishnaprasad Thirunarayan, Francois Lamy, Amit Sheth
"When They Say Weed Causes Depression, But It's Your Fav Antidepressant": Knowledge-Aware Attention Framework For Relationship Extraction, Shweta Yadav, Usha Lokala, Raminta Daniulaityte, Krishnaprasad Thirunarayan, Francois Lamy, Amit Sheth
Publications
With the increasing legalization of medical and recreational use of cannabis, more research is needed to understand the association between depression and consumer behavior related to cannabis consumption. Big social media data has potential to provide deeper insights about these associations to public health analysts. In this interdisciplinary study, we demonstrate the value of incorporating domain-specific knowledge in the learning process to identify the relationships between cannabis use and depression. We develop an end-to-end knowledge infused deep learning framework (Gated-K-BERT) that leverages the pre-trained BERT language representation model and domain-specific declarative knowledge source (Drug Abuse Ontology (DAO)) to jointly extract …
Bibliometric Survey For Stock Market Prediction Using Sentimental Analysis And Lstm, Pooja Bagane, Nimit Mehta Mr, Parth Kakde Mr, Nisarg Bramhbhatt Mr, Ishansh Sahni Mr, Sirbi Kotrappa Dr
Bibliometric Survey For Stock Market Prediction Using Sentimental Analysis And Lstm, Pooja Bagane, Nimit Mehta Mr, Parth Kakde Mr, Nisarg Bramhbhatt Mr, Ishansh Sahni Mr, Sirbi Kotrappa Dr
Library Philosophy and Practice (e-journal)
Creating an overview of the flow fundamentals of the global market trading and sublimation of equities into a superimposed system of economic agendas. Furthermore this leads to dynamic overlapping with the current technological advancements to create a platform for information exchange and inculcations. This created a new field of access points where we could enhance and analyse the data available and create an interface to predict the rise and fall trends involved with the stock market. These help create a sense of control and format over the public personification over the economic impacts and use social media and involve discrete …
The Role Of Institutional Repositories In Advancing Open Scholarship: A Case Study From The United Arab Emirates University, Amina Itani, Linda Östlundh Mrs.
The Role Of Institutional Repositories In Advancing Open Scholarship: A Case Study From The United Arab Emirates University, Amina Itani, Linda Östlundh Mrs.
The Journal of Electronic Theses and Dissertations
The digitization of theses and dissertations at the United Arab Emirates University (UAEU) began five years ago with the Digital Commons institutional repository (IR) platform, Scholarworks, employed for the purpose. The project, initiated by the University Library, exemplifies how academic libraries can take the lead in advocating for digital preservation and open access publishing of institutional research materials. This case study describes how the library’s Electronic Theses and Dissertations (ETD) initiative has provided an excellent model to the UAEU for it to start disseminating its research output and how the library’s copyright and open access policies have been crucial for …
Efficient Hardware Constructions For Error Detection Of Post-Quantum Cryptographic Schemes, Alvaro Cintas Canto
Efficient Hardware Constructions For Error Detection Of Post-Quantum Cryptographic Schemes, Alvaro Cintas Canto
USF Tampa Graduate Theses and Dissertations
Quantum computers are presumed to be able to break nearly all public-key encryption algorithms used today. The National Institute of Standards and Technology (NIST) started the process of soliciting and standardizing one or more quantum computer resistant public-key cryptographic algorithms in late 2017. It is estimated that the current and last phase of the standardization process will last till 2022-2024. Among those candidates, code-based and multivariate-based cryptography are a promising solution for thwarting attacks based on quantum computers. Nevertheless, although code-based and multivariate-based cryptography, e.g., McEliece, Niederreiter, and Luov cryptosystems, have good error correction capabilities, research has shown their hardware …
Welcome To The Journal Of Electronic Theses And Dissertations (J-Etd), Edward A. Fox
Welcome To The Journal Of Electronic Theses And Dissertations (J-Etd), Edward A. Fox
The Journal of Electronic Theses and Dissertations
On behalf of the Networked Digital Library of Theses and Dissertations (NDLTD; see our website with multiple aliases: ndltd.org, theses.org, dissertations.org), I welcome you to the first volume of J-ETD. Now is the time to broadly share through an archival journal some of the most interesting discussions related to the global movement around ETDs. We hope you will find this journal to be of interest, and will spread the word that it is globally accessible as an open access archival forum empowering graduate student researchers and universities to broadly contribute to scholarship, knowledge, education, and understanding. We hope you and …
