No abstract

Cloud computing is a new technology used to manipulate, configure and can be used to access distributed computing applications in the network. It implements the load balancing approach which is used to distribute all of its workload to every node connected in the network. By using this technique resource utilization is done properly. It can also used to achieve user satisfaction and computing resources. If load balancing is used properly then it can efficiently and properly implement the fail-over, scalability, over- provisioning techniques. It can also minimize the resources used and avoid the bottleneck. In my research, review of different load balancing techniques, its usage, limitations, applications and various performance metrics are described..

In analyzing project regressions, automation has emerged as a major agenda in managing changes in software which requires minimum manual intervention. For rapid testing environment, software development processes such as Agile, Scrum, and XP processes depend on continuous integration tools. There is no single tool to handle the project automation, and the main challenge is dependency on multiple tools. The proposed automation tool should support configuration, execution, and debugging facility. Integrating the project automation works such as software configuration management tools Mercurial and Git, job scheduling tools like Jenkins and Apache Continuum, test management tools like TestNG and Selenium need tight integration which is a challenge. The existing PKI infrastructure for access control does not share data among the software tools and processes increasing the complexity when an organization needs to leverage the existing cloud services. The proposed approach optimizes the execution time by taking single CSV with input test case and metadata information and efficiently group and executes the tests automatically. The proposed method includes implementation of security access control mechanism for the jobs execution platform in cloud environment.

The demand of cloud computing is increasing day by day. The whole scenario is changing due to rise in issues with regard to the speed of access, privacy and security of data. The data repositories are showing a real time shift from general data base management systems to cloud storage. This step in technology has made our data prone to attacks from intruders and moreover, this has also created an increased load on the technology used. The sole aim of this research work is to improve the performance of computing systems and their security in cloud environment. A new technology is proposed to balance the load on cloud computing and to improve the quality of cloud service with PSO is presented in this research work.

Cloud computing represents a new era of computing network, where the resources of the system are dispersed and shared among its users in the network premises. The user of this system is able to use such resources through the technology of internet based on system of Pay-As-Per-Use. If a service is used by any type of user, it helps in production of wide variety of data. So, the cost of data transfer between two of the dependent resources will be extremely high. Additionally, an application of complex nature involves large number of tasks boosting the process of total cost of execution with respect to the used application, if the process is not scheduled in an optimized manner. In order to overcome such issues, a hybrid approach of water cycle optimization is proposed with particle swarm optimization. This method is divided into two steps of working determining under and over utilized virtual machines. In experimental analysis, the proposed approach on different scientific workflows is done where significant performance in all the workflows is based on total execution time and total execution cost