This paper focuses on the problemof workload placement in an InterCloud with the view of minimizing the carbon footprint of such a computing environment. In order to reduce the ecological impact of the data center Greenhouse Gas (GhG) emissions, this paper addresses the problemas a whole, by proposing a global mathematical formulation, based on the joint optimization of the Virtual Machine (VM) placement and their related traffics, along with a workload consolidation method and a cooling maximization technique that considers the dynamic behavior of the cooling fans. As the Virtual Machine Placement Problem(VMPP) is classified as an NP-hard problem, with the addition of the traffic embedding, the problembecomes more complex and stays NP-hard. Therefore, we propose a hybrid approach, for solving such problem and find good feasible solutions in a polynomial time. The results obtained from comparing with the exact method and other reference approaches help in assessing the efficiency of the proposed algorithm, as the carbon footprint costs are relatively close to the lower bound, with an average gap of about 3 percent, and found within a reasonable amount of time.

In this paper, we address the problem of virtual machine (VM) placement in an InterCloud with regard to the reduction of carbon footprint in such computing environment. In order to minimize the data center Greenhouse Gas (GhG) emissions, this paper proposes a new mathematical formulation, where the placement approach is stated as a mixed integer programming problem which aims at minimizing the overall carbon footprint of the InterCloud. The proposed formulation presents an accurate carbon footprint evaluation based on joint optimization techniques, such as workload consolidation and cooling efficiency maximization, while considering the greenness of the data centers and the dynamic behavior of the IT equipment cooling fans. Simulation results showed that our model leads to optimal configurations with minimal carbon footprint in the InterCloud environment.

In this paper, we address the problem of virtual machine VM placement in an InterCloud with regard to the reduction of the environmental impact of such environment. We propose a mathematical formulation based on a smart workload consolidation method and a cooling maximisation technique that considers the dynamic behaviour of the cooling fans. As the virtual machine placement problem VMPP is classified as an NP-hard problem, we propose an implementation of the iterated local search ILS algorithm, ILS_CBF, in order to find good solutions in a reasonable time. Computational results allow to identify the parameters that reduce the carbon footprint costs. The comparison of the proposed heuristic with the exact method and other algorithms demonstrate that the obtained costs are relatively close to the lower bounds, ranging from 0% to a maximum distance less than 2.6%, and allow a good tradeoff between the quality of the solution and the computational time.

Cloud Computing raises major challenges among which virtual machine (VM) placement is considered as one of the crucial problems. From the cloud provider's perspective, this process often consists in choosing the best convenient physical hosts with regards to energy efficiency, resource utilization and revenues maximization. However, to secure the loyalty of their clients, cloud providers should also consider the applications performance. In this paper, we propose a VM placement approach tackling the applications performance concern, in an intercloud environment. We state the VM placement as a mixed integer programming problem which aims to maximize a global utility function considering VM bandwidth requirements and network latencies. The proposed approach is evaluated with respect to demands and latencies variations; and through numerical results, we have demonstrated that our model allows us to compute the optimal configuration, in terms of high bandwidth availability and low network latency in the overall intercloud environment.