Automated Intelligent Systems for Secure Live Migration

Cloud computing provides on-demand computing and storage services with high performance and high scalability. In this paper, we first introduce an energy-aware framework for task scheduling and resource scheduling in virtual clusters by creating a number of clusters based on the workload. While virtual machine migration is critical for load balancing, consolidation and server maintenance in virtualized datacenters, it can also increase security risks. Alternatively one should encrypt the migration traffic, while eliminating the need for dedicated control networks, but provide data security and mutual authentication. Currently a few techniques have been proposed to secure the virtual machine migration process. This research paper helps in securing the data without affecting the original data and protecting the data. The architecture proposed in this paper helps in providing an automated intelligent system that monitors for overload or underload and decides when live migration has to take place. Once the VM is selected, encryption is done using a suitable security algorithm and hence the data security, mutual authentication, confidentiality and integrity is achieved. It has been observed that the use of AES reduces the cost and time to encrypt the data and hence we use this efficient algorithm to secure our data. Due to the use of automated monitoring and use of efficient algorithms for clustering and encryption, the total cost and time for the entire process has been reduced and a comparative performance analysis is also demonstrated in this paper.