An Intent-driven DaaS Management Framework to Enhance User Quality of Experience

Abstract

Desktop as a Service (DaaS) has become widely used by enterprises. In 2020, the use of DaaS increased dramatically due to the demand to work remotely from home during the COVID-19 pandemic. The DaaS market is expected to continue growing rapidly [ 1 ]. The quality of experience (QoE) of a DaaS service has been one of the main factors to enhance DaaS user satisfaction. To ensure user QoE, the amount of cloud computation resources for a DaaS service must be appropriately designed. We propose an Intent-driven DaaS Management (IDM) framework to autonomously determine the cloud-resource-amount configurations for a given DaaS QoE requirement. IDM enables autonomous resource design by abstracting the knowledge about the dependency between DaaS workload, resource configuration, and performance from previous DaaS performance log data. To ensure the IDM framework's applicability to actual DaaS services, we analyzed five main challenges in applying the IDM framework to actual DaaS services: identifying the resource-design objective, quantifying DaaS QoE, addressing low log data availability, designing performance-inference models, and addressing low resource variations in the log data. We addressed these challenges through detailed designing of IDM modules. The effectiveness of the IDM framework was assessed from the aspects of DaaS performance-inference precision, DaaS resource design, and time and human-resource cost reduction.