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检索条件"任意字段=13th International Conference on Distributed Computing and Internet Technology, ICDCIT 2017"

共 228 条记录，以下是61-70 订阅

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A High-Speed Cauchy CODEC Algorithm for distributed Storage System 20

A High-Speed Cauchy CODEC Algorithm for Distributed Storage ...

引用

2020 international conference on internet computing for Science and Engineering, ICICSE 2020 and the 13th international conference on Advanced Computer theory and Engineering, ICACTE 2020

作者： Wu, Ruizhen Wang, Lin Wu, Yan Inspur Electronic Information Industry Co. Ltd Xi'an China

ISBN: (纸本)9781450377348

the erasure codes such as Reed-Solomon (RS) code and Cauchy Reed-Solomon (CRS) code have been widely used in distributed storage system. though all the erasure codes are able to help recover the storage data successfully when errors happening, the computation cost of different Cauchy CODEC implementation makes a great impact to the performance of its practical application especially due to its complexity of generating the decoding matrix. this paper introduces a new high-speed Cauchy algorithm to construct an encoding algorithm based on the hardware implementation mechanism of decoding. In comparison to Gauss LU, GS-Cauchy, GS-direct-Cauchy for both decoding matrix generation and CODEC all through, the proposed algorithm requires much less complexities to gain the same performance of CRS. © 2020 ACM.

关键词： Decoding

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Design and Practice of Hybrid Interactive Teaching Platform for Product Design Specialty under the Background of internationalization

Design and Practice of Hybrid Interactive Teaching Platform ...

引用

international conference on Measuring technology and Mechatronics Automation, ICMTMA

作者： Xu Hui Gingko College of Hospitality Management Chengdu China

ISBN: (纸本)9781665438926;9781665446099

In view of the mobile learning environment under the background of internet plus, this paper discusses the interactive teaching reform process by using the hybrid learning theory and taking the product design course under the background of internationalization as an example. We fully apply the idea of hybrid teaching mode to the system design, and use three open source frameworks based on J2EE, Struts2, Hibernate and Spring to realize the development of course production platform. the platform uses the distributed file system MySQL to realize the storage and management of massive teaching resources, and uses the consistent hash algorithm to improve the efficiency of file and data storage and access. Finally, the network learning environment of product design course is constructed by using cloud services. the application effect of e-learning space is investigated and analyzed from two aspects of basic application and learning investment, which verifies the feasibility and effectiveness of hybrid teaching mode.

关键词： Training Cloud computing Companies Production Tools Product design Planning

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Optimal Design Parameters for Tiny-YOLO2 Implementation with Light-Weight Embedded GPGPU Environment 13th

Optimal Design Parameters for Tiny-YOLO2 Implementation with...

引用

13th international conference on Multimedia and Ubiquitous Engineering (MUE) / 14th international conference on Future Information technology (Future Tech)

作者： Yu, Yechan Kim, Daewoo Ha, Jinjoo Kim, Hojin Yi, Kang Handong Global Univ Sch Comp Sci & Elect Engn Pohang Gyungbuk South Korea

ISBN: (纸本)9789813292444;9789813292437

the aim of this paper is to find the optimal design for tiny YOLO2 in an embedded system environment. Our focus is to rebuild the given YOLO2 code and to find the optimal design parameters in order to maximize the speed using the light-weight GPGPU in a target embedded environment. To maximize the YOLO2 performance we used OpenCL framework while utilizing the embedded GPGPU and tried various aspects of OpenCL design parameters such work item, work group, and resulting in reducing the global memory access overhead and maximizing computing load balancing between computing units under constraints including local memory resources and computing resources. Our experimental results show that the overall performance enhancement is 18.2 times compared to the naive implementation.

关键词： High-Performance computing OpenCL YOLO Embedded System Parallel/distributed System

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ACM international conference Proceeding Series

ACM International Conference Proceeding Series

引用

2020 international conference on internet computing for Science and Engineering, ICICSE 2020 and the 13th international conference on Advanced Computer theory and Engineering, ICACTE 2020

ISBN: (纸本)9781450377348

the proceedings contain 20 papers. the topics discussed include: practical control flow integrity using multi-variant execution;a high-speed Cauchy CODEC algorithm for distributed storage system;network intrusion detection using wrapper-based decision tree for feature selection;software remodularization using tabu search;design and implementation of medical process visualization CDSS oriented to NCCN guidelines;research on recommendation strategies integrating emotional tendency and user influences;grey wolf optimizer with multi-strategy optimization and its application on TSP;toward U-net-based GANs for diverse facial image synthesis from sketch;and analysis of convolutional neural network for lifelong learning on Indonesian sentiment analysis.

