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arXiv 2020年

作者： Basodi, Sunitha Ji, Chunyan Zhang, Haiping Pan, Yi Department of Computer Science Georgia State University AtlantaGA30302 United States Center for High Performance Computing Joint Engineering Research Center for Health Big Data Intelligent Analysis Technology Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences ShenzhenGuangdong518 055 China

Improving performance of deep learning models and reducing their training times are ongoing challenges in deep neural networks. There are several approaches proposed to address these challenges one of which is to increase the depth of the neural networks. Such deeper networks not only increase training times, but also suffer from vanishing gradients problem while training. In this work, we propose gradient amplification approach for training deep learning models to prevent vanishing gradients and also develop a training strategy to enable or disable gradient amplification method across several epochs with different learning rates. We perform experiments on VGG-19 and resnet (Resnet-18 and Resnet-34) models, and study the impact of amplification parameters on these models in detail. Our proposed approach improves performance of these deep learning models even at higher learning rates, thereby allowing these models to achieve higher performance with reduced training time. Copyright © 2020, The Authors. All rights reserved.

关键词： Backpropagation

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The DUDFTO Attack: Towards Down-to-UP Timeout Probing and Dynamically Flow Table Overflowing in SDN

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IEEE Transactions on Network and Service Management 2025年

作者： Li, Jiasong Cui, Yunhe Chen, Yi Shen, Guowei Guo, Chun Qian, Qing Guizhou University State Key Laboratory of Public Big Data Engineering Research Center of Text Computing and Cognitive Intelligence Ministry of Education College of Computer Science and Technology Guizhou Provincial Characteristic Key Laboratory of Software Engineering and Information Security Guiyang550000 China Guizhou University of Finance and Economics School of Information Guiyang550000 China

As a new network structure, the decoupling of the control plane and forwarding plane makes Software-Defined Networking (SDN) widely used in large-scale network scenarios. However, the decoupling network architecture also brings new vulnerabilities. The flow table overflow attack is an attack strategy that can overwhelm SDN switches. Nevertheless, the existing flow table overflow attacks may fail in probing timeouts and match fields of flow entries, due to link failure, measurement of the round-trip time (RTT) of different packets, interference of hard-timeout and idle-timeout. Meanwhile, the stealthiness of the existing attacks may also reduce, as these attacks use fixed attack rate. To improve the timeout probing accuracy and the stealthiness of attack, a new flow table overflow attack strategy, DUDFTO, is proposed to accurately probe timeout settings and match fields, then stealthily overflow SDN flow tables. Firstly, it probes the match fields by measuring the one-sided transmission delay of the packets. After that, DUDFTO designs a down-to-up feedback-based timeout probing algorithm to eliminate the issues caused by high RTT, link failure, interference between hard-timeout and idle-timeout. Then, DUDFTO designs a dynamic attack packets sending algorithm to improve its stealthiness. Finally, DUDFTO probes the flow table state to stop sending new attack packets. The evaluation results demonstrate that DUDFTO outperforms the existing attacks in terms of match fields probing ability, timeout probing relative error, number of packet_in and flow_mod messages generated by the attack, rate distribution of packet_in and flow_mod messages generated during the attack, and number of detected attack packets. © 2004-2012 IEEE.

关键词： flow table overflow attack information probing SDN switchs

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Accountable privacy-enhanced multi-authority attribute-based authentication scheme for cloud services*✰

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Computer Communications 2025年

作者： Xin Liu Hao Wang Bo Zhang Bin Zhang School of Information Engineering Shandong Youth University of Political Science Jinan 250103 China New Technology Research and Development Center of Intelligent Information Controlling in Universities of Shandong Jinan 250103 China Smart Healthcare Big Data Engineering and Ubiquitous Computing Characteristic Laboratory in Universities of Shandong Jinan 250103 China School of Information Science and Engineering Shandong Normal University Jinan 250358 China School of Information Science and Engineering University of Jinan Jinan 250022 China

