@Article{iasc.2023.030484,
AUTHOR = {Wenlong Ma, Youhong Xu, Jianwei Zheng, Sadaqat ur Rehman},
TITLE = {QoS-Aware Cloud Service Optimization Algorithm in Cloud Manufacturing Environment},
JOURNAL = {Intelligent Automation \& Soft Computing},
VOLUME = {37},
YEAR = {2023},
NUMBER = {2},
PAGES = {1499--1512},
URL = {http://www.techscience.com/iasc/v37n2/53201},
ISSN = {2326-005X},
ABSTRACT = {In a cloud manufacturing environment with abundant functionally equivalent cloud services, users naturally desire the highest-quality service(s). Thus, a comprehensive measurement of quality of service (QoS) is needed. Optimizing the plethora of cloud services has thus become a top priority. Cloud service optimization is negatively affected by untrusted QoS data, which are inevitably provided by some users. To resolve these problems, this paper proposes a QoS-aware cloud service optimization model and establishes QoS-information awareness and quantification mechanisms. Untrusted data are assessed by an information correction method. The weights discovered by the variable precision Rough Set, which mined the evaluation indicators from historical data, providing a comprehensive performance ranking of service quality. The manufacturing cloud service optimization algorithm thus provides a quantitative reference for service selection. In experimental simulations, this method recommended the optimal services that met users’ needs, and effectively reduced the impact of dishonest users on the selection results.},
DOI = {10.32604/iasc.2023.030484}
}