Robust parallel job scheduling infrastructure for service-oriented grid computing systems

Recent trends in grid computing development is moving towards a service-oriented architecture. With the momentum gaining for the service-oriented grid computing systems, the issue of deploying support for integrated scheduling and fault-tolerant approaches becomes paramount importance. To this end, we propose a scalable framework that loosely couples the dynamic job scheduling approach with the hybrid replications approach to schedule jobs efficiently while at the same time providing fault-tolerance. The novelty of the proposed framework is that it uses passive replication approach under high system load and active replication approach under low system loads. The switch between these two replication methods is also done dynamically and transparently.

Grid accounting service infrastructure for service-oriented grid computing systems

In this paper, we propose an architecture of accounting and payment services for service-oriented grid computing systems. The proposed accounting and payment services provide the mechanisms for service providers to be paid for authorized use of their resources. It supports the recording of usage data, secure storage of that data, analysis of that data for purposes of billing and so forth. It allows a variety of payment methods, it is scalable, secure, convenient, and reduce the overall cost of payment processing while taking into account requirements of Grid computing systems.

Secure accounting and payment infrastructure for grid computing

In this paper, we propose an architecture of accounting and payment services for service oriented grid computing systems. The proposed accounting and payment services provide the mechanisms for service providers to be paid for authorized use of their resources. It supports the recording of usage data, secure storage of that data, analysis of that data for purposes of billing and so forth. It allows a variety of payment methods, it is scalable, secure, convenient, and reduce the overall cost of payment processing while taking into account, requirements of Grid computing systems.

Fault detection service architecture for grid computing systems

The ability to tolerate failures while effectively exploiting the grid computing resources in an scalable and transparent manner must be an integral part of grid computing infrastructure. Hence, fault-detection service is a necessary prerequisite to fault tolerance and fault recovery in grid computing. To this end, we present an scalable fault detection service architecture. The proposed fault-detection system provides services that monitors user applications, grid middlewares and the dynamically changing state of a collection of distributed resources. It reports summaries of this information to the appropriate agents on demand or instantaneously in the event of failures.

Adaptive hierarchical scheduling policy for enterprise grid computing systems

In an enterprise grid computing environments, users have access to multiple resources that may be distributed geographically. Thus, resource allocation and scheduling is a fundamental issue in achieving high performance on enterprise grid computing. Most of current job scheduling systems for enterprise grid computing provide batch queuing support and focused solely on the allocation of processors to jobs. However, since I/O is also a critical resource for many jobs, the allocation of processor and I/O resources must be coordinated to allow the system to operate most effectively. To this end, we present a hierarchical scheduling policy paying special attention to I/O and service-demands of parallel jobs in homogeneous and heterogeneous systems with background workload. The performance of the proposed scheduling policy is studied under various system and workload parameters through simulation. We also compare performance of the proposed policy with a static space–time sharing policy. The results show that the proposed policy performs substantially better than the static space–time sharing policy.

Interoperable and transparent dynamic deployment of web services for service oriented grids

Dynamic deployment of Web services is a term used frequently when describing the selection and deployment of a service to a grid host. Although current grid systems (such as Globus) provide dynamic deployment, the requirements of the service being deployed are not considered. Therefore truly dynamic deployment cannot be achieved as the services deployed are restricted to the grid system used. We present a dynamic deployment mechanism as part of self configuration in a service oriented grid environment. The dynamic deployment mechanism takes the requirements of the service into consideration, including parameters such as the operating system required to execute the service, the required software libraries, any additional required software packages, price and Quality of Service (QoS) parameters.

A reputation-based grid information service

In a large-scale wide-area system such as the Grid, trust is a prime concern. The current generation of grid information services lack the ability to determine how trustworthy a particular grid service provider or grid customer is likely to be. In this paper, we propose a grid information service with reputation management facility and its underlying algorithm for computing and managing reputation in service-oriented grid computing. Our reputation management service is based on the concept of dynamic trust and reputation adaptation based on community experiences. The working model and functionality offered by the proposed reputation management service is discussed.

Service migration in autonomic service oriented grids

The introduction of Web services into grids helped to address their two main obstacles to be embraced by business and industry, heterogeneity and useability. However, many problems are still open, e.g., grid reconfiguration, reliability and computing optimization. We argue here that a mechanism that could help solving these problems is Web Service migration, a part of automatic and transparent brokerage. Web service migration presents a number of new requirements not addressed in traditional process migration, being the outcome of Web services specific configuration of hosts and application servers, and availability of Web services / resources state. In this paper we report on our study into the development of a Web service migration facility focused on providing migration of services in a Service Oriented Grid environment. We present a novel approach to Web service migration, embodied in a System Management Broker, which is transparent, interoperable and flexible. We take the requirements of Web services into consideration when discovering suitable destination hosts and match services to suitable grid resources which are able to fulfil the needs of the service. We discuss a number of experiments conducted with different types of grid and Web service applications to highlight the feasibility and effectiveness of our migration facility and demonstrate how our facility significantly improves Service Oriented Grids.

Analytical communication networks model for enterprise grid computing

This paper addresses the problem of performance analysis based on the communication modeling of large-scale heterogeneous distributed systems, with an emphasis on enterprise Grid computing systems. The study of communication layers is important, as the overall performance of a distributed system often critically hinges on the effectiveness of this part. We propose an analytical model that is based on probabilistic analysis and queuing networks. The proposed model considers the processor as well as network heterogeneity of the enterprise Grid system. The model is validated through comprehensive simulations, which demonstrate that the proposed model exhibits a good degree of accuracy for various system sizes, and under different working conditions.

