Title :
A Virtual Machine Resource Management Method with Millisecond Precision
Author :
Yu Kaneko;Toshio Ito;Tomonori Maegawa
fDate :
7/1/2015 12:00:00 AM
Abstract :
There are several research projects ongoing to apply cloud computing to industrial systems. The main focus of them is real-time performance of virtual machines (VMs) since it is important to guarantee a time-critical feature of industrial systems. However, there is another important issue that how much computing resource (CPU, memory, etc.) should be allocated to each VM which runs processes of an industrial system. In this paper, we propose a resource management method which manages VM resources with millisecond precision. In the proposed method, resource usage is measured and predicted, considering several microseconds allocation delay of Xen. Our experimental results show that the proposed method can guarantee 99% operation timing with higher CPU utilization in comparison with conventional resource management methods.
Keywords :
"Resource management","Delays","Real-time systems","Cloud computing","Crawlers","Conferences"
Conference_Titel :
Autonomic Computing (ICAC), 2015 IEEE International Conference on
DOI :
10.1109/ICAC.2015.24