Qos Prediction for Web Services Based on Deep Learning

Registration ID: IJNRD_214169

Published ID: IJNRD2402297

DOI: Click Here to Get

Thinh Van Le , Nguyen Huu Truc

Deep learning; AutoenCoder; QoS Prediction

With the rapidly growing number of service providers and users, as a result, there are three important issues that we now have to deal with: Firstly, we face challenges with increasingly large data sets. Secondly, many Web service providers have similar functionality but differ in quality properties and services. Finally, there will have a large number of missing QoS values in history records. Therefore, predicting the missing QoS values in the large data sets is becoming more attractive. In this paper, we proposed a new model based on AutoenCoder to solve the above existing problems. It is called AutoenCoder-based Web Service (AWS). The model is performed with two predictions (User-based AWS and Service-based AWS) and the backpropagation algorithm and Stochastic Gradient Descent is used to train the model. The experimental results demonstrated that proposed model has better performance than other approaches

Published Paper   E-Certificate

Thinh Van Le & Nguyen Huu Truc (February-2024). Qos Prediction for Web Services Based on Deep Learning . INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(2), c882-c889. https://ijnrd.org/papers/IJNRD2402297.pdf

Volume 9 Issue 2, February-2024

Pages : c882-c889

Paper Reg. ID: IJNRD_214169

Published Paper Id: IJNRD2402297

Downloads: 000121979

Research Area: Computer Science & Technology 

Country: Tuy Hoa, x, Viet Nam

Published Paper PDF: https://ijnrd.org/papers/IJNRD2402297.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2402297

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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