Frequency Coordinated Control Strategy Of Microgrid Based On Fuzzy Prediction, Kunping Zhang, Hao Lin
Frequency Coordinated Control Strategy Of Microgrid Based On Fuzzy Prediction, Kunping Zhang, Hao Lin
Journal of System Simulation
Abstract: Aiming at the problem of frequency fluctuation of wind power generation connected to microgrid, a frequency coordinated control strategy based on model predictive control (MPC) is proposed. In this strategy, the wind turbine and plug-in hybrid electric vehicle (PHEV) are included in the frequency control system. The pitch angle of the fan and the charge and discharge of PHEV are controlled to adjust the grid frequency and supplement the frequency modulation resources of microgrid. WTG pitch angle control system and PHEV power control system are modeled, and their control principles are described. In order to prevent excessive use of …
Strategies In Botnet Detection And Privacy Preserving Machine Learning, Di Zhuang
Strategies In Botnet Detection And Privacy Preserving Machine Learning, Di Zhuang
USF Tampa Graduate Theses and Dissertations
Peer-to-peer (P2P) botnets have become one of the major threats in network security for serving as the infrastructure that responsible for various of cyber-crimes. Though a few existing work claimed to detect traditional botnets effectively, the problem of detecting P2P botnets involves more challenges. In this dissertation, we present two P2P botnet detection systems, PeerHunter and Enhanced PeerHunter. PeerHunter starts from a P2P hosts detection component. Then, it uses mutual contacts as the main feature to cluster bots into communities. Finally, it uses community behavior analysis to detect potential botnet communities and further identify bot candidates. Enhanced PeerHunter is an …
Guaranteed Cost Preview And Repetitive Control For Uncertain Linear Discrete Time-Delay Systems, Yonghong Lan, Jinlin He
Guaranteed Cost Preview And Repetitive Control For Uncertain Linear Discrete Time-Delay Systems, Yonghong Lan, Jinlin He
Journal of System Simulation
Abstract: For a class of uncertain linear discrete time-delay systems, a design method for guaranteed cost preview and repetitive controller is proposed . By introducing a repetitive controller in the forward channel to improve the tracking accuracy of the system, L-order difference operators are used to construct an augmented error system that contains preview information but does not include time delay, and the design problem of guaranteed cost preview and repetitive controller is converted into an output feedback adjustment problem. Using the Lyapunov stability theory and the linear matrix inequality method, the sufficient conditions for guaranteeing the asymptotic stability of …
Neural Network Optimized Sensorless Permanent Magnet Synchronous Motor Control System, Lixin Ma, Yongjie Zhu, Leyan Ji
Neural Network Optimized Sensorless Permanent Magnet Synchronous Motor Control System, Lixin Ma, Yongjie Zhu, Leyan Ji
Journal of System Simulation
Abstract: In order to solve the poor accuracy of the speed and rotor position of permanent magnet synchronous motor caused by sensor, a sensorless control system is proposed to calculate the speed and rotor position of PMSM with extended Kalman filtering algorithm. BP neural network algorithm is used to optimize the covariance matrix Q and R of EKF, which improves the accurate calculation values of rotational speed and rotor position. At the same time, the speed sliding mode controller combined with the current feed-forward decoupling unit are used to improve the stability of the whole control system. The simulation results …
An Improved Social Force Model For Crowd Simulation, Changhua Li, Yang Jing, Zhijie Li
An Improved Social Force Model For Crowd Simulation, Changhua Li, Yang Jing, Zhijie Li
Journal of System Simulation
Abstract: In view of the traditional social force model, it is difficult to deal with the problems of single pedestrian trajectory and loose crowd in the process of crowd evacuation, and an improved social force model is proposed. Based on the original social force model, the movement trajectory of the person is changed by considering the choice of the movement direction The intensity of panic and attraction in the process of pedestrian evacuation is considered to reproduce the self-organizing behavior in the process of pedestrian evacuation, and the simulations are performed in individual and group mode. The authenticity of the …
Research On The Method Of Operational Concept Description Based On Sysml, Siming Peng, Xiao Gang, Qingzhang Yu, Zeming Li
Research On The Method Of Operational Concept Description Based On Sysml, Siming Peng, Xiao Gang, Qingzhang Yu, Zeming Li
Journal of System Simulation
