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Monte Carlo Simulation-Based Robust Workflow Scheduling for Spot Instances in Cloud Environments

Tsinghua Science and Technology 2024年第1期29卷 112-126页

作者： Quanwang Wu Jianzhao Fang Jie Zeng Junhao Wen Fengji Luo College of Computer Science Chongqing UniversityChongqing 400044China National Experimental Teaching Demonstration Center Chongqing UniversityChongqing 400044China College of Big Data and Software Engineering Chongqing UniversityChongqing 400044China School of Civil Engineering The University of SydneySydney 2006Australia

When deploying workflows in cloud environments,the use of Spot Instances(SIs)is intriguing as they are much cheaper than on-demand ***,Sls are volatile and may be revoked at any time,which results in a more challenging scheduling problem involving execution interruption and hence hinders the successful handling of conventional cloud workflow scheduling *** some scheduling methods for Sls have been proposed,most of them are no more applicable to the latest Sls,as they have evolved by eliminating bidding and simplifying the pricing *** study focuses on how to minimize the execution cost with a deadline constraint when deploying a workflow on volatile Sls in cloud *** on Monte Carlo simulation and list scheduling,a stochastic scheduling method called MCLS is devised to optimize a utility function introduced for this *** the Monte Carlo simulation framework,MCLS employs sampled task execution time to build solutions via deadline distribution and list scheduling,and then returns the most robust solution from all the candidates with a specific evaluation mechanism and selection *** results show that the performance of MCLS is more competitive comparedwithtraditionalalgorithms.

关键词： constrained optimization Monte Carlo simulation robustness Spot Instances(Sls) workflow scheduling

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Tackling Non-stationarity in Decentralized Multi-Agent Reinforcement Learning with Prudent Q-Learning 19th

Tackling Non-stationarity in Decentralized Multi-Agent Rein...

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19th International Conference on Web Information Systems and Applications, WISA 2022

作者： Wei, Jianan Wang, Liang Tao, Xianping Hu, Hao Wu, Haijun State Key Laboratory for Novel Software Technology Nanjing University Nanjing210023 China National Experimental Teaching Demonstration Center of Computer Science Technology and Software Engineering Nanjing University Nanjing210023 China

ISBN: (纸本)9783031203084

Multi-Agent Reinforcement Learning (MARL) is challenging due to the non-stationary issue of an agent’s learning environment caused by multiple co-evolving agents, i.e., the uncertainty rises with multiple agents learning and evolving simultaneously. Though centralized learning can solve the problem to some degree, it is hard to expand into numerous agents or real-world applications. We focus on the native property of the non-stationary environment and use a independent method to alleviate its harmful influence. Here are the two main contributions of this article: 1) We formalize the non-stationary environment by supposing it follows a pessimistic transition, and we explain the existence of a lower bound of accumulated reward expectation that the agent can learn. 2) We devise a scheme called Prudent Q-Learning (PQL) based on independent learning for controlling multi-agent systems in non-stationary environments. We present both tabular and Deep Q-Learning based implementations of the proposed Prudent Q-Learning scheme. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Reinforcement learning

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Research of Virtual Simulation Experiment Course Resource Intelligent Information System Construction 2

Research of Virtual Simulation Experiment Course Resource In...

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2nd IEEE International Conference on Power, Electronics and computer Applications, ICPECA 2022

作者： Wang, Yangping Dang, Jianwu Yong, Jiu Wang, Wenrun Yue, Biao Jin, Fangrui Computer Science and Technology Experimental Teaching Demonstration Center of National Lanzhou Jiaotong University National Virtual Simulation Experiment Teaching Center of Railway Traffic Information and Control Lanzhou Jiaotong University Gansu Prov. Eng. Research Center for Artificial Intelligence and Graphics and Image Processing Lanzhou730070 China National Virtual Simulation Experiment Teaching Center of Railway Traffic Information and Control Lanzhou Jiaotong University College of Intelligence and Computing Tianjin University Computer Science and Technology Experimental Teaching Demonstration Center of National Lanzhou Jiaotong University Gansu Prov. Eng. Research Center for Artificial Intelligence and Graphics and Image Processing Lanzhou730070 China College of Electronic and Information Engineering Lanzhou Jiaotong University Gansu Provincial Engineering Research Center for Artificial Intelligence and Graphics and Image Processing Lanzhou730070 China