Current attribute-based authentication (ABA) schemes have three major drawbacks: first, the single attribute authority (AA) becomes the system bottleneck, i.e., if the AA is corrupted, the entire system will stop working; second, user privacy is not completely secured; and third, malicious users may exploit their anonymity. To overcome these defects, we improved a previously established privacy-preserving decentralized ciphertext policy attribute-based encryption (PPD-CP-ABE) scheme, obtaining a PPD-CP-ABE with verifiable outsourced decryption (PPD-CP-ABE-VOD). This improved scheme uses outsourced decryption, secure two-party computation protocol, and zero-knowledge proofs. We transformed the PPD-CP-ABE-VOD scheme into a new privacy-enhanced multi-authority ABA scheme using an identity tracing mechanism based on linear encryption. This new scheme has the following advantages over similar schemes. First, it introduces multiple AAs and does not require users to trust AA fully. Second, it protects users’ attributes, global identifiers, and access behavior, thus strengthening user privacy protection. Finally, it balances user privacy protection and user accountability. Theoretical and experimental analyses have shown that the new scheme is comparable to recently proposed ABA systems in terms of performance in the key generation and authentication phases, despite appending multiple security properties.

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Nonreciprocal coherent coupling of nanomagnets by exchange spin waves

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Nano research 2021年第7期14卷 2133-2138页

作者： Hanchen Wang Jilei Chen Tao Yu Chuanpu Liu Chenyang Guo Song Liu Ka Shen Hao Jia Tao Liu Jianyu Zhang Marco A.Cabero Z Qiuming Song Sa Tu Mingzhong Wu Xiufeng Han Ke Xia Dapeng Yu Gerrit E.W.Bauer Haiming Yu Fert Beijing Institute School of Integrated Circuit Science and EngineeringBeijing Advanced Innovation Center for Big Data and Brain ComputingBeihang UniversityBeijing 100191China Max Planck Institute for the Structure and Dynamics of Matter 22761 HamburgGermany Beijing National Laboratory for Condensed Matter Physics Institute of PhysicsUniversity of Chinese Academy of SciencesChinese Academy of SciencesBeijing 100190China Shenzhen Institute for Quantum Science and Engineering(SIQSE) and Department of PhysicsSouthern University of Science and Technology(SUSTech)Shenzhen 518055China Department of Physics Beijing Normal UniversityBeijing 100875China Department of Physics Colorado State UniversityFort CollinsColorado 80523USA Kavli Institute of Nanoscience Delft University of Technology2628 CJ DelftThe Netherlands Institute for Materials Research WPI-AIMR and CSNRTohoku UniversitySendai 980-8577Japan Zernike Institute for Advanced Materials University of GroningenGroningenNijenborgh 49747 AG GroningenThe Netherlands

Nanomagnets are widely used to store information in non-volatile spintronic *** waves can transfer information with low-power consumption as their propagations are independent of charge ***,to dynamically couple two distant nanomagnets via spin waves remains a major challenge for *** we experimentally demonstrate coherent coupling of two distant Co nanowires by fast propagating spin waves in an yttrium iron garnet thin film with sub-50 nm *** in two nanomagnets are unidirectionally phase-locked with phase shifts controlled by magnon spin torque and spin-wave *** coupled system is finally formulated by an analytical theory in terms of an effective non-Hermitian *** results are attractive for analog neuromorphic computing that requires unidirectional information transmission.

关键词： spintronics nanomagnets spin waves coherent coupling nonreciprocity

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SCDetector: Software Functional Clone Detection Based on Semantic Tokens Analysis

SCDetector: Software Functional Clone Detection Based on Sem...

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IEEE International Conference on Automated Software Engineering (ASE)

作者： Yueming Wu Deqing Zou Shihan Dou Siru Yang Wei Yang Feng Cheng Hong Liang Hai Jin National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Hubei Engineering Research Center on Big Data Security HUST Wuhan China Shenzhen HUST Research Institute Shenzhen China School of Cyber Science and Engineering HUST Wuhan China School of Computer Science and Technology HUST Wuhan China University of Texas at Dallas United States

