04451 Abstracts Collection -- Future Generation Grids

The Dagstuhl Seminar 04451 "Future Generation Grid" was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl from 1st to 5th November 2004. The focus of the seminar was on open problems and future challenges in the design of next generation Grid systems. A total of 45 participants presented their current projects, research plans, and new ideas in the area of Grid technologies. Several evening sessions with vivid discussions on future trends complemented the talks. This report gives an overview of the background and the findings of the seminar

Management of Cloud systems applied to eHealth

This thesis explores techniques, models and algorithms for an efficient management of Cloud systems and how to apply them to the healthcare sector in order to improve current treatments. It presents two Cloud-based eHealth applications to telemonitor and control smoke-quitting and hypertensive patients. Different Cloud-based models were obtained and used to develop a Cloudbased infrastructure where these applications are deployed. The results show that these applications improve current treatments and that can be scaled as computing requirements grow. Multiple Cloud architectures and models were analyzed and then implemented using different techniques and scenarios. The Smoking Patient Control (S-PC) tool was deployed and tested in a real environment, showing a 28.4% increase in long-term abstinence. The Hypertension Patient Control (H-PC) tool, was successfully designed and implemented, and the computing boundaries were measuredAquesta tesi explora tèniques, models i algorismes per una gestió eficient en sistemes al Núvol i com aplicar-ho en el sector de la salut per tal de millorar els tractaments actuals. Presenta dues aplicacions de salut electrònica basades en el Núvol per telemonitoritzar i controlar pacients fumadors i hipertensos. S'ha obtingut diferents models basats en el Núvol i s'han utilitzat per a desenvolupar una infraestructura on desplegar aquestes aplicacions. Els resultats mostren que aquestes aplicacions milloren els tractaments actuals així com escalen a mesura que els requeriments computacionals augmenten. Múltiples arquitectures i models han estat analitzats i implementats utilitzant diferents tècniques i escenaris. L'aplicació Smoking Patient Control (S-PC) ha estat desplegada i provada en un entorn real, aconseguint un augment del 28,4% en l'absistinència a llarg termini de pacients fumadors. L'aplicació Hypertension Patient Control (H-PC) ha estat dissenyada i implementada amb èxit, i els seus límits computacionals han estat mesurats.Esta tesis explora ténicas, modelos y algoritmos para una gestión eficiente de sistemas en la Nube y como aplicarlo en el sector de la salud con el fin de mejorar los tratamientos actuales. Presenta dos aplicaciones de salud electrónica basadas en la Nube para telemonitorizar y controlar pacientes fumadores e hipertensos. Se han obtenido diferentes modelos basados en la Nube y se han utilizado para desarrollar una infraestructura donde desplegar estas aplicaciones. Los resultados muestran que estas aplicaciones mejoran los tratamientos actuales así como escalan a medida que los requerimientos computacionales aumentan. Múltiples arquitecturas y modelos han sido analizados e implementados utilizando diferentes técnicas y escenarios. La aplicación Smoking Patient Control (S-PC) se ha desplegado y provado en un entorno real, consiguiendo un aumento del 28,4% en la abstinencia a largo plazo de pacientes fumadores. La aplicación Hypertension Patient Control (H-PC) ha sido diseñada e implementada con éxito, y sus límites computacionales han sido medidos

Investigating into Cloud Resource Management Mechanisms

Driven by the rapid growth of the demand for efficient and economical computational power, cloud computing has led the world into a new era. It delivers computing resources as services, whereby shared resources are provided to cloud users over the network in order to offer dynamic flexible resource provisioning for reliable and guaranteed services by using pay-as-you-use pricing model. Since multiple cloud users can request cloud resources simultaneously, cloud resource management mechanisms must operate in an efficient manner to satisfy demand of cloud users. Therefore, investigating cloud resource management mechanisms to achieve cloud resource efficiency is one of key elements that benefits both cloud providers and users. In this thesis, we present cloud resource management mechanisms for two different cloud infrastructures, i.e. virtual machine-based (VM-based) and application-based infrastructure. The VM-based infrastructure is an infrastructure that provides multi-tenancy for cloud users at VM-level, i.e. each cloud user directly controls their VMs in the cloud environment. The application-based infrastructure provides multi-tenancy at application level, in the other word, each cloud user directly control their applications in the cloud environment. For the VM-based infrastructure, we introduce two heuristics metrics to capture multi-dimensional characteristics of logical machines. By using a multivariate probabilistic model, we develop an algorithm to improve resource utilisation for the VM-based infrastructure. We then designed and implemented an application-based infrastructure called Elastic Application Container system (EAC system) to support multi-tenant cloud use. Based on the characteristics of the application-based and the VM-based infrastructure, we developed auto-scaling algorithms that can automatically scale cloud resources in the EAC system. In general, the cloud resource management mechanisms proposed in this thesis aims to investigate resource management mechanisms for cloud resource utilisation in the VM-based infrastructure and to provide suitable cloud resource provisioning mechanisms for the application-based infrastructure.Imperial Users Onl