ISBN: (纸本)9781665442763

In order to enable the construction of virtual simulation experiment resources in colleges and universities to keep up with the development of professional technology, this paper proposes to build a 'diversified virtual simulation experiment teaching resource construction system' through exploration and research. With the help of virtual reality, AR, panoramic roaming, video and other technologies, it provides a unified development framework, development documents and case templates for professional teachers to independently develop virtual simulation experiment teaching resources in line with undergraduate teaching, and helps teachers quickly build virtual simulation experiment resources in accordance with unified standards. It effectively solves the problems that it is difficult for college teachers to independently develop virtual simulation courseware and the technology is not unified. © 2022 IEEE.

关键词： Virtual reality

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Adaptive Density Peak Algorithm Based on K-nearest Neighbors with Pre-screening Strategy 6th

Adaptive Density Peak Algorithm Based on K-nearest Neighbors...

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6th Euro-China Conference on Intelligent Data Analysis and Applications, ECC 2019

作者： Zhao, Long Liang, Yong-quan Fan, Jian-cong College of Computer Science and Engineering Shandong University of Science and Technology Qingdao China Provincial Key Lab for Information Technology of Wisdom Mining of Shandong Province Shandong University of Science and Technology Qingdao China Provincial Experimental Teaching Demonstration Center of Computer Shandong University of Science and Technology Qingdao China

ISBN: (纸本)9789811650352

Clustering by fast search and find of density peaks (DPC) is a new kind of clustering algorithm based on density and distance, which can obtain arbitrary shape of the clusters efficiently. It chooses the cluster centers based on the high value of density and distance. However, in the process of calculating density and distance, the wrong selection of cutoff distance will lead to the clustering performance because initial cluster centers are not selected correctly. In addition, the allocation strategy of one-step is not robust and easy to cause subsequent assignment errors. To overcome these defects, the density peak algorithm based on K-nearest neighbors with pre-screening strategy (PADPC) is proposed in this paper which can effectively increase the robustness of the original algorithm and achieve better experimental results. Experiments on classic datasets show the proposed clustering algorithm outperforms other competitive clustering algorithm greatly. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Clustering algorithms

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A Real Time Automatic Composition Algorithm for Mobile Terminal 3

A Real Time Automatic Composition Algorithm for Mobile Termi...

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3rd IEEE International Conference on Frontiers Technology of Information and computer, ICFTIC 2021

作者： Shao, Junhua Long, Peng Li, Qiang Lanzhou Jiaotong University National Experimental Teaching Demonstration Center of Computer Science and Technology Lanzhou China Yousan Education and Technology Co. Ltd Beijing China

ISBN: (纸本)9781665406055

Photo composition is one of the most basic skills in photography and image processing. Different composition methods often lead to different perceptual effects. Different application scenarios need different composition methods. For the scenes that need to extract main information such as website blog, good composition method is to select the most important information in the image, and for photography and other application scenes, good composition method is to keep the aesthetic feeling of the image and enhance the expressive power. In view of the need to keep the main body in composition and reduce the background area, this paper proposes an automatic composition algorithm based on lightweight salient object detection model and minimum information loss. The test is carried out on the CUHK composition data set and the Flick cropping composition data set. The IOU, model size and model running time are used as quantitative evaluation indexes, Compared with the mainstream aesthetic composition model, the experimental results show that the proposed method can achieve the same performance as the mainstream aesthetic based composition model, while the operation time is only one tenth of the aesthetic model, the model volume is only one percent of the aesthetic model, and the composition results are more stable, which is very suitable for the mobile terminal real-time automatic composition algorithm. © 2021 IEEE.

关键词： Photography

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Chinese Text Emotional Analysis Based on Bi-LSTM Model Fusing Emotional Features 6th

Chinese Text Emotional Analysis Based on Bi-LSTM Model Fusin...

