QoS Provisioning by Meta-Scheduling in Advance within SLA-Based Grid Environments

The establishment of agreements between users and the entities which manage the Grid resources is still a challenging task. On the one hand, an entity in charge of dealing with the communication with the users is needed, with the aim of signing resource usage contracts and also implementing some renegotiation techniques, among others. On the other hand, some mechanisms should be implemented which decide if the QoS requested could be achieved and, in such case, ensuring that the QoS agreement is provided. One way of increasing the probability of achieving the agreed QoS is by performing meta-scheduling of jobs in advance, that is, jobs are scheduled some time before they are actually executed. In this way, it becomes more likely that the appropriate resources are available to run the jobs when needed. So, this paper presents a framework built on top of Globus and the GridWay meta-scheduler to provide QoS by means of performing meta-scheduling in advance. Thanks to this, QoS requirements of jobs are met (i.e. jobs are finished within a deadline). Apart from that, the mechanisms needed to manage the communication between the users and the system are presented and implemented through SLA contracts based on the WS-Agreement specification

Uma abordagem de reserva antecipada de recursos em ambientes oportunistas

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Ciência da Computação, Florianópolis, 2013.A grade computacional é muito utilizada quando se deseja alto desempenho para resolução de problemas que requerem alto poder de processamento. As grades oportunistas, um tipo de grade computacional, possuem o diferencial de utilizar recursos computacionais ociosos de máquinas pessoais para a resolução destes problemas, o que torna esse ambiente mais barato e, consequentemente, mais interessante, principalmente para a comunidade acadêmica. No entanto, nos ambientes oportunistas a disputa por recursos torna-se maior devido à instabilidade e constante uso de seus recursos. Problemas como o excesso de solicitações de alocação de recursos em um mesmo período podem ser recorrentes, o que pode tanto prejudicar o desempenho do sistema quanto tornar o processo de solicitação de recursos trabalhoso para o usuário, uma vez que este terá que repetir o processo até que haja recursos disponíveis para a sua execução. Uma maneira eficiente de resolver tal problema é com a utilização da reserva antecipada de recursos. Este mecanismo permite que o usuário selecione um conjunto de recursos para que sejam utilizados em um período no futuro, considerando oportunisticamente os recursos disponíveis. Diante disso, esta dissertação propôs a utilização do mecanismo de reserva antecipada em um ambiente de grade oportunista. O objetivo foi melhorar a vazão do uso de recursos oportunistas, de modo a oferecer a possibilidade de alocação dos recursos durante um longo período de tempo, e não apenas no momento da solicitação. Estudos de caso foram realizados para ilustrar o comportamento de um ambiente oportunista com a abordagem proposta, bem como para comparar os ambientes que utilizam e não utilizam reserva antecipada. Os resultados mostraram a eficiência e validade da utilização de tal abordagem em um ambiente distribuído.Abstract : Grid computing is widely used when high performance is desired to resolve problems that require high processing power. Opportunistic grids, a type of grid computing system, have the differential to use idle computing resources of personal machines to solving these problems, making the solution cheaper and consequently more interesting, specially for the academic community. However, opportunistic environments have more competition for resources due to instability and constant use of their resources. Problems such as excessive requests of resources allocation can be recurrent and can both degrade the performance of the system and make the process of resource requests harder to user, once the user will have to repeat this process until there are available resources to the execution. An efficient way to solve this problem is through the use of advanced reservation of resources. This mechanism allows user to select a set of resources to be used in the future opportunistically considering available resources. Therefore, this dissertation proposed the use of the advanced reservation mechanism in an opportunistic grid environment. The goal was to improve the use flow of the opportunistic resources in order to offer the resources allocation possibility for a long period of time and not only at the time of request. Case studies were carried out to illustrate the behaviour of an opportunistic environment with the proposed approach, as well as to compare environments that use with others that do not use advanced reservation. The results show the efficiency and validity of the approach in a distributed environment

Semantic resource management and interoperability between distributed computing platforms

