2019 IEEE 9th Annual Computing and Communication Workshop and Conference (CCWC)最新文献

Adapting RGB Pose Estimation to New Domains 将RGB姿态估计应用于新域

2019 IEEE 9th Annual Computing and Communication Workshop and Conference (CCWC) Pub Date : 2019-06-14 DOI: 10.1109/CCWC.2019.8666594

Gururaj Mulay, B. Draper, J. Beveridge

{"title":"Adapting RGB Pose Estimation to New Domains","authors":"Gururaj Mulay, B. Draper, J. Beveridge","doi":"10.1109/CCWC.2019.8666594","DOIUrl":"https://doi.org/10.1109/CCWC.2019.8666594","url":null,"abstract":"Many multi-modal human computer interaction (HCI) systems interact with users in real-time by estimating the user’s pose. Generally, they estimate human poses using depth sensors such as the Microsoft Kinect. For multi-modal HCI interfaces to gain traction in the real world, however, it would be better for pose estimation to be based on data from RGB cameras, which are more common and less expensive than depth sensors. This has motivated research into pose estimation from RGB images. Convolutional Neural Networks (CNNs) represent the state-of-the-art in this literature, for example [1], [2], [9], [13], [14], and [15]. These systems estimate 2D human poses from RGB images. A problem with current CNN-based pose estimators is that they require large amounts of labeled data for training. If the goal is to train an RGB pose estimator for a new domain, the cost of collecting and more importantly labeling data can be prohibitive. A common solution is to train on publicly available pose data sets, but then the trained system is not tailored to the domain. We propose using RGB+D sensors to collect domain-specific data in the lab, and then training the RGB pose estimator using skeletons automatically extracted from the RGB+D data. This paper presents a case study of adapting the RMPE pose estimation network [2] to the domain of the DARPA Communicating with Computers (CWC) program [3], as represented by the EGGNOG data set [8]. We chose RMPE because it predicts both joint locations and Part Affinity Fields (PAFs) in real-time. Our adaptation of RMPE trained on automatically-labeled data outperforms the original RMPE on the EGGNOG data set.","PeriodicalId":132812,"journal":{"name":"2019 IEEE 9th Annual Computing and Communication Workshop and Conference (CCWC)","volume":"426 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132062238","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: 1

Introducing Edge Controlling to Software Defined Networking to Reduce Processing Time 在软件定义网络中引入边缘控制以减少处理时间

2019 IEEE 9th Annual Computing and Communication Workshop and Conference (CCWC) Pub Date : 2019-03-14 DOI: 10.1109/CCWC.2019.8666504

A. Almohaimeed, A. Asaduzzaman

{"title":"Introducing Edge Controlling to Software Defined Networking to Reduce Processing Time","authors":"A. Almohaimeed, A. Asaduzzaman","doi":"10.1109/CCWC.2019.8666504","DOIUrl":"https://doi.org/10.1109/CCWC.2019.8666504","url":null,"abstract":"Edge computing enables computational services to be performed at the edge of a network on behalf of the main cloud services. The rationale of edge computing is applicable to any centralized system where the service should be provided at the proximity of the end-systems. Software-Defined Networking (SDN) is an evolving network model that runs a single-centralized controller to handle all network functions which may lead to limited performance capabilities with the recent growth of data communication. In this paper, we introduce a novel SDN Edge Controlling model that overcomes the performance-limitations by leveraging edge computing capabilities. It aims to bring the computing and storage resources close to network devices so that the load on the main SDN controller can be eased, and the delay between the forward plane and the control plane is minimized. We develop a simulation program to assess the effectiveness of our model. Experimental results show that the bandwidth usage is reduced by about 45% and the total processing time of the main controller is reduced by almost 62% for 10,000 requests. Therefore, the proposed model handles a higher network load and maintains lower latency when compared with a traditional SDN.","PeriodicalId":132812,"journal":{"name":"2019 IEEE 9th Annual Computing and Communication Workshop and Conference (CCWC)","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116149926","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

Shared Entry Logger to Eliminate Duplicate Requests to SDN Controller 共享条目记录器消除对SDN控制器的重复请求

2019 IEEE 9th Annual Computing and Communication Workshop and Conference (CCWC) Pub Date : 2019-03-14 DOI: 10.1109/CCWC.2019.8666595

A. Asaduzzaman, A. Almohaimeed, K. K. Chidella

引用次数: 5

A Study on Flat and Hierarchical System Deployment for Edge Computing 面向边缘计算的扁平分层系统部署研究

2019 IEEE 9th Annual Computing and Communication Workshop and Conference (CCWC) Pub Date : 2019-03-12 DOI: 10.1109/CCWC.2019.8666572