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6th Euro-China Conference on Intelligent Data Analysis and Applications, ECC 2019

作者： Li, Hao Fan, Jian-cong College of Computer Science and Engineering Shandong University of Science and Technology Qingdao China Provincial Key Lab for Information Technology of Wisdom Mining of Shandong Province Shandong University of Science and Technology Qingdao China Provincial Experimental Teaching Demonstration Center of Computer Shandong University of Science and Technology Qingdao China

ISBN: (纸本)9789811650352

With the development of neural network, the method based on neural network is widely used in affective analysis. This model can get better results than the traditional machine-based learning method. However, it ignores a large number of existing emotional knowledge, such as emotional lexicon. In order to solve the problem, this paper proposes a features construction method based on emotional lexicon, and incorporates features into Bi-LSTM. The experimental results show that the improved Bi-LSTM can obtain higher F1 score. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Sentiment analysis

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Towards Emotion-awareness in Programming Education with Behavior-based Emotion Estimation

Towards Emotion-awareness in Programming Education with Beha...

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IEEE Annual International computer Software and Applications Conference (COMPSAC)

作者： Yuqian Zhuang Liang Wang Zhiwen Zheng Hao Hu Haijun Wu Xianping Tao State Key Laboratory for Novel Software Technology Nanjing University Nanjing China National Experimental Teaching Demonstration Center of Computer Science Technology and Software Engineering Nanjing China

ISBN: (数字)9781665488105

ISBN: (纸本)9781665488112

Existing studies in both psychology and software engineering have shown the importance of emotions in complex learning and programming tasks. For students who are learning to program, rich emotions are experienced which can provide valuable feedback to their teachers. To accurately model stu-dents' emotions, this paper adopts the well-recognized model of emotions during complex learning that involves four states: engaged, confused, frustrated, and bored. To perform continuous estimation of students' emotions in a non-intrusive manner, this paper proposes to track students' programming behavior and estimate their corresponding emotional states. Compare to the existing approaches on acquiring the students' emotional states with self-reports or bio-sensors, the proposed approach is more feasible in conducting real-world, and large-scale studies for not requiring extensive human interventions or additional devices. Evaluated using data collected from a real-world course project, the proposed approach is showed to be promising for achieving an estimation accuracy of 72.06 % for the above four emotional states. As an enabling technology, the proposed is potentially useful in supporting many applications and improve the quality of programming education in computer science.

关键词： Emotion recognition Computational modeling Education Estimation Psychology Software Mice

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Exploration and application of virtual simulation practice teaching evaluation system under the background of new engineering 16

Exploration and application of virtual simulation practice t...

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16th IEEE International Conference on computer Science and Education, ICCSE 2021

作者： Yong, Jiu Wang, Yangping Dang, Jianwu Lanzhou Jiaotong Univeristy The National Computer Experimental Teaching Demonstration Center Lanzhou China Lanzhou Jiaotong University The National Virtual Simulation Experiment Teaching Center of Railway Traffic Information and Control China Lanzhou Jiaotong University The School of Electronic and Information Engineering China Gansu Provincial Engineering Research Center for Artificial Intelligence and Graphics and Image Processing Lanzhou China

ISBN: (纸本)9781665414685

Virtual simulation experiment teaching can be carried out in any environment without the limitation of time and space, and used repeatedly for learning, more intuitive understanding of principle and method of the whole experiment, to combine the experimental content and abstract theory, and teachers can improve students' learning situation in virtual simulation teaching line tracking. The exploration and application of evaluation system of virtual simulation practice teaching under the background of new engineering is carried out. By scoring the students' preview, operation, experimental results and reports, and examination, a four-stage process evaluation method of 'preview before class - experimental operation - review after class comprehensive assessment' is constructed. The core of the evaluation system is the cultivation of virtual simulation talents' practice and innovation ability, and virtual simulation is emphasized. The exploration of real experiment teaching process evaluation system and the establishment of comprehensive evaluation index system can promote the deep integration of classroom teaching and virtual simulation experiment teaching, cultivate virtual simulation practice teaching resources and develop teachers, and make the virtual simulation experiment teaching evaluation mode more perfect. © 2021 IEEE.

