A Survey on Web Service QoS Prediction Methods

被引:47
作者
Ghafouri, Seyyed Hamid [1 ]
Hashemi, Seyyed Mohsen [1 ]
Hung, Patrick C. K. [2 ]
机构
[1] Islamic Azad Univ, Sci & Res Branch, Comp Engn Dept, Tehran, Iran
[2] Univ Ontario Inst Technol, Fac Business & IT, Oshawa, ON, Canada
关键词
Quality of service; Web services; Clustering algorithms; Prediction methods; Collaboration; Web service; quality of wervice; QoS prediction; collaborative filtering; recommender system; GEOGRAPHICAL NEIGHBORHOOD; RECOMMENDATION; LOCATION; TRUST; QUALITY; CLOUD; ALGORITHM; FRAMEWORK; DRIVEN;
D O I
10.1109/TSC.2020.2980793
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Nowadays, there are many Web services with similar functionality on the Internet. Users consider Quality of Service (QoS) of the services to select the best service from among them. The prediction of QoS values of the Web services and recommendations of the best service based on these values to the users is one of the major challenges in the web service area. Major studies in this field use collaboration filtering based methods for prediction. The paper introduced prediction methods and divided them into three main categories: memory-based methods, model-based methods, and Collaborative Filtering (CF) methods combined with other methods. In each category, some of the most famous studies were introduced, and then the problems and benefits of each category were reviewed. Finally, we have a discussion about these methods and propose suggestions for future works.
引用
收藏
页码:2439 / 2454
页数:16
相关论文
共 112 条
[11]  
Chen L., 2019, COMPLEXITY, V2019
[12]   Web Service Recommendation via Exploiting Location and QoS Information [J].
Chen, Xi ;
Zheng, Zibin ;
Yu, Qi ;
Lyu, Michael R. .
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, 2014, 25 (07) :1913-1924
[13]  
Chen Z, 2003, ICWS'03: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON WEB SERVICES, P171
[14]   Your neighbors are misunderstood: On modeling accurate similarity driven by data range to collaborative web service QoS prediction [J].
Chen, Zhen ;
Shen, Limin ;
Li, Feng .
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2019, 95 :404-419
[15]   Alleviating Data Sparsity in Web Service QoS Prediction by Capturing Region Context Influence [J].
Chen, Zhen ;
Shen, Limin ;
You, Dianlong ;
Li, Feng ;
Ma, Chuan .
COLLABORATE COMPUTING: NETWORKING, APPLICATIONS AND WORKSHARING, COLLABORATECOM 2016, 2017, 201 :540-556
[16]   Your neighbors alleviate cold-start: On geographical neighborhood influence to collaborative web service QoS prediction [J].
Chen, Zhen ;
Shen, Limin ;
Li, Feng ;
You, Dianlong .
KNOWLEDGE-BASED SYSTEMS, 2017, 138 :188-201
[17]   Exploiting Web service geographical neighborhood for collaborative QoS prediction [J].
Chen, Zhen ;
Shen, Limin ;
Li, Feng .
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2017, 68 :248-259
[18]  
Chen Z, 2016, INT C COMP SUPP COOP, P316, DOI 10.1109/CSCWD.2016.7566007
[19]   Trust-Based Personalized Service Recommendation: A Network Perspective [J].
Deng, Shui-Guang ;
Huang, Long-Tao ;
Wu, Jian ;
Wu, Zhao-Hui .
JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY, 2014, 29 (01) :69-80
[20]   Social network-based service recommendation with trust enhancement [J].
Deng, Shuiguang ;
Huang, Longtao ;
Xu, Guandong .
EXPERT SYSTEMS WITH APPLICATIONS, 2014, 41 (18) :8075-8084