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Enhanced redirection strategy for peer to peer services in high-speed and large-capacity ethernet passive optical networks

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Journal of Optical Communications 2023年第s1期44卷 S887-S897页

作者： Yu, Jinxia Han, Shangya Ye, Qing Qin, Panke Tang, Yongli Wang, Xiaojun Li, Lixiang College of Computer Science and Technology Henan Polytechnic University Henan Jiaozuo China Henan Polytechnic University Henan Jiaozuo China Dublin City University Jiaozuo Dublin Ireland

An important problem of network traffic is how to efficiently carry massive amounts of data traffic generated by Peer-to-Peer (P2P) services in high-speed and large-capacity optical access networks. P2P file-sharing traffic is regarded as one of the biggest bandwidth consumption in the world. Internet service providers can reduce the bandwidth burden in the feeder fiber by localizing the network traffic. In this paper, we propose an enhanced redirection strategy based on the optimized MPCP protocol (ERS-MPCP) to redirect the traffic into the access network and reduce the latency. A Markov chain is used for mathematical modeling. In the proposed strategy, we build a simulation platform for network simulation. Simulation results show that our strategy can improve the overall redirection success rate by up to 9%, thereby reducing the data traffic burden on the core network. © 2023 Walter de Gruyter GmbH. All rights reserved.

关键词： Ethernet

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A Network Security Risk Assessment Method Based on a B_NAG Model

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computer Systems science & Engineering 2021年第7期38卷 103-117页

作者： Hui Wang Chuanhan Zhu Zihao Shen Dengwei Lin Kun Liu MengYao Zhao School of Computer Science&Technology Henan Polytechnic UniversityJiaozuo454000China Office of Educational Administration Jiaozuo UniversityJiaozuo454000China Department of Computer Science University College LondonLondonUnited Kingdom

computer networks face a variety of *** network attacks are contagious and destructive,and these types of attacks can be harmful to society and computer network *** evaluation is an effective method to solve network security *** accurate assessment of the vulnerabilities of computer networks,this paper proposes a network security risk assessment method based on a Bayesian network attack graph(B_NAG)***,a new resource attack graph(RAG)and the algorithm E-Loop,which is applied to eliminate loops in the B_NAG,are ***,to distinguish the confusing relationships between nodes of the attack graph in the conversion process,a related algorithm is proposed to generate the B_NAG ***,to analyze the reachability of paths in B_NAG,the measuring indexs such as node attack complexity and node state transition are defined,and an iterative algorithm for obtaining the probability of reaching the target node is *** this basis,the posterior probability of related nodes can be calculated.A simulation environment is set up to evaluate the effectiveness of the B_NAG *** experimental results indicate that the B_NAG model is realistic and effective in evaluating vulnerabilities of computer networks and can accurately highlight the degree of vulnerability in a chaotic relationship.

关键词： Network attack graph Bayesian network state transition reachability risk assessment

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Entity Embedding and Relational Path on Small Samples for Knowledge Graph Completion 3

Entity Embedding and Relational Path on Small Samples for Kn...

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3rd International Conference on Artificial Intelligence and computer Engineering, ICAICE 2022

作者： Yu, Kaige Zhang, Long Zheng, Qiusheng Li, Jiahao Henan Key Laboratory on Public Opinion Intelligent Analysis Zhengzhou China School of Computer Science Zhongyuan University of Technology Zhengzhou China

ISBN: (纸本)9781510663473

In the modeling work of knowledge graph completion(KGC), we propose a KGC model considering both entity embeddings and relational paths for small sample data. The relational path information between entities can identify the relative positions of two entities in the knowledge graph, and if the distance is too far there is no need for link prediction with high probability, so limiting the number of hopes of relational path can reduce the cost of link prediction. There are many link prediction models that only consider relations, but such models are not suitable for small sample datasets because there are too few types of relations in small datasets, and considering only relations is not a good way to characterize entities, so we added entity embeddings to consider relational paths, aggregated entity neighborhoods and relational neighborhoods around entities to target entities, and finally combined entity embeddings with relational paths to perform link prediction tasks. We have tested on three small sample datasets, and achieved remarkable results. © 2023 SPIE.

关键词： Knowledge graph

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A multi-scale sarcasm sentiment recognition algorithm incorporating sentence hierarchical representation 3

A multi-scale sarcasm sentiment recognition algorithm incorp...

