Title: Comparative study of Topk 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 Topk 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 Topk algorithm combined with the weighted sum method. This approach is introduced for refining the skyline result using the Topk 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: Topk; skyline; weighted sum method; cloud service; Fagin's algorithm; quality of service; QoS; correlation.
International Journal of Internet Technology and Secured Transactions, 2020 Vol.10 No.1/2, pp.143 - 170
Received: 25 Mar 2018
Accepted: 17 May 2018
Published online: 21 Jan 2020 *