As the role of virtualization technology becomes more prevalent, the range of applications deployed in virtualized systems is steadily growing. This increasingly includes applications with soft real-time requirements that benefit from low and predictable latency, even when co-located with other virtualized hosts with arbitrary traffic patterns. In this paper, we examine the policies and mechanisms affecting communication latency between virtual machines based on the Xen platform, and identify limitations that can result in long or unpredictable network stack latency for virtual machines deployed on this platform. To address these limitations, we propose and implementVATC, aVirtualization-Aware Traffic Controlframework that supports differentiation (via rate-limited prioritization) of outbound and inbound network traffic from co-located virtualized hosts. Results of our experiments show how and why VATC can offer predictable (soft) latency guarantees to applications running on virtualized hosts with minimum overhead.

Clouds have become appealing platforms for not only general-purpose applications, but also real-time ones. However, current clouds cannot provide real-time performance to virtual machines (VMs). We observe the demand and the advantage of co-hosting real-time (RT) VMs with non-real-time (regular) VMs in a same cloud. RT VMs can benefit from the easily deployed, elastic resource provisioning provided by the cloud, while regular VMs effectively utilize remaining resources without affecting the performance of RT VMs through proper resource management at both the cloud and the hyper visor levels. This paper presents RT-Open Stack, a cloud CPU resource management system for co-hosting real-time and regular VMs. RT-Open Stack entails three main contributions: (1) integration of a real-time hyper visor (RT-Xen) and a cloud management system (Open Stack) through a real-time resource interface, (2) a real-time VM scheduler to allow regular VMs to share hosts with RT VMs without interfering the real-time performance of RT VMs, and (3) a VM-to-host mapping strategy that provisions real-time performance to RT VMs while allowing effective resource sharing with regular VMs. Experimental results demonstrate that RT-Open Stack can effectively improve the real-time performance of RT VMs while allowing regular VMs to fully utilize the remaining CPU resources.

As virtualization technology becomes ever more capable, large-scale distributed applications are increasingly deployed in virtualized environments such as data centers and computational clouds. Many large-scale applications have soft real-time requirements and benefit from low and predictable latency, even in the presence of diverse traffic patterns between virtualized hosts. In this paper, we examine the policies and mechanisms affecting communication latency between virtual machines based on the Xen platform, and identify limitations that could result in long or unpredictable network traffic latencies. To address these limitations, we propose VATC, aVirtualization-Aware Traffic Controlframework for prioritizing network traffic in virtualized hosts. Results of our experiments show how and why VATC can improve predictability and reduce delay for latency sensitive applications, while introducing limited overhead.

Recent years have witnessed two major trends in the development of complex real-time embedded systems. First, to reduce cost and enhance flexibility, multiple systems are sharing common computing platforms via virtualization technology, instead of being deployed separately on physically isolated hosts. Second, multicore processors are increasingly being used in real-time systems. The integration of real-time systems as virtual machines (VMs) atop common multicore platforms raises significant new research challenges in meeting the real-time performance requirements of multiple systems. This paper advances the state of the art in real-time virtualization by designing and implementing RT-Xen 2.0, a new real-time multicore VM scheduling framework in the popular Xen virtual machine monitor (VMM). RT-Xen 2.0 realizes a suite of real-time VM scheduling policies spanning the design space. We implement both global and partitioned VM schedulers; each scheduler can be configured to support dynamic or static priorities and to run VMs as periodic or deferrable servers. We present a comprehensive experimental evaluation that provides important insights into real-time scheduling on virtualized multicore platforms: (1) both global and partitioned VM scheduling can be implemented in the VMM at moderate overhead; (2) at the VMM level, while compositional scheduling theory shows partitioned EDF (pEDF) is better than global EDF (gEDF) in providing schedulability guarantees, in our experiments their performance is reversed in terms of the fraction of workloads that meet their deadlines on virtualized multi-core platforms; (3) at the guest OS level, pEDF requests a smaller total VCPU bandwidth than gEDF based on compositional scheduling analysis, and therefore using pEDF at the guest OS level leads to more schedulable workloads in our experiments; (4) a combination of pEDF in the guest OS and gEDF in the VMM -- configured with deferrable server -- leads to the highest fraction of schedulable task sets compared to other real-time VM scheduling policies; and (5) on a platform with a shared last-level cache, the benefits of global scheduling outweigh the cache penalty incurred by VM migration.

As computer hardware becomes increasingly powerful, there is an ongoing trend towards integrating QoS-critical systems as virtual machines (domains) on a common, virtualized computing platform. Given the lower latency of local inter-domain communication (IDC) on the same host (compared to inter-host communication), system administrators may preferably colocate domains so that they can communicate locally. When multiple IDC flows contend on the same host, it is important to properly prioritize IDC flows among domains to meet their respective QoS requirements. This paper examines the limitations of IDC in Xen, a widely used open-source virtual machine monitor (VMM) that recently has been extended to support real-time domain scheduling. We find that both the VMM scheduler and the manager domain can significantly impact IDC QoS under different conditions, and show that improving the VMM scheduler alone cannot effectively prevent priority inversion for local IDC. To address those limitations, we present RTCA, a Real-Time Communication Architecture within the manager domain in Xen, along with experimental results that demonstrate the latency of high-priority IDC can be improved dramatically from ms to μs by a combination of the RTCA and a real-time VMM scheduler.

Multicore processors are becoming ubiquitous, and it is becoming increasingly common to run multiple real-time systems on a shared multicore platform. While this trend helps to reduce cost and to increase performance, it also makes it more challenging to achieve timing guarantees and functional isolation. One approach to achieving functional isolation is to use virtualization. However, virtualization also introduces many challenges to the multicore timing analysis, for instance, the overhead due to cache misses becomes harder to predict, since it depends not only on the direct interference between tasks but also on the indirect interference between virtual processors and the tasks executing on them. In this paper, we present a cache-aware compositional analysis technique that can be used to ensure timing guarantees of components scheduled on a multicore virtualization platform. Our technique improves on previous multicore compositional analyses by accounting for the cache-related overhead in the components' interfaces, and it addresses the new virtualization-specific challenges in the overhead analysis. To demonstrate the utility of our technique, we report results from an extensive evaluation based on randomly generated workloads.

We present a co-designed scheduling framework and platform architecture that together support compositional scheduling of real-time systems. The architecture is built on the Xen virtualization platform, and relies on compositional scheduling theory that uses periodic resource models as component interfaces. We implement resource models as periodic servers and consider enhancements to periodic server design that significantly improve response times of tasks and resource utilization in the system while preserving theoretical schedulability results. We present an extensive evaluation of our implementation using workloads from an avionics case study as well as synthetic ones.

As system integration becomes an increasingly important challenge for complex real-time systems, there has been a significant demand for supporting real-time systems in virtualized environments. This paper presents RT-Xen, the first real-time hypervisor scheduling framework for Xen, the most widely used open-source virtual machine monitor (VMM). RT-Xen bridges the gap between real-time scheduling theory and Xen, whose wide-spread adoption makes it an attractive platform for integrating a broad range of real-time and embedded systems. Moreover, RT-Xen provides an open-source platform for researchers and integrators to develop and evaluate real-time scheduling techniques, which to date have been studied predominantly via analysis and simulations.