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3rd International Conference on Artificial Intelligence and computer Engineering, ICAICE 2022

作者： Hao, Yu Zhang, Long Zheng, Qiusheng Niu, Liyue Henan Key Laboratory on Public Opinion Intelligent Analysis Zhengzhou China School of Computer Science Zhongyuan University of Technology Zhengzhou China

ISBN: (纸本)9781510663473

Sarcasm is a special kind of linguistic sentiment that is widely used in a wide range of social media to express strong emotions in users. Therefore, the task of sarcasm recognition is particularly important for social media analysis. There are few studies on sarcasm sentiment recognition in Chinese, and they often ignore the complex interactions between different syntactic components of a sentence, such as sentiment words, entities, dummy words, and special punctuation that occur in the text. In order to improve the accuracy of Chinese sarcasm recognition, this paper proposes a multi-scale neural network sarcasm recognition algorithm incorporating a hierarchical representation of sentences, taking into account the semantic information of sentences and the relationship features between different syntactic components. The hierarchical syntactic tree is reconstructed to distinguish the key components of the sentence, and the multi-channel convolutional network is used to mine the relational features between syntactic levels and deeply fuse them with semantic information to perform the Chinese sarcastic sentiment recognition task. We have tested the method on a publicly available Chinese sarcastic comment dataset, and the results show that the method can effectively improve the accuracy rate of Chinese sarcastic sentiment recognition. © 2023 SPIE.

关键词： Syntactics

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Feature fusion-based weighted broad learning system for imbalanced data 8

Feature fusion-based weighted broad learning system for imba...

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8th IEEE Information technology and Mechatronics Engineering Conference, ITOEC 2025

作者： Li, Yanting Wang, Yusha Jin, Junwei Philip Chen, C.L. Zhengzhou University of Light Industry College of Computer Science and Technology Zhengzhou China Henan University of Technology College of Artificial Intelligence and Big Data Zhengzhou China South China University of Technology School of Computer Science and Engineering Guangzhou China

ISBN: (纸本)9798331517915

Broad Learning System (BLS), characterized by its flat architecture as an efficient neural network, has garnered significant interest for its benefits in terms of training velocity and network scalability. However, BLS does not perform well when dealing with imbalanced classification problems. First, conventional BLS neglects the intrinsic logical information contained in the original input data, which may be critical for classification and prediction. Second, BLS fails to emphasize the significance of minority classes in imbalanced data scenarios. In this paper, we propose a feature fusion-based weighted broad learning system. Unlike traditional BLS, we combine the original features and broad features as fused features for training. Additionally, we introduce a weight generation mechanism that assigns higher weights to minority classes, enhancing the model's focus on these classes. A closed solution is available for the issue, and the transformation matrix can be effectively resolved. The experimental results on multiple imbalanced datasets show that our method is superior to other imbalanced methods. © 2025 IEEE.

关键词： Calibration

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HTSA: A Hybrid Tree Seed Algorithm based on Differential Evolution with Dynamic Population Diversity Maintenance 4

HTSA: A Hybrid Tree Seed Algorithm based on Differential Evo...

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4th International Conference on Artificial Intelligence, Robotics, and Communication, ICAIRC 2024

作者： Han, Dongliang Chang, Hui Wang, Xuance Chen, Mengyao Ji, Yvzhu Hao, Xinran Zhang, Shengwei Cui, Hao Jilin University of Finance and Economics School of Management Science and Information Engineering Changchun China Zhengzhou University of Light Industry College of Electrical and Information Engineering Zhengzhou China Henan University of Science and Technology Modong Polytechnic Faculty Luoyang China

ISBN: (纸本)9798331531225

Based on the problem of Tree Seed Algorithm (TSA), this paper proposes a Hybrid Tree Seed Algorithm (Hybrid-Tree Seed Algorithm, HTSA) based on Differential Evolution and Dynamic Population Diversity Maintenance. HTSA effectively overcomes the limitations of the original TSA by introducing key enhancement mechanisms. By combining Bernoulli mapping initialization, HTSA ensures that the population distribution is more balanced and efficient compared to the stochastic mapping of TSA. Moreover, the introduction of a positional update formula inspired by the Sparrow Search Algorithm in the seed updating enhances population diversity and convergence, especially in the late optimization stages. Integration with Differential Evolution (DE) further enhances global exploration capabilities. Together, these modifications address issues such as premature convergence and sensitivity to local optimal values in *** experiments showed that HTSA outperformed TSA,EST-TSA and other benchmark algorithms, showing significant advantages in optimization power, convergence rate and population diversity. © 2024 IEEE.

关键词： Anthropogenic

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A dynamic program analysis-based method for floating-point program precision loss detection

A dynamic program analysis-based method for floating-point p...

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2023 International Conference on computer Network Security and Software Engineering, CNSSE 2023

作者： Zhang, Yaguang Wang, Lei Wang, Yizhuo Xu, Fangjie Henan Key Laboratory on Public Opinion Intelligent Analysis Zhengzhou China School of Computer Science Zhongyuan University of Technology Zhengzhou China

ISBN: (数字)9781510666528

ISBN: (纸本)9781510666511

The loss of precision in floating-point programs is necessary to detect the loss of precision in floating-point programs because of the computational errors in floating-point operations, which can lead to the loss of precision in floating-point programs and affect the reliability of the upper-level software systems that call them. The inherent storage form of floating-point data makes it impossible to represent all real numbers fully, and the rounding error and error accumulation in floating-point operations make it difficult to detect the precision loss in floating-point programs. In this paper, we propose a dynamic analysis method to detect the precision loss of floating-point programs. First, we analyze the organization of the source code with the front-end Clang tool of LLVM to locate the floating-point data declarations and floating-point operations. Then we run the floating-point operations simultaneously with the higher precision MPFR operations with the help of the Dyninst staking framework to detect the precision loss at the statement level and record the precision loss of the floating-point. The precision loss of each step of the program is recorded. The precision loss change graph is generated to locate the floating-point precision loss. By testing the commonly used functions in the GSL library and some test cases in FPPench, the relative error of the method in this paper is improved by 43% on average compared with the randomly generated input data method to detect GSL functions. The relative error is improved by 1.8 bits on average compared with the Herbgrind tool for testing against FPPench. © 2023 SPIE.

