QoS Ranking Prediction Approach for Cloud Services Using Spearman Rank Correlation Based Nature Inspired Firefly Optimization
Keywords:
Cloud computing, quality of service (QoS),, Cloud Service Provider, Ranking Prediction, Rank Correlation, SelectionAbstract
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 Spearman Rank Correlation Based Nature Inspired Firefly Optimization (SRC-NIFO) method is analyzed 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
References
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