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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Xen and the art of virtualization

Cloud computing has recently emerged as a new paradigm for hosting and delivering services over the Internet. Cloud computing is attractive to business owners as it eliminates the requirement for users to plan ahead for provisioning, and allows enterprises to start from the small and increase resources only when there is a rise in service demand. However, despite the fact that cloud computing offers huge opportunities to the IT industry, the development of cloud computing technology is currently at its infancy, with many issues still to be addressed. In this paper, we present a survey of cloud computing, highlighting its key concepts, architectural principles, state-of-the-art implementation as well as research challenges. The aim of this paper is to provide a better understanding of the design challenges of cloud computing and identify important research directions in this increasingly important area.

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Cloud computing: state-of-the-art and research challenges

To be agile and cost effective, data centers should allow dynamic resource allocation across large server pools. In particular, the data center network should enable any server to be assigned to any service. To meet these goals, we present VL2, a practical network architecture that scales to support huge data centers with uniform high capacity between servers, performance isolation between services, and Ethernet layer-2 semantics. VL2 uses (1) flat addressing to allow service instances to be placed anywhere in the network, (2) Valiant Load Balancing to spread traffic uniformly across network paths, and (3) end-system based address resolution to scale to large server pools, without introducing complexity to the network control plane. VL2's design is driven by detailed measurements of traffic and fault data from a large operational cloud service provider. VL2's implementation leverages proven network technologies, already available at low cost in high-speed hardware implementations, to build a scalable and reliable network architecture. As a result, VL2 networks can be deployed today, and we have built a working prototype. We evaluate the merits of the VL2 design using measurement, analysis, and experiments. Our VL2 prototype shuffles 2.7 TB of data among 75 servers in 395 seconds - sustaining a rate that is 94% of the maximum possible.

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VL2: a scalable and flexible data center network

Network Calculus.- Application of Network Calculus to the Internet.- Basic Min-plus and Max-plus Calculus.- Min-plus and Max-plus System Theory.- Optimal Multimedia Smoothing.- FIFO Systems and Aggregate Scheduling.- Adaptive and Packet Scale Rate Guarantees.- Time Varying Shapers.- Systems with Losses.

Network Calculus: A Theory of Deterministic Queuing Systems for the Internet

Multiple applications request data from multiple storage units over a computer network. The data is divided into segments and each segment is distributed randomly on one of several storage units, independent of the storage units on which other segments of the media data are stored. At least one additional copy of each segment also is distributed randomly over the storage units, such that each segment is stored on at least two storage units. This random distribution of multiple copies of segments of data improves both scalability and reliability. When an application requests a selected segment of data, the request is processed by the storage unit with the shortest queue of requests. Random fluctuations in the load applied by multiple applications on multiple storage units are balanced nearly equally over all of the storage units. This combination of techniques results in a system which can transfer multiple, independent high-bandwidth streams of data in a scalable manner in both directions between multiple applications and multiple storage units.

Computer system and process for transferring multiple high bandwidth streams of data between multiple storage units and multiple applications in a scalable and reliable manner

As IP technologies providing both tremendous capacity and the ability to establish dynamic secure associations between endpoints emerge, Virtual Private Networks (VPNs) are going through dramatic growth. The number of endpoints per VPN is growing and the communication pattern between endpoints is becoming increasingly hard to forecast. Consequently, users are demanding dependable, dynamic connectivity between endpoints, with the network expected to accommodate any traffic matrix, as long as the traffic to the endpoints does not overwhelm the rates of the respective ingress and egress links. We propose a new service interface, termed a hose, to provide the appropriate performance abstraction. A hose is characterized by the aggregate traffic to and from one endpoint in the VPN to the set of other endpoints in the VPN, and by an associated performance guarantee.Hoses provide important advantages to a VPN customer: (i) flexibility to send traffic to a set of endpoints without having to specify the detailed traffic matrix, and (ii) reduction in the size of access links through multiplexing gains obtained from the natural aggregation of the flows between endpoints. As compared with the conventional point to point (or customer-pipe) model for managing QoS, hoses provide reduction in the state information a customer must maintain. On the other hand, hoses would appear to increase the complexity of the already difficult problem of resource management to support QoS. To manage network resources in the face of this increased uncertainty, we consider both conventional statistical multiplexing techniques, and a new resizing technique based on online measurements.To study these performance issues, we run trace driven simulations, using traffic derived from AT&T's voice network, and from a large corporate data network. From the customer's perspective, we find that aggregation of traffic at the hose level provides significant multiplexing gains. From the provider's perspective, we find that the statistical multiplexing and resizing techniques deal effectively with uncertainties about the traffic, providing significant gains over the conventional alternative of a mesh of statically sized customer-pipes between endpoints.