关键词： Digital storage

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Momentum Contrastive Learning for Sequential Recommendation 26

Momentum Contrastive Learning for Sequential Recommendation

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26th International Conference on computer Supported Cooperative Work in Design, CSCWD 2023

作者： Shi, Bing Tan, Wenan Yu, Pengfei Nanjing University of Aeronautics and Astronautics College of Computer Science and Technology Nanjing211106 China Shanghai Polytechnic University School of Computer and Information Engineering Shanghai201209 China

ISBN: (纸本)9798350331684

Contrastive self-supervised learning (SSL) based Sequential Recommendations (SR) have recently achieved significant performance improvements in addressing the data sparsity problem, which hinders learning high-quality user representations. However, current contrastive SSL based models ignore the importance of consistency between sample pairs. Consistency means the similarity degree between the feature representation of encoded sample pairs, and the higher the consistency, the better the feature learning. To figure out the benefits of consistency and utilize it effectively, Momentum Contrastive Learning for Sequential Recommendation (MCL4SRec) is designed. Existing experiments on four public datasets demonstrate the superiority of MCL4SRec, which achieves state-of-the-art performance over existing baselines. © 2023 IEEE.

关键词： Momentum

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A Novel of Proactive Caching Policy for Privacy-Preserving Using Federated Learning and Lottery Hypothesis in Edge Computing 26

A Novel of Proactive Caching Policy for Privacy-Preserving U...

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26th International Conference on computer Supported Cooperative Work in Design, CSCWD 2023

作者： Wu, Xiaotong Tan, Wenan Nanjing University of Aeronautics and Astronautics College of Computer Science and Technology Nanjing211106 China Shanghai Polytechnic University School of Computer and Information Engineering Shanghai201209 China

ISBN: (纸本)9798350331684

Proactive caching is proving to be an increasingly efficient way to handle massive amounts of data as mobile edge computing becomes more widespread. Utilizing the edge nodes' closer proximity to end users, caching content beforehand at the edge nodes can enable quick replies to end-user queries and lower transmission latency. The fact that edge servers have limited resources makes prediction for cached material particularly crucial. The collaboration between edge nodes and the protection of user data privacy have not been taken into account by the numerous studies recently proposed for predicting content popularity. This work suggests a proactive caching strategy (LT-FLPC) by using federated learning and the lottery hypothesis to address the above issues. The lottery hypothesis is used to address the problem of user privacy and data protection when edge nodes communicate with the central server. Given the existence of collaborative domains between different edge nodes, federated learning is employed to achieve the proactive caching strategy. The experiment results show that the proposed method significantly outperforms other caching algorithms for estimating the popularity of a piece of content, such as Thompson Sampling, in terms of caching efficiency. © 2023 IEEE.

关键词： Privacy-preserving techniques

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Complementary memtransistors for neuromorphic computing: How, what and why

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Journal of Semiconductors 2024年第6期45卷 64-80页

作者： Qi Chen Yue Zhou Weiwei Xiong Zirui Chen Yasai Wang Xiangshui Miao Yuhui He School of Integrated Circuits Huazhong University of Science and TechnologyWuhan 430074China Department of Electrical and Computer Engineering University of CaliforniaSan DiegoUSA Dipartimento di Elettronica e Informazione and *** Politecnico di MilanoMilanoItaly Department of Applied Physics Hong Kong Polytechnic UniversityHong KongChina

Memtransistors in which the source-drain channel conductance can be nonvolatilely manipulated through the gate signals have emerged as promising components for implementing neuromorphic *** the other side,it is known that the complementary metal-oxide-semiconductor(CMOS)field effect transistors have played the fundamental role in the modern integrated circuit ***,will complementary memtransistors(CMT)also play such a role in the future neuromorphic circuits and chips?In this review,various types of materials and physical mechanisms for constructing CMT(how)are inspected with their merits and need-to-address challenges *** the unique properties(what)and poten-tial applications of CMT in different learning algorithms/scenarios of spiking neural networks(why)are reviewed,including super-vised rule,reinforcement one,dynamic vision with in-sensor computing,*** exploiting the complementary structure-related novel functions,significant reduction of hardware consuming,enhancement of energy/efficiency ratio and other advan-tages have been gained,illustrating the alluring prospect of design technology co-optimization(DTCO)of CMT towards neuro-morphic computing.

关键词： complementary memtransistor neuromorphic computing reward-modulated spike timing-dependent plasticity remote supervise method in-sensor computing

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