Non-Invasive Virtual Machine Memory Performance Bottleneck Detection

• Main Authors: Tsai, Menq-Ru, 蔡孟儒
• Other Authors: Wu, Yu-Sung
• Format: Others
• Language: en_US
• Published: 2013
• Online Access: http://ndltd.ncl.edu.tw/handle/27776957569780506161

碩士 === 國立交通大學 === 資訊科學與工程研究所 === 102 === Virtualization technology has been widely adapted in cloud environment. In a virtualized environment, some hardware resources such as processors and network bandwidth can be directly shared across virtual machines (VMs), but the memory resource is statically bound to a VM and cannot be shared. On the other hand, a lot of applications are memory-intensive. Efficient utilization of memory resource is a key issue in the use of virtualization technology in cloud environment. In this research, we present NIMBLE, a novel system to detect memory performance bottleneck for VMs in a cloud datacenter. NIMBLE monitors the paging activities of VMs to detect memory performance bottleneck. It will estimate the amount of additional memory needed for removing memory performance bottleneck. NIMBLE can also predict the reduction of the VM execution time due to the additional memory size. The experimental results indicate that the maximum runtime overhead of NIMBLE is about 1.1% on average. For NIMBLE to be applicable in a wide-range of cloud environments, we design it to be non-invasive. NIMBLE does not require modification or manual access to the guest systems is mostly agnostic to guest operating system type.