2020 IEEE International Conference on Fog Computing (ICFC)最新文献

Development and optimization of an MTConnect based edge computing node for remote monitoring in cyber manufacturing systems 基于MTConnect的边缘计算节点的开发与优化，用于网络制造系统的远程监控

2020 IEEE International Conference on Fog Computing (ICFC) Pub Date : 2020-04-01 DOI: 10.1109/ICFC49376.2020.00014

S. Sunny, Xiaoqing Frank Liu, Md Rakib Shahriar

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引用次数: 1

ICFC 2020 Commentary

2020 IEEE International Conference on Fog Computing (ICFC) Pub Date : 2020-04-01 DOI: 10.1109/icfc49376.2020.00002

引用次数: 0

ICFC 2020 TOC

2020 IEEE International Conference on Fog Computing (ICFC) Pub Date : 2020-04-01 DOI: 10.1109/icfc49376.2020.00004

引用次数: 0

R-MStorm: A Resilient Mobile Stream Processing System for Dynamic Edge Networks R-MStorm:动态边缘网络的弹性移动流处理系统

2020 IEEE International Conference on Fog Computing (ICFC) Pub Date : 2020-04-01 DOI: 10.1109/ICFC49376.2020.00018

M. Chao, R. Stoleru

{"title":"R-MStorm: A Resilient Mobile Stream Processing System for Dynamic Edge Networks","authors":"M. Chao, R. Stoleru","doi":"10.1109/ICFC49376.2020.00018","DOIUrl":"https://doi.org/10.1109/ICFC49376.2020.00018","url":null,"abstract":"Mobile Stream Processing (MSP) provides a promising approach to run computation-intensive stream applications, e.g., video face recognition, on a cluster of mobile devices at the edge. However, the performance of MSP is severely restricted by the fluctuating bandwidth and intermittent connectivity of the wireless networks connecting those devices. Therefore, to achieve a good MSP performance, implementing a resilient MSP system that adapts to dynamic edge networks is essential.In this paper, we present R-MStorm, a resilient MSP system deployed at the edge. R-MStorm improves the system survivability by (1) assigning tasks to mobile devices with higher availability to improve the availability of whole system; (2) assigning tasks of the same application components to different devices to increase the diversity of physical stream paths. Besides, to efficiently divide the output of upstream tasks to downstream tasks, R-MStorm adopts adaptive stream grouping, which considers both the transmission rate to and processing rate at each downstream task. Moreover, to alleviate congestion caused by network disconnection and stream redirection, adaptive stream selection is applied to skip some data to achieve a short response time.We conduct extensive experiments on R-MStorm by executing a video face recognition App under different network conditions. The experimental results show that, compared with baseline approaches, R-MStorm achieves up to 1.5x higher throughput, 75% lower response time, at a cost of 3.3% accuracy loss.","PeriodicalId":173977,"journal":{"name":"2020 IEEE International Conference on Fog Computing (ICFC)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128968986","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: 11

Towards Information-Centric Edge Platform for Mesh Networks: The Case of CityLab Testbed 迈向以信息为中心的网状网络边缘平台:以CityLab试验台为例

2020 IEEE International Conference on Fog Computing (ICFC) Pub Date : 2020-04-01 DOI: 10.1109/ICFC49376.2020.00016

Mennan Selimi, L. Navarro, B. Braem, Felix Freitag, Adisorn Lertsinsrubtavee

{"title":"Towards Information-Centric Edge Platform for Mesh Networks: The Case of CityLab Testbed","authors":"Mennan Selimi, L. Navarro, B. Braem, Felix Freitag, Adisorn Lertsinsrubtavee","doi":"10.1109/ICFC49376.2020.00016","DOIUrl":"https://doi.org/10.1109/ICFC49376.2020.00016","url":null,"abstract":"By leveraging resources from the Fed4Fire+ City-Lab testbed, we design the PiGeon edge computing platform that experiments solution that enable ICN based edge services in wireless mesh networks (WMNs). PiGeon combines into a platform several trends in edge computing namely the ICN (Information-Centric Networking), the containerization of services exemplified by Docker, novel service placement algorithms and the increasing availability of energy efficient but still powerful hardware at user premises (Raspberry Pi, mini-PCs, and enhanced home gateways). We underpin the PiGeon platform with Docker container-based service that can be seamlessly delivered, cached and deployed at the network edge. The core of the PiGeon platform is the Decision Engine making a decision on where and when to deploy a service instance to satisfy the service requirements while considering the network status and available hardware resources.We collect network data from a real citywide mesh network such as CityLab FIRE testbed located at the city of Antwerp, Belgium. The collected data is used to feed our service placement heuristic within the PiGeon platform. Through a real deployment in CityLab testbed, we show that our service placement heuristic improves the response time up to 37% for stateful services (Web2.0 service). Apart from improving the QoS for end-users, our results show that ICN plays a key role in improving the service delivery time as well as reducing the traffic consumption in WMNs. The overall effect of ICN in our platform is that most content and service delivery requests can be satisfied very close to the client device, many times just one hop away, decoupling QoS from intra-network traffic and origin server load.","PeriodicalId":173977,"journal":{"name":"2020 IEEE International Conference on Fog Computing (ICFC)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124130701","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: 5

Foreword to the ICFC 2020 Proceedings ICFC 2020会议录前言

2020 IEEE International Conference on Fog Computing (ICFC) Pub Date : 2020-04-01 DOI: 10.1109/icfc49376.2020.00005

引用次数: 0

tinyFaaS: A Lightweight FaaS Platform for Edge Environments tinyFaaS:边缘环境的轻量级FaaS平台

2020 IEEE International Conference on Fog Computing (ICFC) Pub Date : 2020-04-01 DOI: 10.1109/ICFC49376.2020.00011

Tobias Pfandzelter, David Bermbach

引用次数: 60

Managing Latency and Excess Data Dissemination in Fog-Based Publish/Subscribe Systems 基于雾的发布/订阅系统中延迟和过量数据传播的管理

2020 IEEE International Conference on Fog Computing (ICFC) Pub Date : 2020-04-01 DOI: 10.1109/ICFC49376.2020.00010

Jonathan Hasenburg, Florian Stanek, Florian Tschorsch, David Bermbach

引用次数: 17

Joint Power Allocation for Non-orthogonal Multiple Access in Wireless Backhaul Networks 无线回程网络中非正交多址联合功率分配

2020 IEEE International Conference on Fog Computing (ICFC) Pub Date : 2020-04-01 DOI: 10.1109/ICFC49376.2020.00013

Xiaoqi Yang, Cunqing Hua, Pengwenlong Gu, Wenchao Xu

引用次数: 2

ICFC 2020 Index

2020 IEEE International Conference on Fog Computing (ICFC) Pub Date : 2020-04-01 DOI: 10.1109/icfc49376.2020.00020

引用次数: 0