Future cloud systems will become increasingly complicated and highly heterogeneous. It is paramount to develop new techniques that can achieve high performance and low energy consumption in future cloud systems. However, this is not a trivial task because the dynamic nature of system status and user workloads requires that the system must be able to trade off performance and energy efficiency at real time. In this paper, we propose B-MAPS, a self-adaptive resource scheduling framework, which has the potential to improve the performance and energy-efficiency of multi-core or many-core based heterogeneous cloud systems.
['Joal Wood', 'Brian Romoser', 'Ivan Zecena', 'Ziliang Zong']
B-MAPS: a self-adaptive resource scheduling framework for heterogeneous cloud systems