Numerous systems have been designed which use virtualization to subdivide the ample resources of a modern computer. Some require specialized hardware, or cannot support commodity operating systems. Some target 100 % binary compatibility at the expense of performance. Others sacrifice security or functionality for speed. Few offer resource isolation or performance guarantees; most provide only best-effort provisioning, risking denial of service. This paper presents Xen, an x86 virtual machine monitor which allows multiple commodity operating systems to share conventional hardware in a safe and resource managed fashion, but without sacrificing either performance or functionality. This is achieved by providing an idealized virtual machine abstraction to which operating systems such as Linux, BSD and Windows XP, can be ported with minimal effort. Our design is targeted at hosting up to 100 virtual machine instances simultaneously on a modern server. The virtualization approach taken by Xen is extremely efficient: we allow operating systems such as Linux and Windows XP to be hosted simultaneously for a negligible performance overhead — at most a few percent compared with the unvirtualized case. We considerably outperform competing commercial and freely available solutions in a range of microbenchmarks and system-wide tests.

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as utility: computation jobs can be scheduled on-demand in Grid hosts based on available computation capacity. In this paper, we study another emerging usage of Grid utility: the hosting of application services. Different from a computation job, an application service such as e-Laboratory or on-line shopping has longer lifetime, and performs multiple jobs requested by its clients. A service Hosting Utility Platform (HUP) is formed by a set of servers in the Grid, and multiple application services will be hosted on the HUP. We present the design and implementation of SODA, a Service-On-Demand Architecture that enables on-demand creation of application services on a HUP. With SODA, an application service will be created in the form of a set of virtual service nodes; each node is a virtual machine which is physically a `slice' of a real host in the HUP. SODA involves both OS and middleware level techniques, and has the following salient capabilities: (1) on-demand service priming: the image of an application service as well as the OS on which it runs will be created on-demand and bootstrapped automatically; (2) better service isolation: services sharing the same HUP host are isolated with respect to administration, faults, attacks, and resources; (3) integrated service request management: for each service, a service switch will be created to direct client requests to appropriate virtual service nodes. Moreover, the application service provider can replace the default request switching policy with a service-specific policy.

We present NPS, a novel non-intrusive web prefetching system that (1) utilizes only spare resources to avoid interference between prefetch and demand requests at the server as well as in the network , and (2) is deployable without any modifications to servers, browsers, network or the HTTP protocol. NPS's self-tuning architecture eliminates the need for traditional "thresholds" or magic numbers typically used to limit interference caused by prefetching, thereby allowing applications to improve bene ts and reduce the risk of aggressive prefetching.

Although computer programs explicitly represent data values, time values are usually implicit. This makes it difficult to analyze and debug real-time programs whose correctness depends partially on the time at which results are computed. This paper shows how to use Hourglass, an instrumented, synthetic real-time application, to make inferences about what is happening on a computer at millisecond and microsecond granularities. These inferences are possible because Hourglass records a very fine-grained map of when each of its threads runs, and because Hourglass supports a variety of thread execution models that model the properties and requirements of non-synthetic real-time applications. We conclude that between measurements and inferences, surprisingly detailed knowledge about scheduling behavior can be obtained without modifying, or even explicitly interacting with, the operating system kernel.

The performance and capacity of commodity computer systems have improved drastically in recent years. However, these systems still lack the support for real-time data access, which is required by an increasing number of emerging applications. In this paper we first present several important storagebound real-time applications and classify their Quality of Service (QoS) requirements. We then survey the representative work on disk management in the areas of IO scheduling, admission control, and data placement. Finally, we present our approach for providing disk QoS in commodity systems and present key empirical results from the micro-benchmark-based evaluation of our QoS-enhanced Linux kernel.

... important computing platforms, which require low energy consumption while meeting the resource demands of a dynamic application workload. Most proposed dynamic voltage scaling (DVS) algorithms, targeting either best-effort or hard real-time systems, however, cannot be directly applied to such open mobile systems. This paper presents a framework to integrate DVS into soft real-time (SRT) scheduling for open mobile systems, achieving energy saving of DVS while preserving resource guarantees of SRT scheduling. The integrated framework makes three major contributions. First, multimedia applications reserve resource based on their average resource usage, without the knowledge of worst-case execution time, which is difficult to estimate in an open mobile environment. Second, the SRT scheduling ensures the correctness of reservation admission and enforcement in a variable speed context. Finally, the DVS manager reduces the processor energy consumption by utilizing the unallocated resource, reclaiming the allocated but unused resource, or avoiding the unused resource. Our extensive simulation results demonstrate that our framework is able to save 4% to 32% energy while slightly affecting application performance.

Managed hosting and enterprise wide resource consolidation trends are increasingly leading to sharing of storage resources across multiple classes, corresponding to different applications/customers, each with a different Quality of Service (QoS) requirement. To enable a storage system to meet diverse QoS requirements, we present two algorithms for dynamically allocating cache space among multiple _classes of workloads. Our algorithms dynamically adapt the cache space allocated to each class depending upon the observed response time, the temporal locality of reference, and the arrival pattern for each class. Using trace driven simulations collected from large storage system installations, we experimentally demonstrate the following properties of CacheCOW.

This paper presents the design, implementation, and evaluation of a simple programming language for expressing scheduling policies for transmission of multiple objects across a shared network connection. A key design component of our language is the ability to express constraints among the objects to be transmitted. A policy can make ordering constraints such as “all text objects are transmitted before any image objects ” or a policy might express rules on the the relative bandwidth allocations across objects of different types or it can reserve certain amount of bandwidth for an object. Because it is possible to express contradictory constraints, our system finds suitable approximate solutions when no precise solution is available. 1

This paper presents the architecture and implementation of XTREAM, a high-performance streaming multimedia system. XTREAM is supported by its three core components: IO Scheduler, Request Handler, and Admission Controller. Via extensive experiments, we show that, thanks to these core components, XTREAM can achieve low response time as well as high throughput and high-quality service to simultaneous clients.