VMSAGE: A virtual machine scheduling algorithm based on the gravitational effect for green Cloud computing

Abstract

The area of sustainable green smart computing highlights key challenges towards reducing cost and carbon dioxide emissions due to the high-energy consumption of Cloud data centres. Here, we focus on the Cloud virtual machine (VM) scheduling that is usually based on simple algorithms, e.g. VM place

An Algorithm Incarnating Deep Integration of Hardware-Software Energy Regulation Principles for Heterogeneous Green Scheduling

“…Super-scale heterogeneous real-time scheduling needs to reduce energy consumption without affecting performance. This is not only for the low-carbon economy or sustainable human development, but also for the reliability and stability of the system [3][4][5][6] . Many researches turn to virtual management upgrading, using Gaussian process regression method [15] , multidimensional packing mode [16] or integer programming strategy [17] .…”

“…According to the studies, CO2 produced by the industry of information communication technology (ICT), may rise to 14% of the global emissions in 2040 [2] ; and other statistics show that there is a huge waste of energy in data centers, since PUE (Power Usage Effectiveness) of China's data centers is generally greater than 2.2 and that of America's is basically maintained at 1.9, where the closer the PUE value is to 1, the higher the greening degree of a data center. Therefore, no matter for environmental protection or for low-carbon economy, there are imperative requirements on the computing evolution from high performance to high efficiency [3][4][5][6] .…”

Green Computing Approaches - A Survey

“…Gai et al [9] presented an energy-aware mobile cloud computing model that takes advantage of cloudlets to reduce the energy consumption of wireless communications. Xu et al [10] described an energy-efficient algorithm for VM scheduling inspired by physical principles. Zhao-Hui and Qin-Ming [11] proposed a virtual machine scheduling algorithm that deploys VMs on data nodes with the least growth of energy consumption.…”

A Greener Meta-Heuristics Scheduling Algorithm With Energized Optimization Dynamics by Deeper Intelligence Fusion

“…Nowadays, fundamental saving energy or reducing emissions of the wide-area heterogeneous computing, represented by the virtual cloud, is the goal that is far from achieved [1] . In fact, the intelligent decision-making of the scheduling middleware is key, where green scheduling aims for the computing evolution from high performance to high efficiency.…”