Performance analysis of static images and solution for dynamic tracking in private cloud

Nowadays, the World Wide Web has grown tremendously and become more complex because of the growing number of users and the content being added in varied formats. Cloud computing is used as a platform where large amount of data or information can be stored (as it has more storage options) easily as a pay per use model. Hence the storage will not deal only with structured document; possibility of unstructured document storage will also be there. In order to compensate that there is a need to move on to unstructured database system which is mongodb. MongoDB (from "humongous") is an open source, scalable, high-performance, schema-free, document-oriented database. Technologies like cloud computing and SaaS(Software as a Service) in cloud are growing rapidly which replaces the exisiting traditional applications. The disadvantage in maintaining, integrating and acquiring traditional softwares are overcome by cloud applications. In this paper initially a static application is deployed into the private cloud environment as an image and its performance is evaluated. In the proposed system a weblog will be created with the features of locating exact source which is retrieved dynamically from web. The dynamic software application is bundled in to image and then deployed in the private cloud environment. In existing system the search was done only based on annotated word but in proposed system the search will be done concept wise meaningfully using Machine Learning techniques. The dynamic retrieval will be done using meta heuristic techniques and performance will be evaluated under private cloud environment. Then comparison will be done between static and dynamic application as the future work.