Multi-user web service selection based on multi-QoS prediction

Shangguang Wang (), Ching-Hsien Hsu (), Zhongjun Liang (), Qibo Sun () and Fangchun Yang ()
Additional contact information
Shangguang Wang: Beijing University of Posts and Telecommunications
Ching-Hsien Hsu: Chung Hua University
Zhongjun Liang: Beijing University of Posts and Telecommunications
Qibo Sun: Beijing University of Posts and Telecommunications
Fangchun Yang: Beijing University of Posts and Telecommunications

Information Systems Frontiers, 2014, vol. 16, issue 1, No 11, 143-152

Abstract: Abstract In order to find best services to meet multi-user’s QoS requirements, some multi-user Web service selection schemes were proposed. However, the unavoidable challenges in these schemes are the efficiency and effect. Most existing schemes are proposed for the single request condition without considering the overload of Web services, which cannot be directly used in this problem. Furthermore, existing methods assumed the QoS information for users are all known and accurate, and in real case, there are always many missing QoS values in history records, which increase the difficulty of the selection. In this paper, we propose a new framework for multi-user Web service selection problem. This framework first predicts the missing multi-QoS values according to the historical QoS experience from users, and then selects the global optimal solution for multi-user by our fast match approach. Comprehensive empirical studies demonstrate the utility of the proposed method.

Keywords: Web services; Service selection; QoS; Multi-user; QoS prediction (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://link.springer.com/10.1007/s10796-013-9455-4 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:infosf:v:16:y:2014:i:1:d:10.1007_s10796-013-9455-4

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10796

DOI: 10.1007/s10796-013-9455-4

Access Statistics for this article

Information Systems Frontiers is currently edited by Ram Ramesh and Raghav Rao

More articles in Information Systems Frontiers from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().