2020 21st Asia-Pacific Network Operations and Management Symposium (APNOMS)最新文献_第8页

Design and Performance Evaluation of Hexagonal Topology Networks with Novel Routing Algorithms 基于新型路由算法的六边形拓扑网络设计与性能评估

2020 21st Asia-Pacific Network Operations and Management Symposium (APNOMS) Pub Date : 2020-09-01 DOI: 10.23919/APNOMS50412.2020.9236992

Yuh-Jiuh Cheng, Bor-Tauo Chen, Wen-Lin Cheng

引用次数: 1

Prequalification of VDSL2 copper customers for G.fast services with artificial intelligence technology VDSL2铜客户资格预审G.fast人工智能技术服务

2020 21st Asia-Pacific Network Operations and Management Symposium (APNOMS) Pub Date : 2020-09-01 DOI: 10.23919/APNOMS50412.2020.9237059

Pang-Chen Liu, Shun-Kai Yang, Lung-Chin Huang, Huai-En Tseng, Fei-Hua Kuo, Tai-Chueh Shih

引用次数: 0

Reliability Evaluation and Optimization Method in Power Communication Network Based on Environmental Factors and Controlled Hybrid Stochastic Petri Net 基于环境因素和可控混合随机Petri网的电力通信网络可靠性评估与优化方法

2020 21st Asia-Pacific Network Operations and Management Symposium (APNOMS) Pub Date : 2020-09-01 DOI: 10.23919/APNOMS50412.2020.9236955

Huilin Liu, Yucheng Ma, Xushan Chen, Meng Zhou, Shiyou Chen

{"title":"Reliability Evaluation and Optimization Method in Power Communication Network Based on Environmental Factors and Controlled Hybrid Stochastic Petri Net","authors":"Huilin Liu, Yucheng Ma, Xushan Chen, Meng Zhou, Shiyou Chen","doi":"10.23919/APNOMS50412.2020.9236955","DOIUrl":"https://doi.org/10.23919/APNOMS50412.2020.9236955","url":null,"abstract":"The reliability of the power communication network is important to the stable operation of the power grid. Existing studies on the reliability evaluation of power communication networks rarely consider the factors of environmental changes. In fact, changes in the working environment of power service routing will affect the normal operation of the network. This paper studies the reliability evaluation method of power communication network based on environmental factors. The normal cloud model method is used to model the multiple environmental factors in the power communication network, and a controlled hybrid stochastic petri network is used to model and analyze the power transmission system with backup route. In simulation experiments, we compare our algorithm with the contrast algorithm that not considering the impact of environmental factors. The results show that our algorithm can well reflect the impact of changes in environmental factors on the reliability of the system, and more in line with the actual reliability changes of the power service transmission system.","PeriodicalId":122940,"journal":{"name":"2020 21st Asia-Pacific Network Operations and Management Symposium (APNOMS)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121163130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimized Quantization for Convolutional Deep Neural Networks in Federated Learning 联邦学习中卷积深度神经网络的优化量化

2020 21st Asia-Pacific Network Operations and Management Symposium (APNOMS) Pub Date : 2020-09-01 DOI: 10.23919/APNOMS50412.2020.9236949

You Jun Kim, C. Hong

{"title":"Optimized Quantization for Convolutional Deep Neural Networks in Federated Learning","authors":"You Jun Kim, C. Hong","doi":"10.23919/APNOMS50412.2020.9236949","DOIUrl":"https://doi.org/10.23919/APNOMS50412.2020.9236949","url":null,"abstract":"Federated learning is a distributed learning method that trains a deep network on user devices without collecting data from central server. It is useful when the central server can't collect data. However, the absence of data on central server means that deep network compression using data is not possible. Deep network compression is very important because it enables inference even on device with low capacity. In this paper, we proposed a new quantization method that significantly reduces FPROPS(floating-point operations per second) in deep networks without leaking user data in federated learning. Quantization parameters are trained by general learning loss, and updated simultaneously with weight. We call this method as OQFL(Optimized Quantization in Federated Learning). OQFL is a method of learning deep networks and quantization while maintaining security in a distributed network environment including edge computing. We introduce the OQFL method and simulate it in various Convolutional deep neural networks. We shows that OQFL is possible in most representative convolutional deep neural network. Surprisingly, OQFL(4bits) can preserve the accuracy of conventional federated learning(32bits) in test dataset.","PeriodicalId":122940,"journal":{"name":"2020 21st Asia-Pacific Network Operations and Management Symposium (APNOMS)","volume":"181 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116143779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

An Evaluation of Network Service Monitoring Method Using User Traffic Information 基于用户流量信息的网络服务监控方法评价

2020 21st Asia-Pacific Network Operations and Management Symposium (APNOMS) Pub Date : 2020-09-01 DOI: 10.23919/APNOMS50412.2020.9236950

Kei Takeshita, Y. Soejima

引用次数: 1

Smart Self-Checkout Carts Based on Deep Learning for Shopping Activity Recognition 基于深度学习的购物活动识别智能自助结账车

2020 21st Asia-Pacific Network Operations and Management Symposium (APNOMS) Pub Date : 2020-09-01 DOI: 10.23919/APNOMS50412.2020.9237053

Hong-Chuan Chi, M. A. Sarwar, Yousef-Awwad Daraghmi, Kuan Liu, Tsì-Uí İk, Yih-Lang Li

