SOA4All, enabling the SOA revolution on a world wide scale

SOA4All will help to realize a world where billions of parties are exposing and consuming services via advanced Web technology. The outcome of the project will be a comprehensive framework and infrastructure that integrates four complimentary paradigm-shifting technical advances into a coherent and domain independent service delivery platform: Web principles and technology as the underlying infrastructure for the integration of services at a world wide scale; Web 2.0 as a means to structure human-machine cooperation in an efficient and cost effective manner; Semantic Web technology as a means to abstract from syntax to semantics as required for meaningful service discovery; and context management as a way to process in a machine understandable way user needs that facilitate the customization of existing services for the needs of users

Architecture for Analysis of Streaming Data

While several attempts have been made to construct a scalable and flexible architecture for analysis of streaming data, no general model to tackle this task exists. Thus, our goal is to build a scalable and maintainable architecture for performing analytics on streaming data. To reach this goal, we introduce a 7-layered architecture consisting of microservices and publish-subscribe software. Our study shows that this architecture yields a good balance between scalability and maintainability due to high cohesion and low coupling of the solution, as well as asynchronous communication between the layers. This architecture can help practitioners to improve their analytic solutions. It is also of interest to academics, as it is a building block for a general architecture for processing streaming data

A Semantic Data Grid for Satellite Mission Quality Analysis

The combination of Semantic Web and Grid technologies and architectures cases the development of applications that share heterogeneous resource,, (data and computing elements) that belong to several organisations. The Aerospace domain has an extensive and heterogeneous network of facilities and institutions, with a strong need to share both data and computational resources for complex processing tasks. One such task is monitoring and data analysis for Satellite Missions. This paper presents a Semantic Data Grid for satellite missions, where flexibility, scalability, interoperability, extensibility and efficient development have been considered the key issues to be addressed

Semantic Web Services Provisioning

Semantic Web Services constitute an important research area, where vari ous underlying frameworks, such as WSMO and OWL-S, define Semantic Web ontologies to describe Web services, so they can be automatically discovered, composed, and invoked. Service discovery has been traditionally interpreted as a functional filter in current Semantic Web Services frameworks, frequently performed by Description Logics reasoners. However, semantic provisioning has to be performed taking Quality-of-Service (QOS) into account, defining user preferences that enable QOS-aware Semantic Web Service selection. Nowadays, the research focus is actually on QOS-aware processes, so cur rent proposals are developing the field by providing QOS support to semantic provisioning, especially in selection processes. These processes lead to opti mization problems, where the best service among a set of services has to be selected, so Description Logics cannot be used in this context. Furthermore, user preferences has to be semantically defined so they can be used within selection processes. There are several proposals that extend Semantic Web Services frameworks allowing QOS-aware semantic provisioning. However, proposed selection techniques are very coupled with their proposed extensions, most of them being implemented ad hoc. Thus, there is a semantic gap between functional descriptions (usually using WSMO or OWL-S) and user preferences, which are specific for each proposal, using different ontologies or even non-semantic de scriptions, and depending on its corresponding ad hoc selection technique. In this report, we give an overview of most important Semantic Web Ser vices frameworks, showing a comparison between them. Then, a thorough analysis of state-of-the art proposals on QOS-aware semantic provisioning and user preferences descriptions is presented, discussing about their applicabil ity, advantages, and defects. Results from this analysis motivate our research work, which has been already materialized in two early contributions.Los servicios web semánticos constituyen un importante campo de inves tigación, en el cual distintos frameworks, como por ejemplo WSMO y OWL-S, definen ontologías de la web semántica para describir servicios web, de for ma que estos puedan ser descubiertos, compuestos e invocados de manera automática. El descubrimiento de servicios ha sido interpretado tradicional mente como un filtro funcional en los frameworks actuales de servicios web semánticos, usando para ello razonadores de lógica descriptiva. Sin embargo, las tareas de aprovisionamiento semántico deberían tener en cuenta la calidad del servicio, definiendo para ello preferencias de usuario de manera que sea posible realizar una selección de servicios web semánticos sensible a la cali dad. Actualmente, el foco de la investigación está en procesos sensibles a la ca lidad, por lo que las propuestas actuales están trabajando en este campo intro duciendo el soporte adecuado a la calidad del servicio dentro del aprovisio namiento semántico, y principalmente en las tareas de selección. Estas tareas desembocan en problemas de optimización, donde el mejor servicio de entre un concjunto debe ser seleccionado, por lo que las lógicas descriptivas no pue den ser usadas en este contexto. Además, las preferencias de usuario deben ser definidas semánticamente, de forma que puedan ser usadas en las tareas de selección. Existen bastantes propuestas que extienden los frameworks de servicios web semánticos para habilitar el aprovisionamiento sensible a la calidad. Sin embargo, las técnicas de selección propuestas están altamente acopladas con dichas extensiones, donde la mayoría de ellas implementan algoritmos ad hoc. Por tanto, existe un salto semántico entre las descripciones funcionales (nor malmente usando WSMO o OWL-S) y las preferencias de usuario, las cuales son definidas específicamente por cada propuesta, usando ontologías distin tas o incluso descripciones no semánticas que dependen de la correspondiente técnica de selección ad hoc

Digital Ecosystems: Ecosystem-Oriented Architectures

We view Digital Ecosystems to be the digital counterparts of biological ecosystems. Here, we are concerned with the creation of these Digital Ecosystems, exploiting the self-organising properties of biological ecosystems to evolve high-level software applications. Therefore, we created the Digital Ecosystem, a novel optimisation technique inspired by biological ecosystems, where the optimisation works at two levels: a first optimisation, migration of agents which are distributed in a decentralised peer-to-peer network, operating continuously in time; this process feeds a second optimisation based on evolutionary computing that operates locally on single peers and is aimed at finding solutions to satisfy locally relevant constraints. The Digital Ecosystem was then measured experimentally through simulations, with measures originating from theoretical ecology, evaluating its likeness to biological ecosystems. This included its responsiveness to requests for applications from the user base, as a measure of the ecological succession (ecosystem maturity). Overall, we have advanced the understanding of Digital Ecosystems, creating Ecosystem-Oriented Architectures where the word ecosystem is more than just a metaphor.Comment: 39 pages, 26 figures, journa

Building on Quicksand

Reliable systems have always been built out of unreliable components. Early on, the reliable components were small such as mirrored disks or ECC (Error Correcting Codes) in core memory. These systems were designed such that failures of these small components were transparent to the application. Later, the size of the unreliable components grew larger and semantic challenges crept into the application when failures occurred. As the granularity of the unreliable component grows, the latency to communicate with a backup becomes unpalatable. This leads to a more relaxed model for fault tolerance. The primary system will acknowledge the work request and its actions without waiting to ensure that the backup is notified of the work. This improves the responsiveness of the system. There are two implications of asynchronous state capture: 1) Everything promised by the primary is probabilistic. There is always a chance that an untimely failure shortly after the promise results in a backup proceeding without knowledge of the commitment. Hence, nothing is guaranteed! 2) Applications must ensure eventual consistency. Since work may be stuck in the primary after a failure and reappear later, the processing order for work cannot be guaranteed. Platform designers are struggling to make this easier for their applications. Emerging patterns of eventual consistency and probabilistic execution may soon yield a way for applications to express requirements for a "looser" form of consistency while providing availability in the face of ever larger failures. This paper recounts portions of the evolution of these trends, attempts to show the patterns that span these changes, and talks about future directions as we continue to "build on quicksand".Comment: CIDR 200