QoS-Aware Cloud Service Optimization Algorithm in Cloud Manufacturing Environment  

作　　者：Wenlong Ma Youhong Xu Jianwei Zheng Sadaqat ur Rehman 

机构地区：[1]School of Information Engineering,Quzhou College of Technology,Quzhou,324000,China [2]School of Computer Science and Technology,Zhejiang University of Technology,Hangzhou,310023,China [3]Department of Natural and Computing Science,University of Aberdeen,Scotland,Aberdeen,AB243FX,UK

出　　处：《Intelligent Automation & Soft Computing》2023年第8期1499-1512,共14页智能自动化与软计算（英文）

基　　金：supported by the National Natural Science Foundation,China (Grant No:61602413,Jianwei Zheng,https://www.nsfc.gov.cn);the Natural Science Foundation of Zhejiang Province (Grant No:LY15E050007,Wenlong Ma,http://zjnsf.kjt.zj.gov.cn/portal/index.html).

摘　　要：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.Opti-mizing the plethora of cloud services has thus become a top priority.Cloud ser-vice 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 dis-honest users on the selection results.

关 键 词：Cloud manufacturing quality of service optimization algorithm rough set 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]