• S.Beghin Bose
• Dr.S.S.Sujatha

QoS (Quality of Services) is a very important research topic in cloud computing. When we select an optimal cloud service from functionally equivalent service we use QoS value for a good decision making. QoS ranking provides priceless information in selecting the best cloud service in cloud computing. In order to avoid time consumption and to select the best service for the cloud customer a good QoS ranking prediction framework is required. It should be a much user as friendly and less time consuming. In this paper Generalized Jaccard Coefficient Similarity based Grey Wolf Optimization (GJCS-GWO) based optimization method is proposed for ranking prediction. It will give higher accuracy and be less time consuming. When the proposed framework is compared with the previous works on the basics of response in time, throughput, and latency the proposed work is proved to be much better than the previous works.

Generalized Jaccard Coefficient, Grey Wolf Optimization, Ranking Prediction, Optimization, QoS.

"Optimized QoS Ranking Prediction Using Generalized Jaccard Coefficient Similarity based Grey Wolf Optimization (GJCS-GWO) ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.362-365, May-2019, Available :http://www.jetir.org/papers/JETIR1905D51.pdf

"Optimized QoS Ranking Prediction Using Generalized Jaccard Coefficient Similarity based Grey Wolf Optimization (GJCS-GWO) ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp362-365, May-2019, Available at : http://www.jetir.org/papers/JETIR1905D51.pdf