Virtual Organization Clusters: Self-Provisioned Clouds on the Grid

Virtual Organization Clusters (VOCs) provide a novel architecture for overlaying dedicated cluster systems on existing grid infrastructures. VOCs provide customized, homogeneous execution environments on a per-Virtual Organization basis, without the cost of physical cluster construction or the overhead of per-job containers. Administrative access and overlay network capabilities are granted to Virtual Organizations (VOs) that choose to implement VOC technology, while the system remains completely transparent to end users and non-participating VOs. Unlike alternative systems that require explicit leases, VOCs are autonomically self-provisioned according to configurable usage policies. As a grid computing architecture, VOCs are designed to be technology agnostic and are implementable by any combination of software and services that follows the Virtual Organization Cluster Model. As demonstrated through simulation testing and evaluation of an implemented prototype, VOCs are a viable mechanism for increasing end-user job compatibility on grid sites. On existing production grids, where jobs are frequently submitted to a small subset of sites and thus experience high queuing delays relative to average job length, the grid-wide addition of VOCs does not adversely affect mean job sojourn time. By load-balancing jobs among grid sites, VOCs can reduce the total amount of queuing on a grid to a level sufficient to counteract the performance overhead introduced by virtualization

Building Scientific Clouds: The Distributed, Peer-to-Peer Approach

The Scientific community is constantly growing in size. The increase in personnel number and projects have resulted in the requirement of large amounts of storage, CPU power and other computing resources. It has also become necessary to acquire these resources in an affordable manner that is sensitive to work loads. In this thesis, the author presents a novel approach that provides the communication platform that will support such large scale scientific projects. These resources could be difficult to acquire due to NATs, firewalls and other site-based restrictions and policies. Methods used to overcome these hurdles have been discussed in detail along with other advantages of using such a system, which include: increased availability of necessary computing infrastructure; increased grid resource utilization; reduced user dependability; reduced job execution time. Experiments conducted included local infrastructure on the Clemson University Campus as well as resources provided by other federated grid sites

Kestrel: Job Distribution and Scheduling using XMPP

A new distributed computing framework, named Kestrel, for Many-Task Computing (MTC) applications and implementing Virtual Organization Clusters (VOCs) is proposed. Kestrel is a lightweight, highly available system based on the Extensible Messaging and Presence Protocol (XMPP), and has been developed to explore XMPP-based techniques for improving MTC and VOC tolerance to faults due to scaling and intermittently connected heterogeneous resources. Kestrel provides a VOC with a special purpose scheduler for VOCs which can provide better scalability under certain workload assumptions, namely CPU bound processes and bag-of-task applications. Experimental results have shown that Kestrel is capable of operating a VOC of at least 1600 worker nodes with all nodes visible to the scheduler at once. When using multiple sites located in both North America and Europe, the latencies introduced to the round trip time of messages were on the order of 0.3 seconds. To offset the overhead of XMPP processing, a task execution time of 2 seconds is sufficient for a pool of 900 workers on a single site to operate at near 100% use. Requiring tasks that take on the order of 30 seconds to a minute to execute would compensate for increased latency during job dispatch across multiple sites. Kestrel\u27s architecture is rooted in pilot job frameworks heavily used in Grid computing, it is also modeled after the use of IRC by botnets to communicate between compromised machines and command and control servers. For Kestrel, the extensibility of XMPP has allowed development of protocols for identifying manager nodes, discovering the capabilities of worker agents, and for distributing tasks. The presence notifications provided by XMPP allow Kestrel to monitor the global state of the pool and to perform task dispatching based on worker availability. In this work it is argued that XMPP is by design a very good fit for cloud computing frameworks. It offers scalability, federation between servers and some autonomicity of the agents. During the summer of 2010, Kestrel was used and modified based on feedback from the STAR group at Brookhaven National Laboratories. STAR provided a virtual machine image with applications for simulating proton collisions using PYTHIA and GEANT3. A Kestrel-based virtual organization cluster, created on top of Clemson University\u27s Palmetto cluster, was able to provide over 400,000 CPU hours of computation over the course of a month using an average of 800 virtual machine instances every day, generating nearly seven terabytes of data and the largest PYTHIA production run that STAR ever achieved. Several architectural issues were encountered during the course of the experiment and were resolved by moving from the original JSON protocols used by Kestrel to native XMPP equivalents that offered better message delivery confirmation and integration with existing tools

