Analysis of E-Commerce Big Data using Clustering and CloudSim Load Balancing | Zendy

Neha Jain | Zendy; Anil Suryavanshi | Zendy

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Analysis of E-Commerce Big Data using Clustering and CloudSim Load Balancing

Author(s) -

Neha Jain,

Anil Suryavanshi

Publication year - 2017

Publication title -

international journal of computer applications

Language(s) - English

Resource type - Journals

ISSN - 0975-8887

DOI - 10.5120/ijca2017913327

Subject(s) - computer science , cloudsim , cluster analysis , big data , data mining , artificial intelligence , operating system , cloud computing

In this paper an efficient technique is implemented for the analysis of E-Commerce based Applications over Big Data. The Proposed Methodology implemented here is based on the concept of providing Extracting Feature Vectors from the E-Commerce Data and Load balancing of Data using CloudSim based Load balancing and finally Clustered the Data. The Proposed Methodology implemented provides efficient Accuracy & Processing Time as compared to the existing methodology implemented for the analysis of ECommerce Data.

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