关键词： Virtual reality

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Prediction of cutting power and surface quality, and optimization of cutting parameters using new inference system in high-speed milling process

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Advances in Manufacturing 2021年第3期9卷 388-402页

作者： Long-Hua Xu Chuan-Zhen Huang Jia-Hui Niu Jun Wang Han-Lian Liu Xiao-Dan Wang Center for Advanced Jet Engineering Technologies Key Laboratory of High-efficiency and Clean Mechanical Manufacture(Ministry of Education)National Experimental Teaching Demonstration Center for Mechanical Engineering(Shandong University)School of Mechanical EngineeringShandong UniversityJinanPeople’s Republic of China School of Mechanical and Manufacturing Engineering The University of New South Wales(UNSW)SydneyNSW2052Australia Department of Computer Science and Software Engineering Xi’an Jiaotong-Liverpool UniversitySuzhou215123JiangsuPeople’s Republic of China

During the actual high-speed machining process,it is necessary to reduce the energy consumption and improve the machined surface ***,the appropriate prediction models and optimal cutting parameters are difficult to obtain in complex machining ***,a novel intelligent system is proposed for prediction and optimization.A novel adaptive neuro-fuzzy inference system(NANFIS)is proposed to predict the energy consumption and surface *** the NANFIS model,the membership functions of the inputs are expanded into:membership superior and membership *** membership functions are varied based on the machining *** inputs of the NANFIS model are cutting parameters,and the outputs are the machining *** optimization,the optimal cutting parameters are obtained using the improved particle swarm optimization(IPSO)algorithm and NANFIS ***,the IPSO algorithm as a learning algorithm is used to train the NANFIS *** proposed intelligent system is applied to the high-speed milling process of compacted graphite *** experimental results show that the predictions of energy consumption and surface roughness by adopting the NANFIS models are up to 91.2%and 93.4%,*** NANFIS models can predict the energy consumption and surface roughness more accurately compared with other intelligent *** on the IPSO algorithm and NANFIS models,the optimal cutting parameters are obtained and validated to reduce both the cutting power and surface roughness and improve the milling *** is demonstrated that the proposed intelligent system is applicable to actual high-speed milling processes,thereby enabling sustainable and intelligent manufacturing.

关键词： Novel adaptive neuro-fuzzy inference system(NANFIS)model Improved particle swarm optimization(IPSO)algorithm Energy consumption Surface roughness Multiobjective optimization

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Design and research on 3d interactive experiment case of virtual railway signal equipment based on hardware perception 16

Design and research on 3d interactive experiment case of vir...

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16th IEEE International Conference on computer Science and Education, ICCSE 2021

作者： Wang, Yangping Yong, Jiu Wang, Wenrun Yue, Biao Yang, Xu The National Computer Experimental Teaching Demonstration Center Lanzhou Jiaotong Univeristy Lanzhou China Lanzhou Jiaotong University The National Virtual Simulation Experiment Teaching Center of Railway Traffic Information and Control Lanzhou China Lanzhou Jiaotong University The School of Electronic and Information Engineering Lanzhou China Gansu Prov. Eng. Research Center for Artificial Intelligence and Graphics and Image Processing Lanzhou China

ISBN: (纸本)9781665414685

With the continuous increase of railway operation mileage, higher requirements are put forward for professionals who can operate and maintain railway signal equipment accurately and skillfully. In the process of practical teaching for employees, due to the characteristics of railway operation, such as fast train running speed, high traffic density, scattered equipment layout and high safety requirements for on-site operation, the traditional practical teaching of railway signal equipment based on on-site observation is difficult for students to master the working principle of equipment, real-time information transmission process, equipment action status, linkage with other equipment, etc. To a certain extent, it limits the cultivation of students' engineering practice ability and innovation ability. The research has developed a 3D interactive experiment system of virtual railway signal equipment based on hardware perception. Through controlling 3D virtual signal equipment by hardware sensing component, students can know the internal components, composition and operation environment of the equipment at any time, so that they can quickly understand the function of railway signal equipment and understand the actual action principle of signal equipment in railway station. © 2021 IEEE.

关键词： Virtual reality

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