{"title":"Smart Self-Checkout Carts Based on Deep Learning for Shopping Activity Recognition","authors":"Hong-Chuan Chi, M. A. Sarwar, Yousef-Awwad Daraghmi, Kuan Liu, Tsì-Uí İk, Yih-Lang Li","doi":"10.23919/APNOMS50412.2020.9237053","DOIUrl":"https://doi.org/10.23919/APNOMS50412.2020.9237053","url":null,"abstract":"Fast and reliable communication plays a major role in the success of smart shopping applications. In a “Just Walk Out” shopping scenario, a video camera is installed on the cart to monitor shopping activities and transmit images to the cloud for processing so that items in the cart can be tracked and checked out. This paper proposes a prototype of a smart shopping cart based on image-based action recognition. Firstly, deep learning networks such as Faster R-CNN, YOLOv2, and YOLOv2-Tiny are utilized to analyze the content of each video frame. Frames are classified into three classes: No Hand, Empty Hand, and Holding Items. The classification accuracy based on Faster R-CNN, YOLOv2, or YOLOv2-Tiny is between 93.0% and 90.3%, and the processing speed of the three networks can be up to 5 fps, 39 fps, and 50 fps, respectively. Secondly, based on the sequence of frame classes, the timeline is divided into No Hand intervals, Empty Hand intervals, and Holding Items intervals. The accuracy of action recognition is 96%, and the time error is 0.119s on average. Finally, we categorize the events into four cases: No Change, placing, Removing, and Swapping. Even including the correctness of the item recognition, the accuracy of shopping event detection is 97.9%, which is higher than the minimal requirement to deploy such a system in a smart shopping environment. A demo of the system and a link to download the data set used in the paper are in Smart Shopping Cart Prototype or found at this URL: https://hackmd.io/abEiC83rQoqxz7zpL4Kh2w.","PeriodicalId":122940,"journal":{"name":"2020 21st Asia-Pacific Network Operations and Management Symposium (APNOMS)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134316949","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9

A Measurement Study on Evaluating Container Network Performance for Edge Computing 基于边缘计算的容器网络性能评估方法研究

2020 21st Asia-Pacific Network Operations and Management Symposium (APNOMS) Pub Date : 2020-09-01 DOI: 10.23919/APNOMS50412.2020.9236997

Jun-Sup Yoon, Jian Li, Sangho Shin

引用次数: 3

Effect of Packet Loss and Delay on V2X Data Fusion 丢包和时延对V2X数据融合的影响

2020 21st Asia-Pacific Network Operations and Management Symposium (APNOMS) Pub Date : 2020-09-01 DOI: 10.23919/APNOMS50412.2020.9237017

Tzu-Kuang Lee, Jen-Jee Chen, Y. Tseng, Cheng-Kuan Lin

引用次数: 4

A Study on Automation of Network Maintenance in Telecom Carriers for Zero-Touch Operations 电信运营商零接触运营网络维护自动化研究

2020 21st Asia-Pacific Network Operations and Management Symposium (APNOMS) Pub Date : 2020-09-01 DOI: 10.23919/APNOMS50412.2020.9236983

Aiko Oi, Ryosuke Sato, Yuichi Suto, Kosuke Sakata, Motomu Nakajima, Tsuyoshi Furukawa

{"title":"A Study on Automation of Network Maintenance in Telecom Carriers for Zero-Touch Operations","authors":"Aiko Oi, Ryosuke Sato, Yuichi Suto, Kosuke Sakata, Motomu Nakajima, Tsuyoshi Furukawa","doi":"10.23919/APNOMS50412.2020.9236983","DOIUrl":"https://doi.org/10.23919/APNOMS50412.2020.9236983","url":null,"abstract":"In recent years, there are many work efficiency efforts in particular automation of business processes in various industry. The same trend applies to the network operations of telecommunication carriers; however, although automation of service fulfillment, such as developing network services, is progressing, automation of service assurance such as responding to network failure has not progressed. Currently, network maintenance personnel have independently developed tools for automation of network maintenance (such as troubleshooting) process partially and they are manually performing maintenance tasks by coordinating multiple groups of tools. However, in view of the future decrease in the working population, work efficiency must be further improved. Following this situation, this article focuses on further automation of network maintenance process, by developing technologies to orchestrate existing automation tools. In this paper, handling network failures among network maintenance work is targeted, the challenges and the requirements for expansion in the range of automation is discussed, after discussing current automation of network maintenance at telecom carriers in the real world. After that an implementation method that satisfies these requirements using our orchestrator and OSS products is proposed and evaluated. By defining a workflow of network maintenance that makes each process reusable, it becomes easy to create new workflow and update the one, and furthermore it was found that by reviewing how to code the workflow, it was possible to significantly improve processing performance.","PeriodicalId":122940,"journal":{"name":"2020 21st Asia-Pacific Network Operations and Management Symposium (APNOMS)","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127869001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Deployment of Facial Recognition Models at the Edge: A Feasibility Study 边缘面部识别模型的部署:可行性研究

2020 21st Asia-Pacific Network Operations and Management Symposium (APNOMS) Pub Date : 2020-09-01 DOI: 10.23919/APNOMS50412.2020.9236972

Xihao Zhou, S. Keoh

引用次数: 1