Title: Comparative study of Top_k based on Fagin's algorithm using correlation metrics in cloud computing QoS

Authors: Kaoutar El handri; Abdellah Idrissi

Addresses: IPSS Team, Computer Science Department, Faculty of Sciences, Mohammed V University in Rabat, Morocco ' IPSS Team, Computer Science Department, Faculty of Sciences, Mohammed V University in Rabat, Morocco

Abstract: With the exponential growth of cloud computing services recently, several internet technologies began to require the processing of multi-criteria ranking. The collaborative filtering methods and Top_k selection computations have been proven to be more effective in information retrieval. In addition, they are widely used to evaluate the QoS for cloud services recommendation. However, the biggest challenge is not only to reduce the size of skyline results, but also to have a good response quality that reflects the user requirement. To deal with these problems, we propose in this paper an approach based on Top_k algorithm combined with the weighted sum method. This approach is introduced for refining the skyline result using the Top_k query advantages. Then in order to evaluate the performance of our approach, we compared the proposed algorithm with Fagin's one. The experimental results show the efficiency of our algorithm particularly in comparing the runtime results and using specific metrics of correlation.

Keywords: Top_k; skyline; weighted sum method; cloud service; Fagin's algorithm; quality of service; QoS; correlation.

DOI: 10.1504/IJITST.2020.104579

International Journal of Internet Technology and Secured Transactions, 2020 Vol.10 No.1/2, pp.143 - 170

Received: 17 Feb 2018
Accepted: 17 May 2018
Published online: 21 Jan 2020 *

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