Dawei Li, Boxiang Dong, E. Wang, Michelle Zhu

{"title":"A Study on Flat and Hierarchical System Deployment for Edge Computing","authors":"Dawei Li, Boxiang Dong, E. Wang, Michelle Zhu","doi":"10.1109/CCWC.2019.8666572","DOIUrl":"https://doi.org/10.1109/CCWC.2019.8666572","url":null,"abstract":"In this paper, we consider the server allocation problem for edge computing system deployment where each edge cloud is modeled as an M/M/c queue. Our goal is to minimize the overall average system response time of application requests generated by all mobile devices/users. We consider two approaches for edge cloud deployment: the flat deployment, where all edge clouds are co-located with the base stations, and the hierarchical deployment, where edge clouds can be co-located with other system components besides the base stations. In flat deployment, we demonstrate that the allocation of edge cloud servers should be balanced across all the base stations, if the application request arrival rates at the base stations are equal to each other; if the application request arrival rates are not the same, we propose a Largest Weighted Reduction Time First (LWRTF) algorithm to assign servers to edge clouds. Numerical comparisons of the proposed algorithm against several other reasonably designed heuristics verify that algorithm LWRTF has very good performances in terms of minimizing the average system response time. We also conduct preliminary study on hierarchical deployment for edge computing and show that the hierarchical deployment approach has great potentials in minimizing the overall average system response time.","PeriodicalId":132812,"journal":{"name":"2019 IEEE 9th Annual Computing and Communication Workshop and Conference (CCWC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133131778","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

Self Error Detection and Correction for Noisy Labels Based on Error Correcting Output Code in Convolutional Neural Networks 基于纠错输出码的卷积神经网络噪声标签自检与纠错

2019 IEEE 9th Annual Computing and Communication Workshop and Conference (CCWC) Pub Date : 2019-01-01 DOI: 10.1109/CCWC.2019.8666460

Yang Jiao, S. Latifi, Mei Yang

引用次数: 2

Parallel Multi-View Graph Matrix Completion for Large Input Matrix 大输入矩阵的并行多视图图矩阵补全

2019 IEEE 9th Annual Computing and Communication Workshop and Conference (CCWC) Pub Date : 2019-01-01 DOI: 10.1109/CCWC.2019.8666532

A. Koohi, H. Homayoun

引用次数: 0

On the Uniqueness of Stationary Solutions of an Asynchronous Parallel and Distributed Algorithm for Diffusion Equations 扩散方程异步并行分布算法平稳解的唯一性

2019 IEEE 9th Annual Computing and Communication Workshop and Conference (CCWC) Pub Date : 2019-01-01 DOI: 10.1109/CCWC.2019.8666522

Kooktae Lee, R. Bhattacharya

{"title":"On the Uniqueness of Stationary Solutions of an Asynchronous Parallel and Distributed Algorithm for Diffusion Equations","authors":"Kooktae Lee, R. Bhattacharya","doi":"10.1109/CCWC.2019.8666522","DOIUrl":"https://doi.org/10.1109/CCWC.2019.8666522","url":null,"abstract":"In this paper, we study the uniqueness of stationary solutions of an asynchronous parallel and distributed algorithm for diffusion equations. In the literature, it has been reported that asynchronous stationary solutions can be affected by randomness of asynchrony, leading to variations in solutions. The uniqueness in this context implies that the stationary solutions obtained by asynchronous communications between parallel and distributed computing devices are the same as the synchronous one, regardless of asynchrony. In some applications, inexact stationary solutions as an outcome of asynchrony may result in serious consequences. Therefore, it is critical to guarantee the existence of the unique stationary solution for a given problem. As a case study, we analyze the uniqueness of stationary solutions for diffusion equations with a fixed boundary condition, by employing the dynamical system framework and nonnegative matrix theory. The numerical results are presented to validate the proposed method with performance analysis of the asynchronous parallel and distributed algorithm.","PeriodicalId":132812,"journal":{"name":"2019 IEEE 9th Annual Computing and Communication Workshop and Conference (CCWC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129532743","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: 1

Dedicated Backup Units to Alleviate Overload on SDN Controllers 专用备份单元减轻SDN控制器过载

2019 IEEE 9th Annual Computing and Communication Workshop and Conference (CCWC) Pub Date : 2019-01-01 DOI: 10.1109/CCWC.2019.8666452

A. Almohaimeed, A. Asaduzzaman

引用次数: 4

Gender Classification Using Machine Learning with Multi-Feature Method 基于多特征方法的机器学习性别分类

2019 IEEE 9th Annual Computing and Communication Workshop and Conference (CCWC) Pub Date : 2019-01-01 DOI: 10.1109/CCWC.2019.8666601

Sandeep Kumar, Sukhwinder Singh, J. Kumar

引用次数: 33

Noise Performance of Orthogonal RF Beamforming for THz Radio Communications 太赫兹无线电通信中正交射频波束形成的噪声性能

2019 IEEE 9th Annual Computing and Communication Workshop and Conference (CCWC) Pub Date : 2019-01-01 DOI: 10.1109/CCWC.2019.8666546

K. K. Tiwari, E. Grass, R. Kraemer

引用次数: 4