A Framework for Effective Placement of Virtual Machine Replicas for Highly Available Performance-sensitive Cloud-based Applications

REACTION 2012. 1st International workshop on Real-time and distributed computing in emerging applications. December 4th, 2012, San Juan, Puerto Rico.Applications are increasingly being deployed in the Cloud due to benefits stemming from economy of scale, scalability, flexibility and utility-based pricing model. Although most cloud-based applications have hitherto been enterprisestyle, there is a new trend towards hosting performancesensitive applications in the cloud that demand both high availability and good response times. In the current stateof- the-art in cloud computing research, there does not exist solutions that provide both high availability and acceptable response times to these applications in a way that also optimizes resource consumption in data centers, which is a key consideration for cloud providers. This paper addresses this dual challenge by presenting a design of a fault-tolerant framework for virtualized data centers that makes two important contributions. First, it describes an architecture of a fault-tolerance framework that can be used to automatically deploy replicas of virtual machines in data centers in a way that optimizes resources while assures availability and responsiveness. Second, it describes a specific formulation of a replica deployment combinatorial optimization problem that can be plugged into our strategizable deployment framework.This work was supported in part by the National Science Foundation NSF SHF/CNS Award CNS 0915976 and NSF CAREER CNS 0845789. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation

Patterns for Providing Real-Time Guarantees in DOC Middleware - Doctoral Dissertation, May 2002

The advent of open and widely adopted standards such as Common Object Request Broker Architecture (CORBA) [47] has simplified and standardized the development of distributed applications. For applications with real-time constraints, including avionics, manufacturing, and defense systems, these standards are evolving to include Quality-of-Service (QoS) specifications. Operating systems such as Real-time Linux [60] have responded with interfaces and algorithms to guarantee real-time response; similarly, languages such as Real-time Java [59] include mechanisms for specifying real-time properties for threads. However, the middleware upon which large distributed applications are based has not yet addressed end-to-end guarantees of QoS specifications. Unless this challenge can be met, developers must resort to ad hoc solutions that may not scale or migrate well among different platforms. This thesis provides two contributions to the study of real-time Distributed Object Computing (DOC) middleware. First, it identifies potential bottlenecks and problems with respect to guaranteeing real-time performance in contemporary middleware. Experimental results illustrate how these problems lead to incorrect real-time behavior in contemporary middleware platforms. Second, this thesis presents designs and techniques for providing real-time QoS guarantees in DOC middleware in the context of TAO [6], an open-source and widely adopted implementation of real-time CORBA. Architectural solutions presented here are coupled with empirical evaluations of end-to-end real-time behavior. Analysis of the problems, forces, solutions, and consequences are presented in terms of patterns and frame-works, so that solutions obtained for TAO can be appropriately applied to other real-time systems

Argobots: A Lightweight Low-Level Threading and Tasking Framework

In the past few decades, a number of user-level threading and tasking models have been proposed in the literature to address the shortcomings of OS-level threads, primarily with respect to cost and flexibility. Current state-of-the-art user-level threading and tasking models, however, either are too specific to applications or architectures or are not as powerful or flexible. In this paper, we present Argobots, a lightweight, low-level threading and tasking framework that is designed as a portable and performant substrate for high-level programming models or runtime systems. Argobots offers a carefully designed execution model that balances generality of functionality with providing a rich set of controls to allow specialization by end users or high-level programming models. We describe the design, implementation, and performance characterization of Argobots and present integrations with three high-level models: OpenMP, MPI, and colocated I/O services. Evaluations show that (1) Argobots, while providing richer capabilities, is competitive with existing simpler generic threading runtimes; (2) our OpenMP runtime offers more efficient interoperability capabilities than production OpenMP runtimes do; (3) when MPI interoperates with Argobots instead of Pthreads, it enjoys reduced synchronization costs and better latency-hiding capabilities; and (4) I/O services with Argobots reduce interference with colocated applications while achieving performance competitive with that of a Pthreads approach

