A new model for VMMP dealing with execution time uncertainty in a multi-clouds system

The Virtual Machine Mapping Problem (VMMP) arise by the development of cloud computing. Focusing on a novel approach for cloud broker model in multi-clouds environment, we present a new model to deal with VMMP that takes into account the uncertainty of the VM execution time, hence allowing to obtain robust assignment solutions. The uncertainty of the VM execution time is modeled by (i) relying on a truncated normal distribution for constructing mapping instances, and (ii) by using the expected value of the generating truncated normal distribution. The proposed methods, for the optimization for the VMMP, are conducted on the Grid5000 in order to bring a detailed results comparison between the obtained results from the experimental study with different benchmarks.