Distributed Computing is the paradigm where the application execution is distributed across different computers connected by a communication network. Distributed Computing platforms have evolved very fast during the las decades: starting from Clusters, where a set of computers were working together in a single location; then evolving to the Grids, where computing resources are shared by different entities, creating a global computing infrastructure which is available to different user communities; and finally becoming in what is currently known as the Cloud, where computing and data resources are provided, on demand, in a very dynamic fashion, and following the Utility Computing model where you pay only for what you consume. Different types of companies and institutions are exploring the potential benefits of moving their IT services and applications to Cloud infrastructures, in order to decouple the management of computing resources from their core business process to become more productive. Nevertheless, migrating software to Clouds is not an easy task, since it requires a deep knowledge of the technology to decompose the application and the capabilities offered by providers and how to use them. Besides this complex deployment process, the current cloud market place has several providers offering resources with different capabilities, prices and quality, and each provider uses their own properties and APIs for describing and accessing their resources. Therefore, when customers want to execute an application in the providers' resources, they must understand the different providers' description, compare them and select the most suitable resources for their interests. Once the provider and resources have been selected, developers have to inter-operate with the different providers' interfaces to perform the application execution steps. To do all the mentioned steps, application developers have to deal with the design and implementation of complex integration procedures. This thesis presents several contributions to overcome the aforementioned problems by providing a platform that facilitates and automates the integration of applications in different providers' infrastructures lowering the barrier of adopting new distributed computing infrastructure such as Clouds. The achievement of this objective has been split in several parts. In the first part, we have studied how semantic web technologies are helping to describe applications and to automatically infer a model for deploying them in a distributed platform. Once the application deployment model has been inferred, the second step is finding the resources to deploy and execute the different application components. Regarding this topic, we have studied how semantic web technologies can be applied in the resource allocation problem. Once the different components have been allocated in the providers' resources, it is time to deploy and execute the application components on these resources by invoking a workflow of provider API calls. However, every provider defines their own management interfaces, so the workflow to perform the same actions is different depending on the selected provider. In this thesis, we propose a framework to automatically infer the workflow of provider interface calls required to perform any resource management tasks. In the last part of the thesis, we have studied how to introduce the benefits of software agents for coordinating the application management in distributed platforms. We propose a multi-agent system which is in charge of coordinating the different steps of the application deployment in a distributed way as well as monitoring the correct execution of the application in the computing resources. The different contributions have been validated with a prototype implementation and a set of use cases.La Computación Distribuida es un paradigma donde la ejecución de aplicaciones se distribuye entre diferentes computadores contados a través de una red de comunicación. Las plataformas de computación distribuida han evolucionado rápidamente durante las últimas décadas, empezando por los "Clusters", donde varios computadores están conectados por una red local; pasando por los "Grids", donde los recursos computacionales son compartidos por varias instituciones creando un red de computación global; llegando finalmente a lo que actualmente conocemos como "Clouds", donde nos podemos proveer de recursos de manera dinámica, bajo demanda y pagando solo por lo que consumimos. Actualmente, varias compañías están descubriendo los beneficios de mover sus aplicaciones a las infraestructuras Cloud, desacoplando la administración de los recursos computacionales de su "core business" para ser más productivos. Sin embargo migrar el software al Cloud no es una tarea fácil porque se requiere un conocimiento exhaustivo de la tecnología y como usar los servicios ofrecidos por los diferentes proveedores. Además cada proveedor ofrece recursos con diferentes capacidades, precios y calidades, con su propia interfaz para acceder a ellos. Por consiguiente, cuando un usuario quiere ejecutar una aplicación en el Cloud, debe entender que ofrece cada proveedor y como usarlo y una vez que ha elegido debe programar los diferentes pasos del despliegue de su aplicación. Si además se quieren usar varios proveedores o cambiar a otro, este proceso debe repetirse varias veces. Esta tesis presenta varias contribuciones para mitigar estos problemas diseñando una plataforma para facilitar y automatizar la integración de aplicaciones en los diferentes proveedores. Estas contribuciones se dividen en varias partes: Primero, el estudio de como las tecnologías semánticas pueden ayudar para describir aplicaciones y automáticamente inferir como se puede desplegar en un plataforma distribuida. Una vez obtenemos este modelo de despliegue, la segunda contribución nos presenta como estas mismas tecnologías pueden usarse para asignar las diferentes partes del despliegue de la aplicación a los recursos de los proveedores. Una vez sabemos la asignación, la siguiente contribución nos resuelve como se puede usar "AI planning" para encontrar la secuencia de servicios que se deben ejecutar para realizar el despliegue deseado. Finalmente, la última parte de la tesis, nos presenta como el despliegue y ejecuciones de las aplicaciones puede coordinarse por un sistema multi-agentes de una manera escalable y distribuida. Las diferentes contribuciones de la tesis han sido validadas mediante la implementación de prototipos y casos de uso

Negotiated resource brokering for quality of service provision of grid applications

Grid Computing is a distributed computing paradigm where many computers often formed from different organisations work together so that their computing power may be aggregated. Grids are often heterogeneous and resources vary significantly in CPU power, available RAM, disk space, OS, architecture and installed software etc. Added to this lack of uniformity is that best effort services are usually offered, as opposed to services that offer guarantees upon completion time via the use of Service Level Agreements (SLAs). The lack of guarantees means the uptake of Grids is stifled. The challenge tackled here is to add such guarantees, thus ensuring users are more willing to use the Grid given an obvious reluctance to pay or contribute, if the quality of the services returned lacks any guarantees. Grids resources are also finite in nature, hence priorities need establishing in order to best meet any guarantees placed upon the limited resources available. An economic approach is hence adopted to ensure end users reveal their true priorities for jobs, whilst also adding incentive for provisioning services, via a service charge. An economically oriented model is therefore proposed that provides SLAs with bicriteria constraints upon time and cost. This model is tested via discrete event simulation and a simulator is presented that is capable of testing the model. An architecture is then established that was developed to utilise the economic model for negotiating SLAs. Finally experimentation is reported upon from the use of the software developed when it was deployed upon a testbed, including admission control and steering of jobs within the Grid. Results are presented that show the interactions and relationship between the time and cost constraints within the model, including transitions between the dominance of one constraint over the other and other things such as the effects of rescheduling upon the market