Abstract: For the convenience of understanding and communication between researchers among different domains, the standardized method for operational concept description is preferred. Hence, based on the principles of systems architecture, the System Model Language (SysML) is proposed for the visualized and standardized description of operational concept. The form of combination for Department of Defense Architecture Framework (DoDAF) and SysML during the description of operational concept is analyzed, and the multi-view point products are used to descript the operational background, capability requirement and systems architecture as well as the operational activity of operational concept. The "Distributed Lethality" is utilized as an …
Simulation Platform For Source-Load Control Of Active Power Based On Modular Architecture, Hu Yang, Wenying Liu, Liping Zhu, Li Xiao, Weizhou Wang
Simulation Platform For Source-Load Control Of Active Power Based On Modular Architecture, Hu Yang, Wenying Liu, Liping Zhu, Li Xiao, Weizhou Wang
Journal of System Simulation
Abstract: The integrated proportion of wind power is increasing year by year, and the source-load coordinated control of active power can effectively improve the level of wind power consumption. In order to ensure the effective application of the strategy, a simulation platform based on modular architecture is developed for source-load control of active power, including SQL Server database, timing control module of data interaction, calculation module of source-load control strategy, and output display module. The simulation platform solves the automatic control of data interaction timing in the process of source-load control, and visualizes the effect of the source-load control, so …
Path Designing Of Multi-Omnidirectional Wheel Collaborative Sorting Platform, Li Qi, Wang Wei
Path Designing Of Multi-Omnidirectional Wheel Collaborative Sorting Platform, Li Qi, Wang Wei
Journal of System Simulation
Abstract: Aiming at the problems of low efficiency, high labor cost and low flexibility of traditional logistics sorting system, an automatic logistics sorting system is designed. The improved A* algorithm and the artificial potential field method are used to realize the automatic path planning of the system by taking the transportation path as the research object. The A* algorithm is improved by adjusting the weights of actual cost and estimated cost, and the artificial potential field method is improved by adding virtual sub-target points and adjusting adaptive parameters, so as to complete the function of path planning of goods. Simulation …
Performance Evaluation Method For Load Control System Considering “Two Detailed Rules”, Yinsong Wang, Wang Kai
Performance Evaluation Method For Load Control System Considering “Two Detailed Rules”, Yinsong Wang, Wang Kai
Journal of System Simulation
Abstract: With the promulgation of the "two detailed rules" of regional power grid,the requirements by power system thermal power units are more and more strict, and has greatly affected their economic development. In order to combine the performance evaluation theory of multivariable control system with the engineering practice, the covariance index of multivariable control system is improved, and the assessment method of AGC (Automatic Generation Control) is analyzed and summarized. The improved covariance index of load Control system and the economic index based on the "two detailed rules" are proposed, and the comprehensive evaluation of load Control system is made …
Research On Indoor Emergency Evacuation Simulation Of Multi-Exit Based On Social Force Model, Haixiang Guo, Zeng Yang, Weiming Chen
Research On Indoor Emergency Evacuation Simulation Of Multi-Exit Based On Social Force Model, Haixiang Guo, Zeng Yang, Weiming Chen
Journal of System Simulation
Abstract: With the frequent occurrence of emergencies, how to evacuate dense pedestrians safely from indoor space with limited export is the key and difficult point of emergency evacuation research. Taking a university auditorium as an example to simulate through Anylogic, and the degree of consciousness is introduced to comprehensively reflect the safety education, safety training and familiarity of pedestrians and the expected speed of pedestrians in the primary social force model is improved. To solve the problem of uneven utilization of exports in multi-exit indoor, optimization plans including partition guidance and change the structure of exports are proposed. Simulation results …
A Survey Of Edge Computing Resource Allocation And Task Scheduling Optimization, Wang Ling, Chuge Wu, Wenhui Fan
A Survey Of Edge Computing Resource Allocation And Task Scheduling Optimization, Wang Ling, Chuge Wu, Wenhui Fan
Journal of System Simulation
Abstract: With the rapid development of Internet of Things (IoT) and mobile terminals, the concept of edge computing arises. By moving the computation and storage capacity to the edge of network, edge computing is able to deal with a large amount of data produced by IoT devices and the responsive request from IoT application. To improve the utility of edge resource, the quality of service and quality of user experience, resource allocation and task scheduling optimization problems under edge computing attract wide attention. It becomes more difficult due to the geographic separated and heterogeneous features of edge computing resource as …