Sharing-aware intercloud scheduler for data-intensive jobs

Cloud computing, a new concept refers to a hosted computational environment that can provide elastic computation and storage services for users per demand. This paradigm arises due to the huge growth in applications and data sizes. Consider the fact that many agencies, organizations and departments are responsible for time-critical tasks and these tasks need to be completed as soon as possible. At the same time, these agencies also face IT problems because of the rapid growth of their applications, data and solution sizes. Many experts proposed that cloud computing is a solution to these problems so that each agency can execute its tasks via the cloud and expand their requirements based on each situation. This paper tackles the problem of scheduling data-intensive jobs to virtual machines located in the intercloud paradigm. The results depict the huge improvement in data transfer time and the reduction in jobs execution time. This paper concludes that ignoring the shared data would degrade the global system performance.