An energy-aware multi-start local search heuristic for scheduling VMs on the OpenNebula cloud distribution

Reducing energy consumption is an increasingly important issue in cloud computing, more specifically when dealing with a cloud distribution dispatched over a huge number of machines. Minimizing energy consumption can significantly reduce the amount of energy bills, and the greenhouse gas emissions. Therefore, many researches are carried out to develop new methods in order to consume less energy. In this paper, we present an Energy-aware Multi-start Local Search algorithm for an OpenNebula based Cloud (EMLS-ONC) that optimizes the energy consumption of an OpenNebula managed geographically distributed cloud computing infrastructure. The results of our EMLS-ONC scheduler are compared to the results obtained by the default scheduler of OpenNebula. The two approaches have been experimented using different (VMs) arrival scenarios and different hardware infrastructures. The results show that EMLS-ONC outperforms the previous OpenNebula's scheduler by a significant margin in terms of energy consumption. In addition, EMLS-ONC is also proved to schedule more applications.