Analytical performance modeling of the enterprise grid computing

This paper addresses the problem of performance modeling of large-scale heterogeneous distributed systems with emphases on enterprise grid computing systems. To this end, we present an analytical model that can be employed to explore the effectiveness of different design approaches so that one can have an intelligent choice during design and evaluation a cost-effective large-scale heterogeneous distributed computing system. The model is validated through comprehensive simulation.

Services on Application Level in Grid for Scientific Calculations

AMS Subj. Classification: 00-02, (General)

An autonomic management system for service oriented enterprise grid computing

Grid computing and service oriented architectures improve the way computational tasks are performed. Through this research a management system, utilising the autonomic characteristics of self discovery and negotiation, self configuration and self healing, was designed and implemented, ultimately removing the need for users to know the intricacies of these systems.

Analysis of service-oriented computing systems

La computación basada en servicios (Service-Oriented Computing, SOC) se estableció como un paradigma ampliamente aceptado para el desarollo de sistemas de software flexibles, distribuidos y adaptables, donde las composiciones de los servicios realizan las tareas más complejas o de nivel más alto, frecuentemente tareas inter-organizativas usando los servicios atómicos u otras composiciones de servicios. En tales sistemas, las propriedades de la calidad de servicio (Quality of Service, QoS), como la rapídez de procesamiento, coste, disponibilidad o seguridad, son críticas para la usabilidad de los servicios o sus composiciones en cualquier aplicación concreta. El análisis de estas propriedades se puede realizarse de una forma más precisa y rica en información si se utilizan las técnicas de análisis de programas, como el análisis de complejidad o de compartición de datos, que son capables de analizar simultáneamente tanto las estructuras de control como las de datos, dependencias y operaciones en una composición. El análisis de coste computacional para la composicion de servicios puede ayudar a una monitorización predictiva así como a una adaptación proactiva a través de una inferencia automática de coste computacional, usando los limites altos y bajos como funciones del valor o del tamaño de los mensajes de entrada. Tales funciones de coste se pueden usar para adaptación en la forma de selección de los candidatos entre los servicios que minimizan el coste total de la composición, basado en los datos reales que se pasan al servicio. Las funciones de coste también pueden ser combinadas con los parámetros extraídos empíricamente desde la infraestructura, para producir las funciones de los límites de QoS sobre los datos de entrada, cuales se pueden usar para previsar, en el momento de invocación, las violaciones de los compromisos al nivel de servicios (Service Level Agreements, SLA) potenciales or inminentes. En las composiciones críticas, una previsión continua de QoS bastante eficaz y precisa se puede basar en el modelado con restricciones de QoS desde la estructura de la composition, datos empiricos en tiempo de ejecución y (cuando estén disponibles) los resultados del análisis de complejidad. Este enfoque se puede aplicar a las orquestaciones de servicios con un control centralizado del flujo, así como a las coreografías con participantes multiples, siguiendo unas interacciones complejas que modifican su estado. El análisis del compartición de datos puede servir de apoyo para acciones de adaptación, como la paralelización, fragmentación y selección de los componentes, las cuales son basadas en dependencias funcionales y en el contenido de información en los mensajes, datos internos y las actividades de la composición, cuando se usan construcciones de control complejas, como bucles, bifurcaciones y flujos anidados. Tanto las dependencias funcionales como el contenido de información (descrito a través de algunos atributos definidos por el usuario) se pueden expresar usando una representación basada en la lógica de primer orden (claúsulas de Horn), y los resultados del análisis se pueden interpretar como modelos conceptuales basados en retículos. ABSTRACT Service-Oriented Computing (SOC) is a widely accepted paradigm for development of flexible, distributed and adaptable software systems, in which service compositions perform more complex, higher-level, often cross-organizational tasks using atomic services or other service compositions. In such systems, Quality of Service (QoS) properties, such as the performance, cost, availability or security, are critical for the usability of services and their compositions in concrete applications. Analysis of these properties can become more precise and richer in information, if it employs program analysis techniques, such as the complexity and sharing analyses, which are able to simultaneously take into account both the control and the data structures, dependencies, and operations in a composition. Computation cost analysis for service composition can support predictive monitoring and proactive adaptation by automatically inferring computation cost using the upper and lower bound functions of value or size of input messages. These cost functions can be used for adaptation by selecting service candidates that minimize total cost of the composition, based on the actual data that is passed to them. The cost functions can also be combined with the empirically collected infrastructural parameters to produce QoS bounds functions of input data that can be used to predict potential or imminent Service Level Agreement (SLA) violations at the moment of invocation. In mission-critical applications, an effective and accurate continuous QoS prediction, based on continuations, can be achieved by constraint modeling of composition QoS based on its structure, known data at runtime, and (when available) the results of complexity analysis. This approach can be applied to service orchestrations with centralized flow control, and choreographies with multiple participants with complex stateful interactions. Sharing analysis can support adaptation actions, such as parallelization, fragmentation, and component selection, which are based on functional dependencies and information content of the composition messages, internal data, and activities, in presence of complex control constructs, such as loops, branches, and sub-workflows. Both the functional dependencies and the information content (described using user-defined attributes) can be expressed using a first-order logic (Horn clause) representation, and the analysis results can be interpreted as a lattice-based conceptual models.