Title
A Personalized QoS Prediction Method for Web Services via Blockchain-Based Matrix Factorization.
Abstract
Personalized quality of service (QoS) prediction plays an important role in helping users build high-quality service-oriented systems. To obtain accurate prediction results, many approaches have been investigated in recent years. However, these approaches do not fully address untrustworthy QoS values submitted by unreliable users, leading to inaccurate predictions. To address this issue, inspired by blockchain with distributed ledger technology, distributed consensus mechanisms, encryption algorithms, etc., we propose a personalized QoS prediction method for web services that we call blockchain-based matrix factorization (BMF). We develop a user verification approach based on homomorphic hash, and use the Byzantine agreement to remove unreliable users. Then, matrix factorization is employed to improve the accuracy of predictions and we evaluate the proposed BMF on a real-world web services dataset. Experimental results show that the proposed method significantly outperforms existing approaches, making it much more effective than traditional techniques.
Year
DOI
Venue
2019
10.3390/s19122749
SENSORS
Keywords
Field
DocType
web services,quality of service,QoS prediction,blockchain
Consensus,Homomorphic encryption,Matrix decomposition,Quality of service,Encryption,Electronic engineering,Hash function,Blockchain,Engineering,Web service,Distributed computing
Journal
Volume
Issue
ISSN
19
12
1424-8220
Citations 
PageRank 
References 
1
0.34
0
Authors
3
Name
Order
Citations
PageRank
Weihong Cai146.51
Xin Du212726.78
Jianlong Xu3184.00