Flexible Scheduling in Middleware for Distributed rate-based real-time applications - Doctoral Dissertation, May 2002

Distributed rate-based real-time systems, such as process control and avionics mission computing systems, have traditionally been scheduled statically. Static scheduling provides assurance of schedulability prior to run-time overhead. However, static scheduling is brittle in the face of unanticipated overload, and treats invocation-to-invocation variations in resource requirements inflexibly. As a consequence, processing resources are often under-utilized in the average case, and the resulting systems are hard to adapt to meet new real-time processing requirements. Dynamic scheduling offers relief from the limitations of static scheduling. However, dynamic scheduling offers relief from the limitations of static scheduling. However, dynamic scheduling often has a high run-time cost because certain decisions are enforced on-line. Furthermore, under conditions of overload tasks can be scheduled dynamically that may never be dispatched, or that upon dispatch would miss their deadlines. We review the implications of these factors on rate-based distributed systems, and posits the necessity to combine static and dynamic approaches to exploit the strengths and compensate for the weakness of either approach in isolation. We present a general hybrid approach to real-time scheduling and dispatching in middleware, that can employ both static and dynamic components. This approach provides (1) feasibility assurance for the most critical tasks, (2) the ability to extend this assurance incrementally to operations in successively lower criticality equivalence classes, (3) the ability to trade off bounds on feasible utilization and dispatching over-head in cases where, for example, execution jitter is a factor or rates are not harmonically related, and (4) overall flexibility to make more optimal use of scarce computing resources and to enforce a wider range of application-specified execution requirements. This approach also meets additional constraints of an increasingly important class of rate-based systems, those with requirements for robust management of real-time performance in the face of rapidly and widely changing operating conditions. To support these requirements, we present a middleware framework that implements the hybrid scheduling and dispatching approach described above, and also provides support for (1) adaptive re-scheduling of operations at run-time and (2) reflective alternation among several scheduling strategies to improve real-time performance in the face of changing operating conditions. Adaptive re-scheduling must be performed whenever operating conditions exceed the ability of the scheduling and dispatching infrastructure to meet the critical real-time requirements of the system under the currently specified rates and execution times of operations. Adaptive re-scheduling relies on the ability to change the rates of execution of at least some operations, and may occur under the control of a higher-level middleware resource manager. Different rates of execution may be specified under different operating conditions, and the number of such possible combinations may be arbitrarily large. Furthermore, adaptive rescheduling may in turn require notification of rate-sensitive application components. It is therefore desirable to handle variations in operating conditions entirely within the scheduling and dispatching infrastructure when possible. A rate-based distributed real-time application, or a higher-level resource manager, could thus fall back on adaptive re-scheduling only when it cannot achieve acceptable real-time performance through self-adaptation. Reflective alternation among scheduling heuristics offers a way to tune real-time performance internally, and we offer foundational support for this approach. In particular, run-time observable information such as that provided by our metrics-feedback framework makes it possible to detect that a given current scheduling heuristic is underperforming the level of service another could provide. Furthermore we present empirical results for our framework in a realistic avionics mission computing environment. This forms the basis for guided adaption. This dissertation makes five contributions in support of flexible and adaptive scheduling and dispatching in middleware. First, we provide a middle scheduling framework that supports arbitrary and fine-grained composition of static/dynamic scheduling, to assure critical timeliness constraints while improving noncritical performance under a range of conditions. Second, we provide a flexible dispatching infrastructure framework composed of fine-grained primitives, and describe how appropriate configurations can be generated automatically based on the output of the scheduling framework. Third, we describe algorithms to reduce the overhead and duration of adaptive rescheduling, based on sorting for rate selection and priority assignment. Fourth, we provide timely and efficient performance information through an optimized metrics-feedback framework, to support higher-level reflection and adaptation decisions. Fifth, we present the results of empirical studies to quantify and evaluate the performance of alternative canonical scheduling heuristics, across a range of load and load jitter conditions. These studies were conducted within an avionics mission computing applications framework running on realistic middleware and embedded hardware. The results obtained from these studies (1) demonstrate the potential benefits of reflective alternation among distinct scheduling heuristics at run-time, and (2) suggest performance factors of interest for future work on adaptive control policies and mechanisms using this framework

