We present Tapestry, a peer-to-peer overlay routing infrastructure offering efficient, scalable, locationindependent routing of messages directly to nearby copies of an object or service using only localized resources. Tapestry supports a generic Decentralized Object Location and Routing (DOLR) API

for service deployment will facilitate service introduction in both cases.

This article provides an overview of the current Grid Service deployment problems and proposes a general multi layer architecture for service deployment solutions based on the previously published specialised and partially defined ones. From the architectural point of view a service could be a

This thesis first introduces the topological categories of service deployment, namely, continuous and sparse path-based, node-based, fence-based, and combinations thereof. A five-step deployment mechanism of hierarchically distributed computations in the network and node levels is presented

and scale of these systems continues to grow, it becomes increasingly difficult to administer and manage them. At the same time, the service deployment technologies are still based on scripts and configuration files with minimal ability to express dependencies, to document and to verify configurations

As IT services become more powerful and complex, service deployment gets more difficult and expensive. Service deployment, the process of making a service ready for use, often includes deploying multiple, interrelated software components into heterogeneous environments. Different technologies

Manual deployment of the application usually requires expertise both about the underlying system and the application. Automatic service deployment can improve deployment significantly by using on-demand deployment and selfhealing services. To support these features this paper describes an extension

Abstract—Advanced IT solutions allow users to create, organize and share user services and computing resources across a wide range of heterogeneous platforms. This makes managing (updating and deploying) the IT systems considerably more complex. Management tasks are so entangled within the existing

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Wind turbines experience long term fluctuating variable amplitude fatigue loads with occasional large amplitude stochastic peak loads. The fatigue loads are usually characterised by a mean load with a fixed amplitude oscillation superimposed; the stochastic peak loads by modelled peak loads, such as the fifty year gust. A methodology for wind turbine blade monitoring using acoustic emission (AE) detection of damage processes in the structure has been developed by the AEGIS consortium, supported by the European Commission. The methodology has been developed separately for the peak load events and the more usual operational fatigue loading. It can be applied as an enhancement to the conventional blade certification test and has the potential to be adapted to large-scale field application of the techniques on operational wind turbines. Wind turbine blade certification tests are carried out to validate design and production. AE monitoring during all stages of a test can both locate and characterise damage processes in blades, starting with non-audible signals