Hwanju Kim

Task-aware virtual machine scheduling for I/O performance.

The use of virtualization is progressively accommodating diverse and unpredictable workloads as being adopted in virtual desktop and cloud computing environments. Since a virtual machine monitor lacks knowledge of each virtual machine, the unpredictableness of workloads makes resource allocation difficult. Particularly, virtual machine scheduling has a critical impact on I/O performance in cases where the virtual machine monitor is agnostic about the internal workloads of virtual machines. This paper presents a task-aware virtual machine scheduling mechanism based on inference techniques using gray-box knowledge. The proposed mechanism infers the I/O-boundness of guest-level tasks and correlates incoming events with I/O-bound tasks. With this information, we introduce partial boosting, which is a priority boosting mechanism with task-level granularity, so that an I/O-bound task is selectively scheduled to handle its incoming events promptly. Our technique focuses on improving the performance of I/O-bound tasks within heterogeneous workloads by lightweight mechanisms with complete CPU fairness among virtual machines. All implementation is confined to the virtualization layer based on the Xen virtual machine monitor and the credit scheduler. We evaluate our prototype in terms of I/O performance and CPU fairness over synthetic mixed workloads and realistic applications.

Guest-Aware Priority-Based Virtual Machine Scheduling for Highly Consolidated Server

The use of virtualization is rapidly expanding from server consolidation to various computing systems including PC, multimedia set-top box and gaming console. However, different from the server environment, timeliness response for the external input is an essential property for the user-interactive applications. To provide timeliness scheduling of virtual machine this paper presents a priority-based scheduling scheme for virtual machine monitors. The suggested scheduling scheme selects the next task to be scheduled based on the task priorities and the I/O usage stats of the virtual machines. The suggested algorithm was implemented and evaluated on Xen virtual machine monitor. The results showed that the average response time to I/O events is improved by 5~22% for highly consolidated environment.

XHive: Efficient Cooperative Caching for Virtual Machines

Since a virtual machine independently uses its own caching policy, redundant disk operations exacerbate the I/O virtualization overhead when virtual machines access large amounts of data on shared storage. This paper presents XHive, an efficient cooperative caching system that is implemented at the virtualization layer, for consolidated environments. Our proposed scheme globally manages buffer caches of consolidated virtual machines in order to accommodate a shared working set in machine memory. A singlet, which is a block cached solely by a virtual machine, is preferentially given more chances to be cached in machine memory by XHive, when it is evicted by a guest operating system. For efficient use of limited memory, singlets are cached in memory that is collaboratively donated from idle memory of virtual machines. Our evaluation shows that XHive significantly reduces disk I/O operations for shared working sets, thereby achieving high read performance and scalability. Improved scalability enables a high degree of workload consolidation with respect to virtual machines that have shared working sets.

Demand-based coordinated scheduling for SMP VMs

As processor architectures have been enhancing their computing capacity by increasing core counts, independent workloads can be consolidated on a single node for the sake of high resource efficiency in data centers. With the prevalence of virtualization technology, each individual workload can be hosted on a virtual machine for strong isolation between co-located workloads. Along with this trend, hosted applications have increasingly been multithreaded to take advantage of improved hardware parallelism. Although the performance of many multithreaded applications highly depends on communication (or synchronization) latency, existing schemes of virtual machine scheduling do not explicitly coordinate virtual CPUs based on their communication behaviors. This paper presents a demand-based coordinated scheduling scheme for consolidated virtual machines that host multithreaded workloads. To this end, we propose communication-driven scheduling that controls time-sharing in response to inter-processor interrupts (IPIs) between virtual CPUs. On the basis of in-depth analysis on the relationship between IPI communications and coordination demands, we devise IPI-driven coscheduling and delayed preemption schemes, which effectively reduce synchronization latency and unnecessary CPU consumption. In addition, we introduce a load-conscious CPU allocation policy in order to address load imbalance in heterogeneously consolidated environments. The proposed schemes are evaluated with respect to various scenarios of mixed workloads using the PARSEC multithreaded applications. In the evaluation, our scheme improves the overall performance of consolidated workloads, especially communication-intensive applications, by reducing inefficient synchronization latency.

