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Full Record Details
Persistent URL
http://purl.org/net/epubs/work/49245813
Record Status
Checked
Record Id
49245813
Title
Managing the Cloud Continuum: Lessons Learnt from a Real Fog-to-Cloud Deployment
Contributors
X Masip-Bruin (UPC Barcelona)
,
E Marín-Tordera (UPC Barcelona)
,
S Sánchez-López (UPC Barcelona)
,
J Garcia (UPC Barcelona)
,
A Jukan (TU Braunschweig)
,
A Juan-Ferrer (ATOS Barcelona)
,
A Queralt (Barcelona Supercomputing Center)
,
A Salis (Engineering IT)
,
A Bartoli (Engineering IT)
,
M Cankar (XLAB)
,
C Cordeiro (SixSQ)
,
J Jensen (STFC Rutherford Appleton Lab.)
,
J Kennedy (INTEL)
Abstract
The wide adoption of the recently coined fog and edge computing paradigms alongside conventional cloud computing creates a novel scenario, known as the cloud continuum, where services may benefit from the overall set of resources to optimize their execution. To operate successfully, such a cloud continuum scenario demands for novel management strategies, enabling a coordinated and efficient management of the entire set of resources, from the edge up to the cloud, designed in particular to address key edge characteristics, such as mobility, heterogeneity and volatility. The design of such a management framework poses many research challenges and has already promoted many initiatives worldwide at different levels. In this paper we present the results of one of these experiences driven by an EU H2020 project, focusing on the lessons learnt from a real deployment of the proposed management solution in three different industrial scenarios. We think that such a description may help understand the benefits brought in by a holistic cloud continuum management and also may help other initiatives in their design and development processes.
Organisation
STFC
,
SCI-COMP
,
SCI-COMP-DST
Keywords
fog computing
,
fog-to-cloud
,
internet of things
,
edge computing
,
cloud continuum
,
IoT
Funding Information
EU
, Horizon 2020 (730929)
Related Research Object(s):
Licence Information:
Language
English (EN)
Type
Details
URI(s)
Local file(s)
Year
Journal Article
Sensors
21, no. 9 (2021): 2974.
doi:10.3390/s21092974
2021
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