A Novel Approach for Clustering Large-scale Cloud Data using Computational Mechanism

Abstract

In the present situation, with the enhancement of virtualization techniques, it is very essential to keep track of accumulated large-scaled heterogeneous data in every respect. In addition to that, it is also necessary to prioritize the processing mechanisms when being linked with clustered data. Sometimes it has been observed that the large scaled datasets are too complex and therefore, the normal computation mechanisms are not sufficient or adequate for the specific applications. But it is highly required to observe the significance of each individual dataset and focus on the responses being accumulated from other aspects to make a suitable decision and generation of efficient analytical clustered data. The main aim of such applications is to apply the clustering gaining merits from evolutionary computation to process the large-scaled data and based on optimality, the performance of datasets can be measured.