SSD-HDD-hybrid virtual disk in consolidated environments

With the prevalence of multi-core processors and cloud computing, the server consolidation using virtualization has increasingly expanded its territory, and the degree of consolidation has also become higher. As a large number of virtual machines individually require their own disks, the storage capacity of a data center could be exceeded. To address this problem, copy-on-write storage systems allow virtual machines to initially share a template disk image. This paper proposes a hybrid copy-on-write storage system that combines solid-state disks and hard disk drives for consolidated environments. In order to take advantage of both devices, the proposed scheme places a read-only template disk image on a solid-state disk, while write operations are isolated to the hard disk drive. In this hybrid architecture, the disk I/O performance benefits from the fast read access of the solid-state disk, especially for random reads, precluding write operations from the degrading flash memory performance. We show that the hybrid virtual disk, in terms of performance and cost, is more effective than the pure copy-on-write disks for a highly consolidated system.

Transparently bridging semantic gap in CPU management for virtualized environments

Consolidated environments are progressively accommodating diverse and unpredictable workloads in conjunction with virtual desktop infrastructure and cloud computing. Unpredictable workloads, however, aggravate the semantic gap between the virtual machine monitor and guest operating systems, leading to inefficient resource management. In particular, CPU management for virtual machines has a critical impact on I/O performance in cases where the virtual machine monitor is agnostic about the internal workloads of each virtual machine. This paper presents virtual machine scheduling techniques for transparently bridging the semantic gap that is a result of consolidated workloads. To enable us to achieve this goal, we ensure that the virtual machine monitor is aware of task-level I/O-boundedness inside a virtual machine using inference techniques, thereby improving I/O performance without compromising CPU fairness. In addition, we address performance anomalies arising from the indirect use of I/O devices via a driver virtual machine at the scheduling level. The proposed techniques are implemented on the Xen virtual machine monitor and evaluated with micro-benchmarks and real workloads on Linux and Windows guest operating systems.

Transparent Fault Tolerance of Device Drivers for Virtual Machines

In a consolidated server system using virtualization, physical device accesses from guest virtual machines (VMs) need to be coordinated. In this environment, a separate driver VM is usually assigned to this task to enhance reliability and to reuse existing device drivers. This driver VM needs to be highly reliable, since it handles all the I/O requests. This paper describes a mechanism to detect and recover the driver VM from faults to enhance the reliability of the whole system. The proposed mechanism is transparent in that guest VMs cannot recognize the fault and the driver VM can recover and continue its I/O operations. Our mechanism provides a progress monitoring-based fault detection that is isolated from fault contamination with low monitoring overhead. When a fault occurs, the system recovers by switching the faulted driver VM to another one. The recovery is performed without service disconnection or data loss and with negligible delay by fully exploiting the I/O structure of the virtualized system.

Improving the startup time of digital TV

Digital TV was introduced with promises for higher quality displays and converging Internet services which require more computing power and complex software systems. Such complexity entails a prolonged startup time that is similar to booting a computer system. In this paper, we propose two approaches to reduce the startup time of digital TV. Based on the suspend-resume technique employed in many commodity operating systems, our mechanisms replace the cold startup process of digital TV with the resuming from a suspend image. We also analyze the bottlenecks in the startup process and suggest hardware supports to improve the startup time. The proposed approaches reduce the startup time of digital TV by about 50%.

An event-driven power management scheme for mobile consumer electronics

Dynamic processor power management based on periodic monitoring of processor load is being widely used to enhance battery life of mobile consumer electronics. The existing power management schemes, however, often lead to poor user-perceived responsiveness, which is a crucial factor for the quality of user experiences, by making inadequate or delayed decisions on the processor performance level. This paper presents a novel event-driven scheme of the processor power management to guarantee high responsiveness while minimizing ineffective energy consumption. The proposed scheme exploits the characteristic of an interactive event, which is triggered by a user input instead of a periodic timer interrupt. The prototype of the proposed event-driven scheme is implemented for an application launch event as an example. In order to quantify user-perceived responsiveness and energy consumption simultaneously, this paper introduces a latency measurement benchmark program. In the evaluation with the benchmark, the proposed power management scheme showed comparable responsiveness with higher energy savings up to 20 % than the existing dynamic schemes when the interactive workload is mixed with a CPU-intensive background task.

Optimizing the startup time of embedded systems: a case study of digital TV

The demand for fast startup is mostly motivated by embedded systems, especially for home appliances such as digital TV. Though a new storage device such as a flash memory may help reduce the startup time, its applicability is limited to a small size application, which is not the case for recent media processing software consisting of millions lines of code. This paper proposes novel approaches to reduce the startup time of large embedded systems. The startup latency of a commercial digital TV is analyzed in order to marshal resource initialization and to warm up the buffer cache. Based on the analysis we propose a better initialization order and determine when data should be prefetched to the buffer cache in order to reduce the startup time, and which data. Our measurements show that our schemes reduce the total startup time by 35%.