Paper Info
Title
A Service Trust Evaluation Model Using Clustering Fuzzy Inference For Guiding Network Service Selection
Abstract
The evolution of distributed and virtualized network services makes service selection difficult, as service providers and their links are becoming open and random. The trust degree of service providers is considered as an effective guidance, but it is unmethodical to establish and maintain a clear and stable trust relationship between them. Traditional solutions of service trust evaluation are not comprehensive and accurate enough, because they generally do not take randomness and fuzziness into account. In this context, a model of service trust evaluation based on clustering fuzzy inference for guiding network service selection is proposed in this paper. Four clustering evaluation indexes are determined, and an evaluation mechanism is established based on the fuzzy membership function. The valuation process is time-aware, and the fuzzy knowledge base can be iteratively updated to keep the trust degree fresh. Simulation experiments illustrate the feasibility of the proposed model and indicate the superiority of greater performance compared with other similar solutions.
Year
DOI
Venue
2018
10.1002/dac.3790
INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS
Keywords
Field
DocType
fuzzy inference, service evaluation, service selection, trust, trust restoration
Network service,Computer science,Fuzzy inference,Computer network,Artificial intelligence,Service selection,Cluster analysis
Journal
Volume
Issue
ISSN
31
17
1074-5351
Citations 
PageRank 
References 
0
0.34
5
Authors
2
Name
Order
Citations
PageRank
Zhaozheng Li100.68
Weimin Lei22916.35