By Topic

An Enhanced PROMETHEE Model for QoS-Based Web Service Selection

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Karim, R. ; Dept. of Comput. Sci., Ryerson Univ., Toronto, ON, Canada ; Chen Ding ; Chi-Hung Chi

Since selecting a web service based on Quality of Services (QoS) is essentially a Multi-Criteria Decision Making (MCDM) problem, various MCDM models would be suitable for implementing the selection systems. A few of the MCDM approaches have been explored in previous research works. In this paper, we propose to use an enhanced PROMETHEE model for QoS-based web service selection. Many selection algorithms assume the independency between the QoS criteria, which is not very accurate. Thus, our first enhancement is to take into account the QoS interdependency by using the Analytical Network Process (ANP) to calculate the weight/priority associated with each criterion. User's QoS requirement is not considered in the original PROMETHEE model. As a consequence, during the process of finding an optimal service, when tradeoff decisions are involved, we may end up with a service which optimizes the overall QoS criteria, however, does not satisfy the user request. To overcome this insufficiency, our second enhancement is to check the outranking flows of each service with respect to the request in the ranking step, so that we know how well a service satisfies the user requirement. A case study is presented to explain the detailed selection process.

Published in:

Services Computing (SCC), 2011 IEEE International Conference on

Date of Conference:

4-9 July 2011