ISBN: (数字)9781450367684

ISBN: (纸本)9781728172811

Code clone detection is to find out code fragments with similar functionalities, which has been more and more important in software engineering. Many approaches have been proposed to detect code clones, in which token-based methods are the most scalable but cannot handle semantic clones because of the lack of consideration of program semantics. To address the issue, researchers conduct program analysis to distill the program semantics into a graph representation and detect clones by matching the graphs. However, such approaches suffer from low scalability since graph matching is typically time-consuming. In this paper, we propose SCDetector to combine the scalability of token-based methods with the accuracy of graph-based methods for software functional clone detection. Given a function source code, we first extract the control flow graph by static analysis. Instead of using traditional heavyweight graph matching, we treat the graph as a social network and apply social-network-centrality analysis to dig out the centrality of each basic block. Then we assign the centrality to each token in a basic block and sum the centrality ofthe same token in different basic blocks. By this, a graph is turned into certain tokens with graph details (i.e., centrality), called semantic tokens. Finally, these semantic tokens are fed into a Siamese architecture neural network to train a code clone detector. We evaluate SCDetector on two large datasets of functionally similar code. Experimental results indicate that our system is superior to four state-of-the-art methods (i.e., SourcererCC, Deckard, RtvNN, and ASTNN) and the time cost of SCDetector is 14 times less than a traditional graph-based method (i.e., CCSharp) on detecting semantic clones.

关键词： Scalability Semantics Cloning Detectors Transforms Static analysis Software engineering

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An extragradient algorithm for fixed point problems and pseudomonotone equilibrium problems

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UPB Scientific Bulletin, Series A: Applied Mathematics and Physics 2020年第4期82卷 89-96页

作者： Yao, Zhangsong Liou, Yeong-Cheng Zhu, Li-Jun School of Information Engineering Nanjing Xiaozhuang University Nanjing211171 China Department of Healthcare Administration and Medical Informatics Research Center of Nonlinear Analysis and Optimization Kaohsiung Medical University Department of Medical Research Kaohsiung Medical University Hospital Kaohsiung807 Taiwan The Key Laboratory of Intelligent Information and Big Data Processing of NingXia Province and Health Big Data Research Institute Advanced Intelligent Perception and Control Technology Innovative Team of NingXia North Minzu University Yinchuan750021 China

Iterative methods for solving fixed point problems and pseudomonotone equilibrium problems have been considered. An extragradient algorithm has been presnted for finding a common element of the fixed points of pseudocontractive operators and the solutions of pseudomonotone equilibrium problems in Hilbert spaces. Weak convergence result of the suggested algorithm is proved. © 2020, Politechnica University of Bucharest. All rights reserved.

关键词： Iterative methods

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Towards Lightweight Serverless computing via Unikernel as a Function

Towards Lightweight Serverless Computing via Unikernel as a ...

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International Workshop on Quality of Service

作者： Bo Tan Haikun Liu Jia Rao Xiaofei Liao Hai Jin Yu Zhang National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab/Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China The University of Texas at Arlington

ISBN: (数字)9781728168876

ISBN: (纸本)9781728168883

Serverless computing, also known as “Function as a Service (FaaS)”, is emerging as an event-driven paradigm of cloud computing. In the FaaS model, applications are programmed in the form of functions that are executed and managed separately. Functions are triggered by cloud users and are provisioned dynamically through containers or virtual machines (VMs). The startup delays of containers or VMs usually lead to rather high latency of response to cloud users. Moreover, the communication between different functions generally relies on virtual net devices or shared memory, and may cause extremely high performance overhead. In this paper, we propose Unikernel-as-a-Function (UaaF), a much more lightweight approach to serverless computing. Applications are abstracted as a combination of different functions, and each function are built as an unikernel in which the function is linked with a specified minimum-sized library operating system (LibOS). UaaF offers extremely low startup latency to execute functions, and an efficient communication model to speed up inter-functions interactions. We exploit an new hardware technique (namely VMFUNC) to invoke functions in other unikernels seamlessly (mostly like inter-process communications), without suffering performance penalty of VM Exits. We implement our proof-of-concept prototype based on KVM and deploy UaaF in three unikernels (MirageOS, IncludeOS, and Solo5). Experimental results show that U aaF can significantly reduce the startup latency and memory usage of serverless cloud applications. Moreover, the VMFUNC-based communication model can also significantly improve the performance of function invocations between different unikernels.

关键词： Cloud computing FAA Libraries Containers Task analysis Computer architecture Virtual machine monitors

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Partitioning large-scale property graph for efficient distributed query processing 21

Partitioning large-scale property graph for efficient distri...

