Trusted Service Provider Discovery Based on Data, Information, Knowledge, and Wisdom

被引:6
作者
Lei, Yu [1 ]
Duan, Yucong [2 ]
机构
[1] Inner Mongolia Univ, Dept Comp Sci, Hohhot, Inner Mongolia, Peoples R China
[2] Hainan Univ, Sch Comp & Cyberspace Secur, Haikou, Hainan, Peoples R China
关键词
Knowledge graphs; trusted service discovery; reasoning; PROTECTION; FRAMEWORK; SYSTEM;
D O I
10.1142/S0218194021400015
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Data, information, knowledge, and wisdom forms a progressive relationship. Information is formed by data collation. Knowledge is filtered, refined, and processed from relevant information. Wisdom is based on knowledge and is accumulated through experience. This paper uses the progressive relationship of service data, information, knowledge, and wisdom to explain the expression of service knowledge graph. It is an increasingly challenging demand to discover trusted Cloud service providers with service data, information, and knowledge. We propose an efficient method of trusted service provider discovery based on service knowledge graphs, called PDG (Provider Discovery based on Graphs), to ensure that each service instance of composite services in Cloud systems is trustworthy. PDG evaluates the outputs of service providers in service classes with the help of additional service information. According to the additional service information, service knowledge is generated and trusted service providers can be found easily. PDG improves the accuracy of processing results by automatically replacing data provided by untrusted service providers with results provided by trusted service providers.
引用
收藏
页码:3 / 19
页数:17
相关论文
共 47 条
[41]   Social Learning Evolution (SLE): Computational Experiment-Based Modeling Framework of Social Manufacturing [J].
Xue, Xiao ;
Wang, Shufang ;
Zhang, Lejun ;
Feng, Zhiyong ;
Guo, Yaodan .
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2019, 15 (06) :3343-3355
[42]   CloudScout: A Non-Intrusive Approach to Service Dependency Discovery [J].
Yin, Jianwei ;
Zhao, Xinkui ;
Tang, Yan ;
Zhi, Chen ;
Chen, Zuoning ;
Wu, Zhaohui .
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, 2017, 28 (05) :1271-1284
[43]   Ontology-based service discovery framework for dynamic environments [J].
Zeshan, Furkh ;
Mohamad, Radziah ;
Ahmad, Mohammad Nazir ;
Hussain, Syed Asad ;
Ahmad, Adnan ;
Raza, Imran ;
Mehmood, Abid ;
Ulhaq, Ikram ;
Abdulgader, Arafat ;
Babar, Imran .
IET SOFTWARE, 2017, 11 (02) :64-74
[44]   Dynamic Uncertain Causality Graph for Knowledge Representation and Reasoning: Utilization of Statistical Data and Domain Knowledge in Complex Cases [J].
Zhang, Qin ;
Yao, Quanying .
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2018, 29 (05) :1637-1651
[45]   A hybrid approach combining an extended BBO algorithm with an intuitionistic fuzzy entropy weight method for QoS-aware manufacturing service supply chain optimization [J].
Zhang, Shuai ;
Xu, Song ;
Zhang, Wenyu ;
Yu, Dejian ;
Chen, Kai .
NEUROCOMPUTING, 2018, 272 :439-452
[46]   EWnFM: An Environment States Oriented Web Service Non-Functional Property Model [J].
Zhang, Yin ;
Ge, Liang ;
Gao, Kening ;
Zhang, Bin ;
Xue, Zhuyin .
ENTROPY, 2015, 17 (02) :509-527
[47]  
Zhang YY, 2018, AAAI CONF ARTIF INTE, P6069