A Real-Time Scheduling Framework Based on Multi-core Dynamic Partitioning in Virtualized Environment

Abstract

With the prevalence of virtualization and cloud computing, many real-time applications are running in virtualized cloud environments. However, their performance cannot be guaranteed because current hypervisors' CPU schedulers aim to share CPU resources fairly and improve system throughput. They do not consider real-time constraints of these applications, which result in frequent deadline misses. In this paper, we present a real-time scheduling framework in virtualized environment. In the framework, we propose a mechanism called multi-core dynamic partitioning to divide physical CPUs (PCPUs) into two pools dynamically according to the scheduling parameters of real-time virtual machines (RT-VMs). We apply different schedulers to these pools to schedule RT-VMs and non-RT-VMs respectively. Besides, we design a global earliest deadline first (vGEDF) scheduler to schedule RT-VMs. We implement a prototype in the Xen hypervisor and conduct experiments to verify its effectiveness.

Biobjective VoIP Service Management in Cloud Infrastructure

“…The author develops analytical and simulation models to evaluate the performance of VoIP services in terms of the average throughput and the signaling overhead according to the scheduling schemes. Lee et al (2006) [15] present a real-time scheduling framework in virtualized environment that considers real-time constraints of applications. The authors propose a mechanism called multicore dynamic partitioning to divide physical CPUs into two pools dynamically according to the scheduling parameters of VMs.…”