A Policy-Based System for Dynamic Scaling of Virtual Machine Memory Reservations

Abstract

To maximize the effectiveness of modern virtualization systems, resources must be allocated fairly and efficiently amongst virtual machines (VMs). However, current policies for allocating memory are relatively static. As a result, system-wide memory utilization is often sub-optimal, leading to unnecessary paging and performance degradation. To better utilize the large-scale memory resources of modern machines, the virtualization system must allow virtual machines to expand beyond their initial memory reservations, while still fairly supporting concurrent virtual machines. This paper presents a system for dynamically allocating memory amongst virtual machines at runtime, as well as an evaluation of six allocation policies implemented within the system. The system allows guest VMs to expand and contract according to their changing demands by uniquely improving and integrating mechanisms such as memory ballooning, memory hotplug, and hypervisor paging. Furthermore, the system provides fairness by guaranteeing each guest a minimum reservation, charging for rentals beyond this minimum, and enforcing timely reclamation of memory.

Publication
Proceedings of the ACM Symposium on Cloud Computing (SOCC)