Distributed analytics in fog computing platforms using tensorflow and kubernetes

Pei Hsuan Tsai, Hua Jun Hong, An Chieh Cheng, Cheng Hsin Hsu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

44 Citations (Scopus)

Abstract

Modern Internet-of-Things (IoT) applications produce large amount of data and require powerful analytics approaches, such as Deep Learning to extract useful information. Existing IoT applications transmit the data to resource-rich data centers for analytics. However, it may congest networks, overload data centers, and increase security vulnerability. In this paper, we implement a platform, which integrates resources from data centers (servers) to end devices (IoT devices). We launch distributed analytics applications among the devices without sending everything to the data centers. We analyze challenges to implement such a platform and carefully adopt popular open-source projects to overcome the challenges. We then conduct comprehensive experiments on the implemented platform. The results show: (i) the benefits/limitations of distributed analytics, (ii) the importance of decisions on distributing an application across multiple devices, and (iii) the overhead caused by different components in our platform.

Original languageEnglish
Title of host publication19th Asia-Pacific Network Operations and Management Symposium
Subtitle of host publicationManaging a World of Things, APNOMS 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages145-150
Number of pages6
ISBN (Electronic)9781538611012
DOIs
Publication statusPublished - 2017 Nov 1
Event19th Asia-Pacific Network Operations and Management Symposium, APNOMS 2017 - Seoul, Korea, Republic of
Duration: 2017 Sept 272017 Sept 29

Publication series

Name19th Asia-Pacific Network Operations and Management Symposium: Managing a World of Things, APNOMS 2017

Other

Other19th Asia-Pacific Network Operations and Management Symposium, APNOMS 2017
Country/TerritoryKorea, Republic of
CitySeoul
Period17-09-2717-09-29

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Hardware and Architecture
  • Information Systems and Management

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