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Analysis of Nantong Public Culture Supply Mode Innovation Based on "internet +" Platform 1

Analysis of Nantong Public Culture Supply Mode Innovation Ba...

引用

1st international conference on Computer Applied Science and Information technology, ICCASIT 2020

作者： Shen, Xiaohu Deng, Yangyang School of Commercial Nantong Institute of Technology Nan Tong China

Currently, public cultural services are mainly provided by the government, there is a contradiction between supply and demand. Use the "internet +" innovation-driven thinking to establish a demand-centric innovation mechanism for public cultural supply, rely on big data, cloud computing, information technology, cloud sharing and mobile internet to build a public cultural internet service platform, forming "internet + "Public cultural services" resource information sharing model, innovate the supply of public culture, enrich the content of public cultural services, encourage social forces to participate in cultural construction, at the same time focus on the integration of science and technology, effectively meet the public cultural needs, solve the contradiction between supply and demand in public cultural services. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Economics

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An optimization method for resource allocation in fog computing 13

An optimization method for resource allocation in fog comput...

引用

2020 IEEE Congress on Cybermatics: 13th IEEE international conferences on internet of things, ithings 2020, 16th IEEE international conference on Green computing and Communications, GreenCom 2020, 13th IEEE international conference on Cyber, Physical and Social computing, CPSCom 2020 and 6th IEEE international conference on Smart Data, SmartData 2020

作者： Yin, Chao Li, Tongfang Qu, Xiaoping Yuan, Sihao School of Information Science and Technology Jiujiang University Jiujiang332005 China

ISBN: (纸本)9781728176475

With the rapid development of the network, a huge amount of data will be generated. Existing technologies usually use cloud computing to process data. However, when all the data of users need to be transferred to the cloud for processing, it will cause long transmission delay due to the distance between users and cloud computing data center. Fog computing connects network edge devices downward and cloud data center upward, which greatly shortens the transmission distance of user data. Fog computing is an effective way to solve the problems of high delay, bandwidth bottleneck and security. In this paper, we have developed an optimization method, which establish an optimization problem with minimum average task delay as optimization objective and various system resources. By variable substitution, the nonconvex optimization problem is equivalent to a new optimization problem whose objective is nonconvex and all constraints are convex. In order to solve the global optimal solution of the nonconvex optimization problem, a new lower bound is designed by relaxing the objective to a lower bound quadratic function. We have evaluated our system by simulation test. the results verify the effectiveness of the optimization method. © 2020 IEEE.

关键词： Resource allocation

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Blockchain-Based Vehicular Collaborative computing 13

Blockchain-Based Vehicular Collaborative Computing

引用

13th EAI international conference on Mobile Multimedia Communications, Mobimedia 2020

作者： Zheng, Qibin Zhang, Rongqing Zhao, Shengjie School of Software Engineering Tongji University Shanghai201804 China Shandong Provincial Key Laboratory of Wireless Communication Technologies Shandong University China

ISBN: (纸本)9781631902710

Collaborative computing among vehicles on the road has been regarded as a promising application for connected and intelligent vehicles as new computing and communication technologies emerge. Instead of using cloud computing services, a vehicle can complete computing-intensive tasks by making use of neighboring vehicles' idle computing resources and meanwhile, pay for this service to the assisting vehicles to increase their incentive to participate in such collaborative computing tasks. In collaborative computing among vehicles, how to balance the profits of both sides need to be investigated. What's more, the reliability of transactions is also a concerning problem. In this paper, we first introduce a collaborative computing scenario and propose a two-layer blockchain architecture to enhance the reliability of transactions. then, we propose a coalition formation game-based collaborative computing algorithm to efficiently achieve effective computing coalition formation in a distributed manner. Simulation results show that the proposed algorithm can significantly improve the vehicles' utilities as well as the task performance. Copyright © 2020 EAI.

关键词： Vehicles

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Data Scheduling and Resource Optimization for Fog computing Architecture in Industrial IoT 15th

Data Scheduling and Resource Optimization for Fog Computing ...