Twos Company, Threes A Cloud: Challenges To Implementing Service Models

Although three models are currently being used in cloud computing (Software as a Service, Platform as a Service, and infrastructure as a service, there remain many challenges before most business accept cloud computing as a reality. Virtualization in cloud computing has many advantages but carries a penalty because of state configurations, kernel drivers, and user interface environments. In addition, many non-standard architectures exist to power cloud models that are often incompatible. Another issue is adequately provisioning the resources required for a multi-tier cloud-based application in such a way that on-demand elasticity is present at vastly different scales yet is carried out efficiently. For networks that have large geographical footprints another problem arises from bottlenecks between elements supporting virtual machines and their control. While many solutions have been proposed to alleviate these problems, some of which are already commercial, much remains to be done to see whether these solutions will be practicable at scale up and address business concerns

Practical Implementation of the Virtual Organization Cluster Model

Virtualization has great potential in the realm of scientific computing because of its inherent advantages with regard to environment customization and isolation. Virtualization technology is not without it\u27s downsides, most notably, increased computational overhead. This thesis introduces the operating mechanisms of grid technologies in general, and the Open Science Grid in particular, including a discussion of general organization and specific software implementation. A model for utilization of virtualization resources with separate administrative domains for the virtual machines (VMs) and the physical resources is then presented. Two well-known virtual machine monitors, Xen and the Kernel-based Virtual Machine (KVM), are introduced and a performance analysis conducted. The High-Performance Computing Challenge (HPCC) benchmark suite is used in conjunction with independent High-Performance Linpack (HPL) trials in order to analyze specific performance issues. Xen was found to introduce much lower performance overhead than KVM, however, KVM retains advantages with regard to ease of deployment, both of the VMM itself and of the VM images. KVM\u27s snapshot mode is of special interest, as it allows multiple VMs to be instantiated from a single image located on a network store. With virtualization overhead shown to be acceptable for high-throughput computing tasks, the Virtual Organization Cluster (VOC) Model was implemented as a prototype. Dynamic scaling and multi-site scheduling extensions were also successfully implemented using this prototype. It is also shown that traditional overlay networks have scaling issues and that a new approach to wide-area scheduling is needed. The use of XMPP messaging and the Google App Engine service to implement a virtual machine monitoring system is presented. Detailed discussions of the relevant sections of the XMPP protocol and libraries are presented. XMPP is found to be a good choice for sending status information due to its inherent advantages in a bandwidth-limited NAT environment. Thus, it is concluded that the VOC Model is a practical way to implement virtualization of high-throughput computing tasks. Smaller VOCs may take advantage of traditional overlay networks whereas larger VOCs need an alternative approach to scheduling

Running user-provided virtual machines in batch-oriented computing clusters

The use of virtualization in HPC clusters can provide rich software environments, application isolation and efficient workload management mechanisms, but system-level virtualization introduces a software layer on the computing nodes that reduces performance and inhibits the direct use of hardware devices. We propose an unobtrusive user-level platform that allows the execution of virtual machines inside batch jobs without limiting the computing cluster’s ability to execute the most demanding applications. A per-user platform uses a static mode in which the VMs run entirely using the resources of a single batch job and a dynamic mode in which the VMs navigate at runtime between the continuously allocated jobs node time-slots. A dynamic mode is introduced to build complex scenarios with several VMs for personalized HPC environments or persistent services such as databases or web services based applications. Fault-tolerant system agents, integrated using group communication primitives, control the system and execute user commands and automatic scheduling decisions made by an optional monitoring function. The performance of compute intensive applications running on our system suffers negligible overhead compared to the native configuration. The performance of distributed applications is dependent on their communication patterns as the user-mode network overlay introduces a relevant communication overhead.FC

