Memory Reclamation and Compression Using Accurate Working Set Size Estimation

Minimizing the total amount of physical memory consumption of the virtual machines (VM) concurrently running on a physical server is a key to improving a hyper visor´s consolidation ratio, defined as the maximum number of VMs that can run on a physical server without performance degradation. This paper describes the design, implementation and evaluation of a memory resource manager called Gatun that constantly measures the working set size of each running VM, and exploits this information to make the best of the available physical memory on a physical server. The per-VM working set size information allows Gatun to reclaim only unused physical memory from each running VM without negatively affecting its performance, and to compress the right subset of memory pages for each VM to reduce its memory pressure to the maximal extent possible. Compared with a state-of-the-art commercial hyper visor, Gatun is able to make noticeably more efficient utilization of a virtualized server´s physical memory because of its ability to capture and leverage the per-VM working set size information.