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Source code management systems (such as Concurrent Versions System (CVS), Subversion, and git) record changes to code repositories of open source software projects. This study explores a fuzzy data mining algorithm for time series data to generate the association rules for evaluating the existing trend and regularity in the evolution of open source software project. The idea to choose fuzzy data mining algorithm for time series data is due to the stochastic nature of the open source software development process. Commit activity of an open source project indicates the activeness of its development community. An active development community is a strong contributor to the success of an open source project. Therefore commit activity analysis along with the trend and regularity analysis for commit activity of open source software project acts as an important indicator to the project managers and analyst regarding the evolutionary prospects of the project in the future.

Pricing of the services, is one of the main factor in deciding the will of any organization, for the growth, In the existing Security Mechanisms of the Cloud, the way of providing Security to Cloud user is purely Provider-driven and user has no role in deciding, which security capabilities, he actually wants, based on the significance of his Cloud Instance. As a result of which, a cost inefficient Security Pricing persists in Cloud Computing. This paper focuses on exploring the pricing of existing Security mechanism and proposes a new user-driven approach, which will prove to be a cost-efficient in regard of former approach and will play a role of catalyst in large scale adoption of the Cloud Computing.

Smart grid is maximum optimization of energy management achieved through transmission and distribution automation, efficient use of existing network and integration of smart devices. The intelligent monitoring sensors generate enormous heterogeneous, uncorrelated and unstructured data which need large number of scalable storage servers. The analytic tools and control and optimization algorithms require reliable computation servers for self-healing, fault tolerant, load balancing, demand response and optimal power flow features. Also the customer web applications for real-time consumption patterns, flexible tariffs and online bill payments need designing and deployment tools. The lack of computing infrastructure and financial constraints are the primary challenges for full realization of complex smart grid in developing countries like India. The appliance of the cloud computing model meets the requirement of data and computing intensive smart grid applications. Through the proposed cloud computing model, smart grid can enhance the reliability, availability, safety, efficiency and environment friendliness of power sector.