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15th international conference on distributed computing and internet technology (icdcit)

作者： Wang, Wei Wu, Guanyu Guo, Zhe Qian, Liang Ding, Lianghui Yang, Feng Shanghai Jiao Tong Univ Dept Elect Engn Shanghai Peoples R China Shanghai Microwave Res Inst Shanghai Peoples R China CETC Key Lab Data Link Technol Shanghai Peoples R China

ISBN: (纸本)9783030053666;9783030053659

In the actual industrial environment, how the system processes and analyzes big data stably in real time is the main challenge of industrial internet of things (IIoT) currently. Although fog computing, as a significant extension of cloud computing, provides a distributed solution to real-time data processing in the industrial environment, it is an unavoidable problem that non-negligible network latency and fluctuations in the industrial network and limited computing power of fog nodes make it difficult to process big data timely and stably. We integrate the decentralized resources of fog nodes to form a cluster which can deliver sufficient processing power to deal with a complicated computational task. And then we propose an optimal data scheduling policy with multiple communication channels to minimize real-time processing delay and increase stability of the system. A series of experiments are designed to evaluate the behaviors with three different scheduling policies. Simulation results show that over 15% performance gain, in the system adopted optimal data scheduling policy, can be achieved according to different working scenarios, in which network communication conditions and processing power make the decisive contributions. Meanwhile, the fluctuating range of system delay curve is lower with the fluctuating of the network than the other two, which means the system has a better stability.

关键词： Fog computing IIoT Real-time Stability Optimal scheduling

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Practical Control Flow Integrity using Multi-Variant execution 20

Practical Control Flow Integrity using Multi-Variant executi...

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2020 international conference on internet computing for Science and Engineering, ICICSE 2020 and the 13th international conference on Advanced Computer theory and Engineering, ICACTE 2020

作者： Yao, Dong Zhang, Zheng Zhang, Gaofei State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781450377348

the popularity of computers and networks brings many conveniences to our daily life but also brings a variety of security threats. the proliferation of attacks and the rapid spread of viruses make security researchers gradually shift their perspective from passive defense to active defense. Among many active defenses, the technique of software multi-variant execution (MVX) framework has been widely concerned. It can detect and defend most known or even 0-day attacks without depending on the feature of specific threats. However, there is a big performance bottleneck in this technique. Control flow integrity (CFI) is another ideal security solution, but it is not widely used in practice because of performance loss and compatibility problems. In this paper, we propose a multi-variant execution framework called MVX-CFI. MVX-CFI improves execution efficiency without losing its original security. MVX-CFI is a dynamic and transparent CFI implementation based on the MVX framework. It can effectively capture the control flow of the target software and find illegal path transfer caused by malicious acts such as attacks. MVX-CFI extends the general MVX with a feedback assisted-detection module, which reduces a lot of repetitive voting work of traditional MVX and improves the performance. It also provides a probability to detect preset back door in a software. © 2020 ACM.

关键词： Network security

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Research on CNN Parallel computing and Learning Architecture Based on Real-Time Streaming Architecture 15th

Research on CNN Parallel Computing and Learning Architecture...

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15th international conference on distributed computing and internet technology (icdcit)

作者： Zhu, Yuting Qian, Liang Wang, Chuyan Ding, Lianghui Yang, Feng Wang, Hao Shanghai Jiao Tong Univ Sch Elect Informat & Elect Engn Shanghai Peoples R China Air Force Mil Representat Off Shanghai Nanjing Nanjing Peoples R China

ISBN: (纸本)9783030053666;9783030053659

Convolutional neural network (CNN) is a deep feed-forward artificial neural network, which is widely used in image recognition. However, this mode highlights the problems that the training time is too long and memory is insufficient. Traditional acceleration methods are mainly limited to optimizing for an algorithm. In this paper, we propose a method, namely CNN-S, to improve training efficiency and cost based on Storm and is suitable for every algorithm. this model divides data into several sub sets and processes data on several machine in parallel flexibly. the experimental results show that in the case of achieving a recognition accuracy rate of 95%, the training time of single serial model is around 913 s, and in CNN-S model only needs 248 s. the acceleration ratio can reach 3.681. this shows that the CNN-S parallel model has better performance than single serial mode on training efficiency and cost of system resource.

关键词： CNN Parallel computing Apache storm Real time

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