VISOR: virtual machine images management service for cloud infarestructures

Cloud Computing is a relatively novel paradigm that aims to fulfill the computing as utility dream. It has appeared to bring the possibility of providing computing resources (such as servers, storage and networks) as a service and on demand, making them accessible through common Internet protocols. Through cloud offers, users only need to pay for the amount of resources they need and for the time they use them. Virtualization is the clouds key technology, acting upon virtual machine images to deliver fully functional virtual machine instances. Therefore, virtual machine images play an important role in Cloud Computing and their efficient management becomes a key concern that should be carefully addressed. To tackle this requirement, most cloud offers provide their own image repository, where images are stored and retrieved from, in order to instantiate new virtual machines. However, the rise of Cloud Computing has brought new problems in managing large collections of images. Existing image repositories are not able to efficiently manage, store and catalogue virtual machine images from other clouds through the same centralized service repository. This becomes especially important when considering the management of multiple heterogeneous cloud offers. In fact, despite the hype around Cloud Computing, there are still existing barriers to its widespread adoption. Among them, clouds interoperability is one of the most notable issues. Interoperability limitations arise from the fact that current cloud offers provide proprietary interfaces, and their services are tied to their own requirements. Therefore, when dealing with multiple heterogeneous clouds, users face hard to manage integration and compatibility issues. The management and delivery of virtual machine images across different clouds is an example of such interoperability constraints. This dissertation presents VISOR, a cloud agnostic virtual machine images management service and repository. Our work towards VISOR aims to provide a service not designed to fit in a specific cloud offer but rather to overreach sharing and interoperability limitations among different clouds. With VISOR, the management of clouds interoperability can be seamlessly abstracted from the underlying procedures details. In this way, it aims to provide users with the ability to manage and expose virtual machine images across heterogeneous clouds, throughout the same generic and centralized repository and management service. VISOR is an open source software with a community-driven development process, thus it can be freely customized and further improved by everyone. The conducted tests to evaluate its performance and resources usage rate have shown VISOR as a stable and high performance service, even when compared with other services already in production. Lastly, placing clouds as the main target audience is not a limitation for other use cases. In fact, virtualization and virtual machine images are not exclusively linked to cloud environments. Therefore and given the service agnostic design concerns, it is possible to adapt it to other usage scenarios as well.A Computação em Nuvem (”Cloud Computing”) é um paradigma relativamente novo que visa cumprir o sonho de fornecer a computação como um serviço. O mesmo surgiu para possibilitar o fornecimento de recursos de computação (servidores, armazenamento e redes) como um serviço de acordo com as necessidades dos utilizadores, tornando-os acessíveis através de protocolos de Internet comuns. Através das ofertas de ”cloud”, os utilizadores apenas pagam pela quantidade de recursos que precisam e pelo tempo que os usam. A virtualização é a tecnologia chave das ”clouds”, atuando sobre imagens de máquinas virtuais de forma a gerar máquinas virtuais totalmente funcionais. Sendo assim, as imagens de máquinas virtuais desempenham um papel fundamental no ”Cloud Computing” e a sua gestão eficiente torna-se um requisito que deve ser cuidadosamente analisado. Para fazer face a tal necessidade, a maioria das ofertas de ”cloud” fornece o seu próprio repositório de imagens, onde as mesmas são armazenadas e de onde são copiadas a fim de criar novas máquinas virtuais. Contudo, com o crescimento do ”Cloud Computing” surgiram novos problemas na gestão de grandes conjuntos de imagens. Os repositórios existentes não são capazes de gerir, armazenar e catalogar images de máquinas virtuais de forma eficiente a partir de outras ”clouds”, mantendo um único repositório e serviço centralizado. Esta necessidade torna-se especialmente importante quando se considera a gestão de múltiplas ”clouds” heterogéneas. Na verdade, apesar da promoção extrema do ”Cloud Computing”, ainda existem barreiras à sua adoção generalizada. Entre elas, a interoperabilidade entre ”clouds” é um dos constrangimentos mais notáveis. As limitações de interoperabilidade surgem do fato de as ofertas de ”cloud” atuais possuírem interfaces proprietárias, e de os seus serviços estarem vinculados às suas próprias necessidades. Os utilizadores enfrentam assim problemas de compatibilidade e integração difíceis de gerir, ao lidar com ”clouds” de diferentes fornecedores. A gestão e disponibilização de imagens de máquinas virtuais entre diferentes ”clouds” é um exemplo de tais restrições de interoperabilidade. Esta dissertação apresenta o VISOR, o qual é um repositório e serviço de gestão de imagens de máquinas virtuais genérico. O nosso trabalho em torno do VISOR visa proporcionar um serviço que não foi concebido para lidar com uma ”cloud” específica, mas sim para superar as limitações de interoperabilidade entre ”clouds”. Com o VISOR, a gestão da interoperabilidade entre ”clouds” é abstraída dos detalhes subjacentes. Desta forma pretende-se proporcionar aos utilizadores a capacidade de gerir e expor imagens entre ”clouds” heterogéneas, mantendo um repositório e serviço de gestão centralizados. O VISOR é um software de código livre com um processo de desenvolvimento aberto. O mesmo pode ser livremente personalizado e melhorado por qualquer pessoa. Os testes realizados para avaliar o seu desempenho e a taxa de utilização de recursos mostraram o VISOR como sendo um serviço estável e de alto desempenho, mesmo quando comparado com outros serviços já em utilização. Por fim, colocar as ”clouds” como principal público-alvo não representa uma limitação para outros tipos de utilização. Na verdade, as imagens de máquinas virtuais e a virtualização não estão exclusivamente ligadas a ambientes de ”cloud”. Assim sendo, e tendo em conta as preocupações tidas no desenho de um serviço genérico, também é possível adaptar o nosso serviço a outros cenários de utilização

