  Cloud computing has become a critical infrastructure for modern society, like
electric power grids and roads. As the backbone of the modern economy, it
offers subscription-based computing services anytime, anywhere, on a
pay-as-you-go basis. Its use is growing exponentially with the continued
development of new classes of applications driven by a huge number of emerging
networked devices. However, the success of Cloud computing has created a new
global energy challenge, as it comes at the cost of vast energy usage.
Currently, data centres hosting Cloud services world-wide consume more energy
than most countries. Globally, by 2025, they are projected to consume 20% of
global electricity and emit up to 5.5% of the world's carbon emissions. In
addition, a significant part of the energy consumed is transformed into heat
which leads to operational problems, including a reduction in system
reliability and the life expectancy of devices, and escalation in cooling
requirements. Therefore, for future generations of Cloud computing to address
the environmental and operational consequences of such significant energy
usage, they must become energy-efficient and environmentally sustainable while
continuing to deliver high-quality services.
  In this paper, we propose a vision for learning-centric approach for the
integrated management of new generation Cloud computing environments to reduce
their energy consumption and carbon footprint while delivering service quality
guarantees. In this paper, we identify the dimensions and key issues of
integrated resource management and our envisioned approaches to address them.
We present a conceptual architecture for energy-efficient new generation Clouds
and early results on the integrated management of resources and workloads that
evidence its potential benefits towards energy efficiency and sustainability.