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21st IEEE International Conference on High Performance computing and Communications, 17th IEEE International Conference on Smart City and 5th IEEE International Conference on data Science and Systems, HPCC/SmartCity/DSS 2019

作者： Pang, Haohan Gan, Peng Yuan, Pingpeng Jin, Hai Hua, Qiangsheng National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab. Clusters and Grid Computing Lab. School of Computer Science and Technology Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9781728120584

Recently, many communities have published their domain knowledge in the form of graphs. A significant trend is that the relations between pairs of nodes in the graph have become so complex that these data can be treated as property graphs. Complex properties imply semantic constraints which can distinguish elements of property graph into different semantic-related aspects. If the property graph can be partitioned according to these aspects, cross-partition communication would be reduced when evaluating SPARQL queries, for the reason that a query can often be evaluated in a single aspect. Conventional graph partition methods, however, pay little attention to semantic constraints in property graphs. To solve this problem, we propose a new property graph partition method for query optimization. First, we propose the property semantic reachable path as basic partition element, with which to capture the semantic-related aspects in a property graph. Second, to combine paths into partitions, we develop a space-efficient algorithm which merges vertices rather than entire paths. Extensive experiments over representative property graph data confirm the effectiveness of our semantic awareness approach. The performance of our approach is comparable with leading competitors, in terms of load balance, data redundancy, and network overhead. © 2019 IEEE.

关键词： Semantics

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Finedge: A Dynamic Cost-Efficient Edge Resource Management Platform for NFV Network

Finedge: A Dynamic Cost-Efficient Edge Resource Management P...

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International Workshop on Quality of Service

作者： Miao Li Qixia Zhang Fangming Liu National Engineering Research Center for Big Data Technology and System Key Laboratory of Services Computing Technology and System Ministry of Education School of Computer Science and Technology Huazhong University of Science and Technology China

ISBN: (数字)9781728168876

ISBN: (纸本)9781728168883

With the evolution of network function virtualization (NFV) and edge computing, software-based network functions (NFs) can be deployed on closer-to-end-user edge servers to support a broad range of new services with high bandwidth and low latency. However, due to the resource limitation, strict QoS requirements and real-time flow fluctuations in edge network, existing cloud-based resource management strategy in NFV platforms is inefficient to be applied to the edge. Thus, we propose Finedge, a dynamic, fine-grained and cost-efficient edge resource management platform for NFV network. First, we conduct empirical experiments to find out the effect of NFs' resource allocation and their flow-level characteristics on performance. Then, by jointly considering these factors and QoS requirements (e.g., latency and packet loss rate), Finedge can automatically assign the most suitable CPU core and tune the most cost-efficient CPU quota to each NF. Finedge is also implemented with some key strategies including real-time flow monitoring, elastic resource scaling up and down, and also flexible NF migration among cores. Through extensive evaluations, we validate that Finedge can efficiently handle heterogeneous flows with the lowest CPU quota and the highest SLA satisfaction rate as compared with the default OS scheduler and other state-of-the-art resource management schemes.

关键词： Resource management Noise measurement Packet loss Servers Throughput Quality of service

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Network pharmacology study on anti-depressant mechanism of Shuyu Capsule 3

Network pharmacology study on anti-depressant mechanism of S...

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3rd International Conference on Biological Information and Biomedical Engineering, BIBE 2019

作者： Li, Liting Qiu, Haiyan Liu, Mimi Cai, Yongming Guangdong Pharmaceutical University Guangdong Guangzhou510000 China Guangdong Provincial TCM Precision Medicine Big Data Engineering Technology Research Center Guangdong Guangzhou510000 China Guangdong Univ. Coll. of Prec. Med. Big Data Engineering Research Center Based on Cloud Computing Guangdong Guangzhou510000 China Guangdong Guangzhou510000 China

ISBN: (纸本)9783800750269

Depression is a common emotional mental disorder with high morbidity, recurrence rate and disability rate. The incidence of depression increases year by year, reducing the quality of life of patients and imposing a heavy burden on families and society. The present work adopted a network pharmacology-based approach to provide new insights into the active compounds and therapeutic targets of Shuyu Capsule for the treatment of depression. Ninety-two avtive ingredients of Shuyu Capsule possessing favorable pharmacokinetic profiles and biological activities were selected,interacting 96 depression-related targets to provide potential synergistic therapeutic *** analysis of the constructed networks revealed that these targets such as ESR1, PTGS2, NOS2and SLC6A4 were mainly involved in prolactin signaling pathway, PI3K-Akt signaling pathway,serotonergic synapse and thyroid hormone signaling pathway. © VDE VERLAG GMBH · Berlin · Offenbach.

关键词： Signaling

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