Cloud computing is a style of computing in which dynamically scalable and other virtualized resources are provided as a service over the Internet. The energy consumption and makespan associated with the resources allocated should be taken into account. This paper proposes an improved clonal selection algorithm based on time cost and energy consumption models in cloud computing environment. We have analyzed the performance of our approach using the CloudSim toolkit. The experimental results show that our approach has immense potential as it offers significant improvement in the aspects of response time and makespan, demonstrates high potential for the improvement in energy efficiency of the data center, and can effectively meet the service level agreement requested by the users.
In REF , authors proposed improved version of clonal selection algorithm (ICSA) which proved to be better in the area of response time and has taken minimal time for task execution.
A novel energy-efficient resource allocation algorithm based on immune clonal optimization for green cloud computing
EURASIP Journal on Wireless Communications and Networking
Computer Science