Efficient VM Memory Balancing Algorithm Design and Implementation

Abstract

A common strategy to manage memory resources of VMs under changing workloads is Dynamic VM memory management via hotplug. However, in order to estimate the VM working set size, most researchers are utilizing approaches that rely on kernel instrumentation but this most often results to high runtime overhead. This will result in system administrate to exercise a tradeoff between the estimate accuracy and system performance. The novelty of this work is to present a light weight accurate and transparent prediction algorithm for re-balancing memory resources among VMs. Experiments result attained on Dacapo and SPECjvm2008 from renowned benchmarks shows that with only 4% performance overhead our proposed method is capable of accurately adjusting virtual machine memory size on its real time requirements, and improve application performance in the virtual machine more than 10% better when virtual machine has 2 CPUs and 20% better when it has 4 CPUs. In case there is no free memory available our proposed method will try first to use host's free memory but if there is no free memory, it starts memory over-commitment for a fixed duration to help the requested VM complete its task.