Addressing the Node Discovery Problem in Fog Computing release_mxhglwx5lvf2nnbve3tpubzmou

by Vasileios Karagiannis, Nitin Desai, Stefan Schulte, Sasikumar Punnekkat, Yang Yang, Anton Cervin

Published in Workshop on Fog Computing and the Internet of Things by Schloss Dagstuhl - Leibniz-Zentrum für Informatik.

2020   p5:1-5:10

Abstract

In recent years, the Internet of Things (IoT) has gained a lot of attention due to connecting various sensor devices with the cloud, in order to enable smart applications such as: smart traffic management, smart houses, and smart grids, among others. Due to the growing popularity of the IoT, the number of Internet-connected devices has increased significantly. As a result, these devices generate a huge amount of network traffic which may lead to bottlenecks, and eventually increase the communication latency with the cloud. To cope with such issues, a new computing paradigm has emerged, namely: fog computing. Fog computing enables computing that spans from the cloud to the edge of the network in order to distribute the computations of the IoT data, and to reduce the communication latency. However, fog computing is still in its infancy, and there are still related open problems. In this paper, we focus on the node discovery problem, i.e., how to add new compute nodes to a fog computing system. Moreover, we discuss how addressing this problem can have a positive impact on various aspects of fog computing, such as fault tolerance, resource heterogeneity, proximity awareness, and scalability. Finally, based on the experimental results that we produce by simulating various distributed compute nodes, we show how addressing the node discovery problem can improve the fault tolerance of a fog computing system.
In text/plain format

Archived Files and Locations

application/pdf   611.9 kB
file_chrnux6fjfd6nbhhr63lifju5u
drops.dagstuhl.de (web)
web.archive.org (webarchive)
Read Archived PDF
Preserved and Accessible
Type  paper-conference
Stage   published
Year   2020
Language   en ?
Work Entity
access all versions, variants, and formats of this works (eg, pre-prints)
Catalog Record
Revision: 709df6b5-e103-4b9b-88c7-707573a196eb
API URL: JSON