vioft2nntf2t|tblJournal|Abstract_paper|0xf4ffb84c2a000000fd09020001000500 Web Services in ample amount lying over the net are found similar in functionality varying in QoS (Quality of Services). Various methods and techniques have been proposed by researchers in order to get the most favoured and best-suited candidate services to be able to become the part of the final outcome which is called composite web service. Quality of Service has emerged as an important tool playing decisive role while selecting best candidate web Services as well as Composite Web Services. Undoubtedly, the technique of web services composition is the key property of service-orientation helps create new as well as advanced level services reusing the existing ones. In a distributed environment, services with no quality guarantees, have adverse impact on the final composition outcome. In their efforts to select the most favoured candidate services to be used for the composition, scholars while proposing new composition techniques relied on either Users’ provided feedbacks or Providers’ provided information. None of them took into account both of the information altogether. In our novel approach, we took into account both of the information (Users’ provided feedbacks and Providers’ provided information) altogether. We have designed an innovative framework incorporating an entity called Information Verification Engine whose job is to take into account both of the information, filtering out malicious feedback ratings and cross verifying both of the information in order to find the most suitable candidate web services. We have implemented this newly added Engine taking into account total of 450 Web Services and applying Statistical Computations using SPSS version 21.0. This has helped achieve a set of 279 web services, purely rated by Unbiased Users. Then We Cross Verified both of the ratings which further reduced no. of Web Services to 83. Experimental results confirmed the efficiency and reliability of our proposed framework. Detailed methodology and its implementation has been presented in the later part of this paper.
Khozema Shabbar1, Tarun Shrimali2, Ajay Chaudhary3
Career Point University, India1, Janardan Rai Nagar Rajasthan Vidyapeeth, India2, Government Meera Girls College, India3
Web Services Composition, SPSS, Mean, Mode, Median, SD, Skewness
| January | February | March | April | May | June | July | August | September | October | November | December |
| 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Published By :
ICTACT
Published In :
ICTACT Journal on Soft Computing
( Volume: 9 , Issue: 3 , Pages: 1932-1938 )
Date of Publication :
April 2019
Page Views :
186
Full Text Views :
1
|