Energy-aware joint management of networks and Cloud infrastructures
Fueled by the massive adoption of Cloud services, the CO2 emissions of the Information and Communication Technology (ICT) systems are rapidly increasing. Overall service centers and networks account for 2-4% of global CO2 emissions and it is expected they can reach up to 10% in 5-10 years. Service centers and communication networks have been managed independently so far, but the new generation of Cloud systems can be based on a strict integration of service centers and networking
... . Moreover, geographically-distributed service centers are being widely adopted to keep cloud services close to end users and to guarantee high performance. The geographical distribution of the computing facilities offers many opportunities for optimizing energy consumption and costs by means of a clever distribution of the computational workload exploiting different availability of renewable energy sources, but also different time zones and hourly energy pricing. Energy and cost savings can be pursued by dynamically allocating computing resources to applications at a global level, while communication networks allow to assign flexibly load requests and to move data. Even if in the last years a quite large research effort has been devoted to the energy efficiency of service centers and communication networks, limited work has been done for exploring the opportunities of integrated approaches able to exploit possible synergies between geographically distributed service centers and networks for accessing and interconnecting them. In this paper we propose an optimization framework able to jointly manage the use of brown and green energy in an integrated system and to guarantee quality requirements. We propose an efficient and accurate problem formulation that can be solved for real-size instances in few minutes to optimality. Numerical results, on a set of randomly generated instances and a case study representative of a large Cloud provider, show that the availability of green energy have a big impact on optimal energy management policies and that the contribution of the network is far from being negligible.