  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.