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A flexible model for resource management in virtual private networks

We present Start-time Fair Queuing (SFQ) algorithm that is computationally efficient, achieves fairness regardless of variation in a server capacity, and has the smallest fairness measure among all known fair scheduling algorithms. We analyze its throughput, single server delay, and end-to-end delay guarantee for variable rate Fluctuation Constrained (FC) and Exponentially Bounded Fluctuation (EBF) servers. We show that SFQ is better suited than Weighted Fair Queuing for integrated services networks and it is strictly better than Self Clocked Fair Queuing. To support heterogeneous services and multiple protocol families in integrated services networks, we present a hierarchical SFQ scheduler and derive its performance bounds. Our analysis demonstrates that SFQ is suitable for integrated services networks since it: (1) achieves low average as well as maximum delay for low-throughput applications (e.g., interactive audio, telnet, etc.); (2) provides fairness which is desirable for VBR video; (3) provides fairness, regardless of variation in a server capacity, for throughput-intensive, flow-controlled data applications; (4) enables hierarchical link sharing which is desirable for managing heterogeneity; and (5) is computationally efficient.

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Start-time fair queueing: a scheduling algorithm for integrated services packet switching networks

We present a start-time fair queueing (SFQ) algorithm that is computationally efficient and achieves fairness regardless of variation in a server capacity. We analyze its single server and end-to-end deadline guarantee for variable rate fluctuation constrained (FC) and exponentially bounded fluctuation (EBF) servers. To support heterogeneous services and multiple protocol families in integrated services networks, we present a hierarchical SFQ scheduler and derive its performance bounds. Our analysis demonstrates that SFQ is suitable for integrated services networks since it: (1) achieves low average as well as maximum delay for low-throughput applications (e.g., interactive audio, telnet, etc.); (2) provides fairness which is desirable for VBR video; (3) provides fairness, regardless of variation in server capacity, for throughput-intensive, flow-controlled data applications; (4) enables hierarchical link sharing which is desirable for managing heterogeneity; and (5) is computationally efficient.

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Dynamic capacity provisioning is a useful technique for handling the multi-time-scale variations seen in Internet workloads. In this article, we propose a novel dynamic provisioning technique for multi-tier Internet applications that employs (1) a flexible queuing model to determine how much of the resources to allocate to each tier of the application, and (2) a combination of predictive and reactive methods that determine when to provision these resources, both at large and small time scales. We propose a novel data center architecture based on virtual machine monitors to reduce provisioning overheads. Our experiments on a forty-machine Xen/Linux-based hosting platform demonstrate the responsiveness of our technique in handling dynamic workloads. In one scenario where a flash crowd caused the workload of a three-tier application to double, our technique was able to double the application capacity within five minutes, thus maintaining response-time targets. Our technique also reduced the overhead of switching servers across applications from several minutes to less than a second, while meeting the performance targets of residual sessions.

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Agile dynamic provisioning of multi-tier Internet applications

The need for supporting variety of hard and soft real-time as well as best effort applications in a multimedia computing environment requires an operating system framework that: (1) enables different schedulers to be employed for different application classes, and (2) provides protection between the various classes of applications. We argue that these objectives can be achieved by hierarchical partitioning of CPU bandwidth, in which an operating system partitions the CPU bandwidth among various application classes, and each application class, in turn, partitions its allocation (potentially using a different scheduling algorithm) among its sub-classes or applications. We present Start-time Fair Queuing (SFQ) algorithm, which enables such hierarchical partitioning. We have implemented a hierarchical scheduler in Solaris 2.4. We describe our implementation, and demonstrate its suitability for multimedia operating systems.

Pawan Goyal

Papers

A flexible model for resource management in virtual private networks

Start-time fair queueing: a scheduling algorithm for integrated services packet switching networks

Start-time fair queueing: a scheduling algorithm for integrated services packet switching networks

Agile dynamic provisioning of multi-tier Internet applications

A hierarchial CPU scheduler for multimedia operating systems