Multidimensional Resource Allocation in Practice

One of the main motivations for the shift to the Cloud (and the more recent shift of telco operators into NFV) is cost reduction due to high utilization of infrastructure resources. However, achieving high utilization in practical scenarios is complex since the term "resources" covers different orthogonal aspects, such as server CPU, storage (or disk) usage and network capacity, and the workload characterization varies over time and over different users. In this paper we study the placement of Virtual Machines (VMs) that implement services over the physical infrastructure, trying to understand what makes a placement scheme better than others in the overall utilization of the various resources. We show that the multidimensional case is inherently different from the single dimension case, and develop novel placement heuristics to address the specific challenges. We then show, by extensive evaluation over real data, that operators can significantly improve their resource utilization by selecting the most appropriate placement policy, according to their system specifications and the deployed services. In particular, two of our new heuristics that dynamically change the placement logic according to the amount of available (unused) resources are shown to perform very well in many practical scenarios.