Variability in Behavior of Application Service Workload in a Utility Cloud

Using the elasticity feature of a utility cloud, users can acquire and release resources as required and pay for what they use. Applications with time-varying workloads can request for variable resources over time that makes cloud a convenient option for such applications. The elasticity in current IaaS cloud provides mainly two options to the users: horizontal and vertical scaling. In both ways of scaling the basic resource allocation unit is fixed-sized VM, it forces the cloud users to characterize their workload based on VM size, which might lead to under-utilization or over-allocation of resources. This turns out to be an inefficient model for both cloud users and providers. In this paper we discuss and calculate the variability in different kinds of application service workload. We also discuss different dynamic provisioning approaches proposed by researchers. We conclude with a brief introduction to the issues or limitations in existing solutions and our approach to resolve them in a way that is suitable and economic for both cloud user and provider

Scheduling in virtual infrastructure

For the execution of the scientific applications, different methods have been proposed to dynamically provide execution environments for such applications that hide the complexity of underlying distributed and heterogeneous infrastructures. Recently virtualization has emerged as a promising technology to provide such environments. Virtualization is a technology that abstracts away the details of physical hardware and provides virtualized resources for high-level scientific applications. Virtualization offers a cost-effective and flexible way to use and manage computing resources. Such an abstraction is appealing in Grid computing and Cloud computing for better matching jobs (applications) to computational resources. This work applies the virtualization concept to the Condor dynamic resource management system by using Condor Virtual Universe to harvest the existing virtual computing resources to their maximum utility. It allows existing computing resources to be dynamically provisioned at run-time by users based on application requirements instead of statically at design-time thereby lay the basis for efficient use of the available resources, thus providing way for the efficient use of the available resources.En la ejecución de aplicaciones científicas, existen diversas propuestas cuyo objetivo es proporcionar entornos adecuados de ejecución que oculten la complejidad de las infraestructuras distribuidas y heterogéneas subyacentes a las aplicaciones. Recientemente, la virtualización ha emergido como una prometedora tecnología que permite abstraer los detalles del hardware, mediante la asignación de recursos virtualizados a las aplicaciones científicas de altas necesidades de cómputo. La virtualización ofrece una solución rentable y además permite una gestión flexible de recursos. Este nivel de abstracción es deseable en entornos de Grid Computing y Cloud Computing para obtener una planificación adecuada de tarea (aplicaciones) sobre los recursos computacionales. Este trabajo aplica el concepto de virtualización al sistema gestor dinámico de recursos Condor, mediante la utilización de Condor Virtual Universe para conseguir una máxima utilización de los recursos computacionales virtuales. Además, permite que los recursos de cómputo existentes sean proporcionados dinámicamente en tiempo de ejecución por los usuarios, en función de los requisitos de la aplicación, en lugar de mantener la definición estática definida en tiempo de diseño, y así sentar las bases del uso eficiente de los recursos disponibles.En l'execució d'aplicacions científiques, existeixen diverses propostes amb l'objectiu de proporcionar entorns adequats d'execució que amaguin la complexitat de les infraestructures distribuïdes i heterogènies subjacents a les aplicacions. Recentment, la virtualització ha sorgit com una prometedora tecnologia que ha de permetre abstraure els detalls del hardware, mitjançant l'assignació de recursos virtualitzats a les aplicacions científiques amb altes necessitats de còmput. La virtualizatzació ofereix una solució rentable i a més permet una gestió flexible de recursos. Aquest nivell d'abstracció es desitjable en entorns de Grid Computing i Cloud Computing per a obtenir una planificació adequada del treball (aplicacions) sobre els recursos computacionals. Aquest treball aplica el concepte de virtualització al sistema gestor dinàmic de recursos Condor, mitjançant la utilització de Condor Virtual Universe per aconseguir una màxima utilització dels recursos computacionals virtuals. A més, permet que els recursos de còmput existents siguin proporcionats dinàmicament en temps d'execució pels usuaris, en funció dels requisits de l'aplicació, en lloc de mantenir la definició estàtica definida en temps de disseny, i així assentar unes bases per l'ús eficient dels recursos disponibles