Juri Papay

Platform-as-a-Service Architecture for Real-Time Quality of Service Management in Clouds

Cloud computing offers the potential to dramatically reduce the cost of software services through the commoditization of information technology assets and on-demand usage patterns. However, the complexity of determining resource provision policies for applications in such complex environments introduces significant inefficiencies and has driven the emergence of a new class of infrastructure called Platform-as-a-Service (PaaS). In this paper, we present a novel PaaS architecture being developed in the EU IST IRMOS project targeting real-time Quality of Service (QoS) guarantees for online interactive multimedia applications. The architecture considers the full service lifecycle including service engineering, service level agreement design, provisioning and monitoring. QoS parameters at both application and infrastructure levels are given specific attention as the basis for provisioning policies in the context of temporal constraints. The generic applicability of the architecture is being verified and validated through implemented scenarios from three important application sectors (film post-production, virtual augmented reality for engineering design, collaborative e-Learning in virtual worlds).

Automating experiments using semantic data in a bioinformatics grid

The transition from laboratory science to in silico e-science has facilitated a paradigmatic shift in the way we conduct modern science. We can use computationally based analytical models to simulate and investigate scientific questions such as those posed by high-energy physics and bioinformatics, yielding high-quality results and discoveries at an unprecedented rate. However, while experimental media have changed, the scientific methodologies and processes we choose for conducting experiments are still relevant. As in the lab environment, experimental methodology requires samples to undergo several processing stages. The staging of operations is what constitutes the in silico experimental process. The use of workflows formalizes earlier ad hoc approaches for representing experimental methodology. We can represent the stages of in silico experiments formally as a set of services to invoke.

Recycling workflows and services through discovery and reuse

Scientific workflows are becoming a valuable tool for scientists to capture and automate e‐Science procedures. Their success brings the opportunity to publish, share, reuse and re‐purpose this explicitly captured knowledge. Within the

Virtualised e-Learning with real-time guarantees on the IRMOS platform

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Towards a Protocol for the Attachment of Semantic Descriptions to Grid Services

Grid project, we have identified key resources that can be shared including complete workflows, fragments of workflows and constituent services. We have examined the alternative ways that these resources can be described by their authors (and subsequent users) and developed a unified descriptive model to support their later discovery. By basing this model on existing standards, we have been able to extend existing Web service and Semantic Web service infrastructure whilst still supporting the specific needs of the e‐Scientist. The

Towards a protocol for the attachment of metadata to grid service descriptions and its use in semantic discovery

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Virtualised e-Learning on the IRMOS real-time Cloud

Grid components enable a workflow life‐cycle that extends beyond execution to include the discovery of previous relevant designs, the reuse of those designs and their subsequent publication. Experience with example groups of scientists indicates that this cycle is valuable. The growing number of workflows and services mean more work is needed to support the user in effective ranking of search results and to support the re‐purposing process. Copyright

Predictive resource management for meta-applications

In this paper we focus on how Quality of Service guarantees are provided to virtualised applications in the Cloud Computing infrastructure that is being developed in the context of the IRMOS1 European Project. Provisioning of proper timeliness guarantees to distributed real-time applications involves the careful use of real-time scheduling mechanisms at the virtual-machine hypervisor level, of QoS-aware networking protocols and of proper design methodologies and tools for stochastic modelling of the application. The paper focuses on how we applied these techniques to a case-study involving a real e-Learning mobile content delivery application that has been integrated into the IRMOS platform and its achieved performance.

Predicting application performance for multi-vendor clouds using dwarf benchmarks

Service discovery in large scale, open distributed systems is difficult because of the need to filter out services suitable to the task at hand from a potentially huge pool of possibilities. Semantic descriptions have been advocated as the key to expressive service discovery, but the most commonly used service descriptions and registry protocols do not support such descriptions in a general manner. In this paper, we present a protocol, its implementation and an api for registering semantic service descriptions and other task/user-specific metadata, and for discovering services according to these. Our approach is based on a mechanism for attaching structured and unstructured metadata, which we show to be applicable to multiple registry technologies. The result is an extremely flexible service registry that can be the basis of a sophisticated semantically-enhanced service discovery engine, an essential component of a Semantic Grid.

The role of performance engineering techniques in the context of the Grid

Service discovery in large scale, open distributed systems is difficult because of the need to filter out services suitable to the task at hand from a potentially huge pool of possibilities. Semantic descriptions have been advocated as the key to expressive service discovery, but the most commonly used service descriptions and registry protocols do not support such descriptions in a general manner. In this paper, we present a protocol, its implementation and an api for registering semantic service descriptions and other task/user-specific metadata, and for discovering services according to these. Our approach is based on a mechanism for attaching structured and unstructured metadata, which we show to be applicable to multiple registry technologies. The result is an extremely flexible service registry that can be the basis of a sophisticated semantically-enhanced service discovery engine, an essential component of a Semantic Grid.