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IoV environment exploring coordination:A federated learning approach

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Digital Communications and Networks 2024年第1期10卷 135-141页

作者： Tong Ding Lei Liu Yi Zhu Lizhen Cui Zhongmin Yan school of software Shandong UniversityJinan250101China

Exploring open fields with coordinated unmanned vehicles is popular in academia and *** of the most impressive applicable approaches is the Internet of Vehicles(lov).The IoV connects vehicles,road infrastructures and communication facilities to provide solutions for exploration ***,the coordination of acquiring information from multi-vehicles may risk data *** this end,sharing high-quality experiences instead of raw data has become an urgent *** paper employs a Deep Reinforcement Learning(DRL)method to enable IoVs to generate training data with prioritized experience and states,which can support the IoV to explore the environment more ***,a Federated Learning(FL)experience sharing model is established to guarantee the vehicles'*** numerical results show that the proposed method presents a better successful sharing rate and a more stable convergence within the comparison of fundamental *** experiments also suggest that the proposed method could support agents without full information to achieve the tasks.

关键词： Internet of vehicle Deep reinforcement learning Federated learning Data privacy

Towards a Full-Stack Dev Ops Environment (Platform-as-a-Service) for Cloud-Hosted Applications

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Tsinghua Science and Technology 2017年第1期22卷 1-9页

作者： Zhenhua Li Yun Zhang Yunhao Liu school of software Tsinghua University Beijing 100084 China

If every programmer of cloud-hosted apps possessed exceptional technical capability and endless patience, the Dev Ops environment（also known as Platform-as-a-Service, or Paa S） would perhaps become irrelevant. However, the reality is almost always the opposite case. Hence, IT engineers dream of a reliable and usable Dev Ops environment that can substantially facilitate their developments and simplify their *** Dev Ops environments include Google App Engine, Docker, Kubernetes, Mesos, and so forth. In other words, Paa S bridges the gap between vivid IT engineers and stiff cloud systems. In this paper, we comprehensively examine state-of-the-art Paa S solutions across various tiers of the cloud-computing Dev Ops stack. On this basis,we identify areas of consensus and diversity in their philosophies and methodologies. In addition, we explore cutting-edge solutions towards realizing a more fine-grained, full-stack Dev Ops environment. From this paper,readers are expected to quickly grasp the essence, current status, and future prospects of Paa S.

关键词： cloud computing Platform-as-a-Service(PaaS) DevOps development operation environment

Multi-scale joint feature network for micro-expression recognition

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Computational Visual Media 2021年第3期7卷 407-417页

作者： Xinyu Li Guangshun Wei Jie Wang Yuanfeng Zhou school of software Shandong UniversityJinan 250101China

Micro-expression recognition is a substantive cross-study of psychology and computer science,and it has a wide range of applications(e.g.,psychological and clinical diagnosis,emotional analysis,criminal investigation,etc.).However,the subtle and diverse changes in facial muscles make it difficult for existing methods to extract effective features,which limits the improvement of micro-expression recognition ***,we propose a multi-scale joint feature network based on optical flow images for micro-expression ***,we generate an optical flow image that reflects subtle facial motion *** optical flow image is then fed into the multi-scale joint network for feature extraction and *** proposed joint feature module(JFM)integrates features from different layers,which is beneficial for the capture of micro-expression features with different *** improve the recognition ability of the model,we also adopt a strategy for fusing the feature prediction results of the three JFMs with the backbone *** experimental results show that our method is superior to state-of-the-art methods on three benchmark datasets(SMIC,CASME II,and SAMM)and a combined dataset(3 DB).

关键词： micro-expression recognition multi-scale feature optical flow deep learning

An Efficient Reinforcement Learning Game Framework for UAV-Enabled Wireless Sensor Network Data Collection

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Journal of Computer Science & Technology 2022年第6期37卷 1356-1368页

作者： Tong Ding Ning Liu Zhong-Min Yan Lei Liu Li-Zhen Cui school of software Shandong UniversityJinan 250101China

With the developing demands of massive-data services,the applications that rely on big geographic data play crucial roles in academic and industrial *** aerial vehicles(UAVs),combining with terrestrial wireless sensor networks(WSN),can provide sustainable solutions for data *** rising demands for efficient data collection in a larger open area have been posed in the literature,which requires efficient UAV trajectory planning with lower energy consumption ***,there are amounts of inextricable solutions of UAV planning for a larger open area,and one of the most practical techniques in previous studies is deep reinforcement learning(DRL).However,the overestimated problem in limited-experience DRL quickly throws the UAV path planning process into a locally optimized ***,using the central nodes of the sub-WSNs as the sink nodes or navigation points for UAVs to visit may lead to extra collection *** paper develops a data-driven DRL-based game framework with two partners to fulfill the above demands.A cluster head processor(CHP)is employed to determine the sink nodes,and a navigation order processor(NOP)is established to plan the *** and NOP receive information from each other and provide optimized solutions after the Nash *** numerical results show that the proposed game framework could offer UAVs low-cost data collection trajectories,which can save at least 17.58%of energy consumption compared with the baseline methods.

