Authors:
Malvina Latifaj
;
Federico Ciccozzi
and
Séverine Sentilles
Affiliation:
School of Innovation, Design and Engineering, Mälardalen University, Sweden
Keyword(s):
Industrial Cloud Computing, Quality of Service, Quality Attributes, Systematic Mapping Study.
Abstract:
The rapid development of Industry 4.0 and Industrial Cyber-Physical Systems is leading to the exponential growth of unprocessed volumes of data. Industrial cloud computing has great potential for providing the resources for processing this data. To be widely adopted, the cloud must ensure satisfactory levels of Quality of Service (QoS). However, the lack of a standardized model of quality attributes hinders the assessment of QoS levels. This paper provides a comprehensive systematically defined map of current research trends, results, and gaps in quality attributes and QoS in industrial cloud computing. An extract of the main insights is as follows: (i) the adoption of cloud technologies is closely related to performance indicators, however other quality attributes, such as security, are not considered as much as they should; (ii) solutions are most often not tailored to specific industrial application domains; (iii) research largely focuses on providing solutions without solid valid
ation, unsuitable for effective and fruitful technology transfer.
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