(I) A Declarative Framework for ERP Systems(II) Reactors: A Data-Driven Programming Model for Distributed Applications

To those who can be swayed by argument and those who know they do not have all the answers This dissertation is a collection of six adapted research papers pertaining to two areas of research. (I) A Declarative Framework for ERP Systems: • POETS: Process-Oriented Event-driven Transaction Systems. The paper describes an ontological analysis of a small segment of the enterprise domain, namely the general ledger and accounts receivable. The result is an event-based approach to designing ERP systems and an abstract-level sketch of the architecture. • Compositional Specification of Commercial Contracts. The paper de-scribes the design, multiple semantics, and use of a domain-specific lan-guage (DSL) for modeling commercial contracts. • SMAWL: A SMAll Workflow Language Based on CCS. The paper show

Biweekly Report for 6 May 1955

Bi-weekly progress report of Division 6 research teams

Continuum: an architecture for user evolvable collaborative virtual environments

Continuum is a software platform for collaborative virtual environments. Continuum\u27s architecture supplies a world model and defines how to combine object state, behavior code, and resource data into this single shared structure. The system frees distributed users from the constraints of monolithic centralized virtual world architectures and instead allows individual users to extend and evolve the virtual world by creating and controlling their own individual pieces of the larger world model. The architecture provides support for data distribution, code management, resource management, and rapid deployment through standardized viewers. This work not only provides this architecture, but it includes a proven implementation and the associated development tools to allow for creation of these worlds