关键词： wireless sensor network efficient data collection deep reinforcement learning game theory

An Online Algorithm Based on Replication for Using Spot Instances in IaaS Clouds

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Journal of Computer Science & Technology 2024年第1期39卷 103-115页

作者：许志伟潘丽刘士军 school of software Shandong UniversityJinan 250101China

Infrastructure-as-a-Service(IaaS)cloud platforms offer resources with diverse buying *** can run an instance on the on-demand market which is stable but expensive or on the spot market with a significant ***,users have to carefully weigh the low cost of spot instances against their poor *** instances will be revoked when the revocation event ***,an important problem that an IaaS user faces now is how to use spot in-stances in a cost-effective and low-risk *** on the replication-based fault tolerance mechanism,we propose an on-line termination algorithm that optimizes the cost of using spot instances while ensuring operational *** prove that in most cases,the cost of our proposed online algorithm will not exceed twice the minimum cost of the optimal of-fline algorithm that knows the exact future a *** a large number of experiments,we verify that our algorithm in most cases has a competitive ratio of no more than 2,and in other cases it can also reach the guaranteed competitive ratio.

关键词： Infrastructure-as-a-Service(IaaS)cloud cost management competitive analysis online algorithm spot instance

Probabilistic Modeling and Optimization of Real-Time Protocol for Multifunction Vehicle Bus

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Tsinghua Science and Technology 2016年第5期21卷 561-569页

作者： Lifan Su Min Zhou Hai Wan Ming Gu school of software Tsinghua University Beijing 100084 China

In this paper, we present the modeling and optimization of a Real-Time Protocol（RTP） used in Train Communication Networks（TCN）. In the proposed RTP, message arbitration is represented by a probabilistic model and the number of arbitration checks is minimized by using the probability of device activity. Our optimized protocol is fully compatible with the original standard and can thus be implemented easily. The experimental results demonstrate that the proposed algorithm can reduce the number of checks by about 50%, thus significantly enhancing bandwidth.

关键词： train communication network probabilistic modelling protocol optimization

Hypergraph Computation

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Engineering 2024年第9期40卷 188-201页

作者： Yue Gao Shuyi Ji Xiangmin Han Qionghai Dai school of software Tsinghua UniversityBeijing 100084China

Practical real-world scenarios such as the Internet,social networks,and biological networks present the challenges of data scarcity and complex correlations,which limit the applications of artificial *** graph structure is a typical tool used to formulate such correlations,it is incapable of modeling highorder correlations among different objects in systems;thus,the graph structure cannot fully convey the intricate correlations among *** with the aforementioned two challenges,hypergraph computation models high-order correlations among data,knowledge,and rules through hyperedges and leverages these high-order correlations to enhance the ***,hypergraph computation achieves collaborative computation using data and high-order correlations,thereby offering greater modeling *** particular,we introduce three types of hypergraph computation methods:①hypergraph structure modeling,②hypergraph semantic computing,and③efficient hypergraph *** then specify how to adopt hypergraph computation in practice by focusing on specific tasks such as three-dimensional(3D)object recognition,revealing that hypergraph computation can reduce the data requirement by 80%while achieving comparable performance or improve the performance by 52%given the same data,compared with a traditional data-based method.A comprehensive overview of the applications of hypergraph computation in diverse domains,such as intelligent medicine and computer vision,is also ***,we introduce an open-source deep learning library,DeepHypergraph(DHG),which can serve as a tool for the practical usage of hypergraph computation.

关键词： High-order correlation Hypergraph structure modeling Hypergraph semantic computing Efficient hypergraph computing Hypergraph computation framework

The LP-rounding plus greed approach for partial optimization revisited

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Frontiers of Computer Science 2022年第1期16卷 67-75页

作者： Peng ZHANG school of software Shandong UniversityJinan250101China

There are many optimization problems having the following common property:Given a total task consisting of many subtasks,the problem asks to find a solution to complete only part of these *** include the k-Forest problem and the k-Multicut problem,*** problems are called partial optimization problems,which are often *** this paper,we systematically study the LP-rounding plus greed approach,a method to design approximation algorithms for partial optimization *** approach is simple,powerful and *** show how to use this approach to design approximation algorithms for the k-Forest problem,the k-Multicut problem,the k-Generalized connectivity problem,etc.

关键词： k-Forest k-Multicut partial optimization LP-rounding Greedy algorithm Approximation algorithm

Grey incidence clustering method based on multidimensional dynamic time warping distance

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Journal of Systems Engineering and Electronics 2017年第5期28卷 946-954页

作者： Jin Dai Yi Yan Yuhong He school of software Engineering Chongqing University of Posts and Telecommunications

The traditional grey incidence degree is mainly based on the distance analysis methods, which is measured by the displacement difference between corresponding points between sequences. When some data of sequences are missing (inconsistency in the length of the sequences), the only way is to delete the longer sequences or to fill the shorter sequences. Therefore, some uncertainty is introduced. To solve this problem, by introducing three-dimensional grey incidence degree (3D-GID), a novel GID based on the multidimensional dynamic time warping distance (MDDTW distance-GID) is proposed. On the basis of it, the corresponding grey incidence clustering (MDDTW distance-GIC) method is constructed. It not only has the simpler computation process, but also can be applied to the incidence comparison between uncertain multidimensional sequences directly. The experiment shows that MDDTW distance-GIC is more accurate when dealing with the uncertain sequences. Compared with the traditional GIC method, the precision of the MDDTW distance-GIC method has increased nearly 30%.

关键词： grey incidence analysis (GIA) dynamic time warping (DTW) distance grey incidence clustering