izpis_h1_title_alt

A capillary computing architecture for dynamic Internet of Things : orchestration of microservices from edge devices to fog and cloud providers
ID Taherizadeh, Salman (Author), ID Stankovski, Vlado (Author), ID Grobelnik, Marko (Author)

.pdfPDF - Presentation file, Download (3,59 MB)
MD5: C0A0D98281BEE9BF19ACA0B2AF42480A
URLURL - Source URL, Visit http://www.mdpi.com/1424-8220/18/9/2938 This link opens in a new window

Abstract
The adoption of advanced Internet of Things (IoT) technologies has impressively improved in recent years by placing such services at the extreme Edge of the network. There are, however, specific Quality of Service (QoS) trade-offs that must be considered, particularly in situations when workloads vary over time or when IoT devices are dynamically changing their geographic position. This article proposes an innovative capillary computing architecture, which benefits from mainstream Fog and Cloud computing approaches and relies on a set of new services, including an Edge/Fog/Cloud Monitoring System and a Capillary Container Orchestrator. All necessary Microservices are implemented as Docker containers, and their orchestration is performed from the Edge computing nodes up to Fog and Cloud servers in the geographic vicinity of moving IoT devices. A car equipped with a Motorhome Artificial Intelligence Communication Hardware (MACH) system as an Edge node connected to several Fog and Cloud computing servers was used for testing. Compared to using a fixed centralized Cloud provider, the service response time provided by our proposed capillary computing architecture was almost four times faster according to the 99th percentile value along with a significantly smaller standard deviation, which represents a high QoS.

Language:English
Keywords:Internet of Things, container-based virtualization, edge computing, fog computing, microservices, on/offloading
Work type:Article
Typology:1.01 - Original Scientific Article
Organization:FGG - Faculty of Civil and Geodetic Engineering
Publication status:Published
Publication version:Version of Record
Year:2018
Number of pages:23 str.
Numbering:Vol. 18, iss. 9, art. 2938
PID:20.500.12556/RUL-132104 This link opens in a new window
UDC:004.738.5
ISSN on article:1424-8220
DOI:10.3390/s18092938 This link opens in a new window
COBISS.SI-ID:8522593 This link opens in a new window
Publication date in RUL:13.10.2021
Views:572
Downloads:134
Metadata:XML RDF-CHPDL DC-XML DC-RDF
:
Copy citation
Share:Bookmark and Share

Record is a part of a journal

Title:Sensors
Shortened title:Sensors
Publisher:MDPI
ISSN:1424-8220
COBISS.SI-ID:10176278 This link opens in a new window

Licences

License:CC BY 4.0, Creative Commons Attribution 4.0 International
Link:http://creativecommons.org/licenses/by/4.0/
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
Licensing start date:04.09.2018

Secondary language

Language:Slovenian
Keywords:internet stvari, vizualizacija z uporabo vsebnikov, rob omrežja, računalništvo v megli, mikro-servisi

Projects

Funder:EC - European Commission
Funding programme:H2020
Project number:732339
Name:Proactive Cloud Resources Management at the Edge for Efficient Real-Time Big Data Processing
Acronym:PrEstoCloud

Funder:EC - European Commission
Funding programme:H2020
Project number:815141
Name:Decentralised technologies for orchestrated cloud-to-edge intelligence
Acronym:DECENTER

Funder:EC - European Commission
Funding programme:H2020
Project number:636160
Name:Multi-source Big Data Fusion Driven Proactivity for Intelligent Mobility
Acronym:OPTIMUM

Similar documents

Similar works from RUL:
Similar works from other Slovenian collections:

Back