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

Comparison on OpenStack and OpenNebula performance to improve multi-Cloud architecture on cosmological simulation use case

With the increasing numbers of Cloud Service Providers and the migration of the Grids to the Cloud paradigm, it is necessary to be able to leverage these new resources. Moreover, a large class of High Performance Computing (HPC) applications can run these resources without (or with minor) modifications. But using these resources come with the cost of being able to interact with these new resource providers. In this paper we introduce the design of a HPC middleware that is able to use resources coming from an environment that compose of multiple Clouds as well as classical \hpc resources. Using the \diet middleware, we are able to deploy a large-scale, distributed HPC platform that spans across a large pool of resources aggregated from different providers. Furthermore, we hide to the end users the difficulty and complexity of selecting and using these new resources even when new Cloud Service Providers are added to the pool. Finally, we validate the architecture concept through cosmological simulation RAMSES. Thus we give a comparison of 2 well-known Cloud Computing Software: OpenStack and OpenNebula.Avec l'augmentation du nombre de fournisseurs de service Cloud et la migration des applications depuis les grilles de calcul vers le Cloud, il est nécessaire de pouvoir tirer parti de ces nouvelles ressources. De plus, une large classe des applications de calcul haute performance peuvent s'exécuter sur ces ressources sans modifications (ou avec des modifications mineures). Mais utiliser ces ressources vient avec le coût d'être capable d'intéragir avec des nouveaux fournisseurs de ressources. Dans ce papier, nous introduisons la conception d'un nouveau intergiciel HPC qui permet d'utiliser les ressources qui proviennent d'un environement composé de plusieurs Clouds comme des ressources classiques. En utilisant l'intergiciel \diet, nous sommes capable de déployer une plateforme HPC distribuée et large échelle qui s'étend sur un large ensemble de ressources aggrégées entre plusieurs fournisseurs Cloud. De plus, nous cachons à l'utilisateur final la difficulté et la complexité de sélectionner et d'utiliser ces nouvelles ressources quand un nouveau fournisseur de service Cloud est ajouté dans l'ensemble. Finalement, nous validons notre concept d'architecture via une application de simulation cosmologique RAMSES. Et nous fournissons une comparaison entre 2 intergiciels de Cloud: OpenStack et OpenNebula

Security and management policy specification

Accepted versio

Web Service Trust: Towards A Dynamic Assessment Framework

Trust in software services is a key prerequisite for the success and wide adoption of services-oriented computing (SOC) in an open Internet world. However, trust is poorly assessed by existing methods and technologies, especially in dynamically composed and deployed SOC systems. In this paper, we discuss current methods for assessing trust in service-oriented computing and identify gaps of current platforms, in particular with regards to runtime trust assessment. To address these gaps, we propose a model of runtime trust assessment of software services and introduce a framework for realizing the model. A key characteristic of our approach is the support that it offers for customizable assessment of trust based on evidence collected during the operation of software services and its ability to combine this evidence with subjective assessments coming from service clients