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

Anh Quan Nguyen (1) , Pascal Bouvry (1) , El-Ghazali Talbi (2, 3)

1 University of Luxembourg [Luxembourg]
2 DOLPHIN - Parallel Cooperative Multi-criteria Optimization
3 CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189

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.

Domaines: Recherche opérationnelle [math.OC]

Anh Quan Nguyen, Pascal Bouvry, El-Ghazali Talbi. A new model for VMMP dealing with execution time uncertainty in a multi-clouds system. CloudNet‘2015 4th IEEE Int. Conf. on Cloud Networking, Oct 2015, Naigara Falls, Canada. pp.165-170, ⟨10.1109/CloudNet.2015.7335300⟩. ⟨hal-01249482⟩