Expertise and Trust-Aware Social Web Service Recommendation

With the increasing number of Web services, the personalized recommendation of Web services has become more and more important. Fortunately, the social network popularity nowadays brings a good alternative for social recommendation to avoid the data sparsity problem that is not treated very well in the collaborative filtering approach. Since the social network provides a big data about the users, the trust concept has become necessary to filter this abundance and to foster the successful interactions between the users. In this paper, we firstly propose a trusted friend detection mechanism in a social network. The dynamic of the users’ interactions over time and the similarity of their interests have been considered. Secondly, we propose a Web service social recommendation mechanism which considers the expertise of the trusted friends according to their past invocation histories and the active user’s query. The experiments of each mechanism produced satisfactory results

Automatic Deployment of Services in the Cloud with Aeolus Blender

International audienceWe present Aeolus Blender (Blender in the following), a software product for the automatic deployment and configuration of complex service-based, distributed software systems in the " cloud ". By relying on a configuration optimiser and a deployment planner, Blender fully automates the deployment of real-life applications on OpenStack cloud deployments , by exploiting a knowledge base of software services provided by the Mandriva Armonic tool suite. The final deployment is guaranteed to satisfy not only user requirements and relevant software dependencies , but also to be optimal with respect to the number of used virtual machines

Adaptation of Asynchronously Communicating Software

International audienceSoftware adaptation techniques aim at generating new components called adapters, which make a set of services work correctly together by compensating for existing mismatch. Most approaches assume that services interact synchronously using rendez-vous communication. In this paper, we focus on asynchronous communication, where services interact exchanging messages via buffers. We overview a method for automatically generating adapters in such asynchronous environments

Handling Constraints in Cardinality-Based Feature Models: The Cloud Environment Case Study

Feature modeling is a well-known approach to describe variability in Software Product Lines. Cardinality-based Feature Models (FMs) is a type of FMs where features can be instantiated several times in the configuration, contrarily to boolean FMs where a feature is present or not. While boolean FMs configuration is easily handled by current approaches, there is still a lack of support regarding cardinality-based FMs. In particular, expressing constraints over the set of feature instances is not supported in current approaches, where cardinality involved in such constraints can not be specified. To face this limitation, we define in this paper cardinality-based expressions and provide the related formal syntax and semantics as well as the way to automate the underlying configuration. We study the need for such a support using cloud computing environment configurations as a motivating example. To evaluate the soundness of the proposed approach, we analyze a corpus of 10 cloud environments. Our empirical evaluation shows that constraints relying on our cardinality-based expressions are common and that our approach is effective and can provide an useful support to developers for modeling and reasoning about FMs with cardinalities.La modélisation à l'aide de caractéristiques est une approche très utilisée dans les lignes de produits logiciels. Les Modèles de Caractéristiques (MCs) étendus avec des cardinalités sont un des MCs dans lesquels une caractéristique peut être instanciée plusieurs fois lors de la configuration, contrairement au MCs booléens dans lesquels une caractéristique est présente ou non. Alors que la configuration de MCs booléens est aujourd'hui maitrisée par différentes approches, il reste cependant un manque en terme de support pour les MCs étendus avec des cardinalités. Notamment, pouvoir exprimé des contraintes sur le nombre d'instances requises n'est pas permis dans les approches existantes, puisque les contraintes ne peuvent être exprimées que sur des caractéristiques booléennes. Pour contrer cette limite, nous fournissons dans cet article une nouvelle notation pour exprimer ces contraintes, une définition formelle de leur syntaxe et de leur sémantique ainsi qu'un moyen d'automatiser la vérification des configurations associées. Pour illustrer notre approche, nous étudions le besoin pour un tel support dans le cadre de la configuration d'environnements d'informatique dans les nuages. Nous évaluons notre approche sur un ensemble de 10 environnements. Notre étude empirique montre que les besoins pour exprimer ce type de contraintes sont communs dans ces environnements et que notre approche est efficace pour les gérer

Composing JSON-based Web APIs

International audienceThe development of Web APIs has become a discipline that companies have to master to succeed in the Web. The so-called API economy is pushing companies to provide access to their data by means of Web APIs, thus requiring web developers to study and integrate such APIs into their applications. The exchange of data with these APIs is usually performed by using JSON, a schemaless data format easy for computers to parse and use. While JSON data is easy to read, its structure is implicit, thus entailing serious problems when integrating APIs coming from di erent vendors. Web developers have therefore to understand the domain behind each API and study how they can be composed. We tackle this issue by presenting an approach able to both discover the domain of JSON-based Web APIs, and identify composition links among them. Our approach allows developers to easily visualize what is behind APIs and how they can be composed to be used in their applications

Reasoning on the usage control security policies over data artifact business process models

The inclusion of security aspects in organizations is a crucial aspect to ensure compliance with both internal and external regulations. Business process models are a well-known mechanism to describe and automate the activities of the organizations, which should include security policies to ensure the correct performance of the daily activities. Frequently, these security policies involve complex data which cannot be represented using the standard Business Process Model Notation (BPMN). In this paper, we propose the enrichment of the BPMN with a UML class diagram to describe the data model, that is also combined with security policies defined using the UCONABC framework annotated within the business process model. The integration of the business process model, the data model, and the security policies provides a context where more complex reasoning can be applied about the satisfiability of the security policies in accordance with the business process and data models. To do so, wetransform the original models, including security policies, into the BAUML framework (an artifact-centric approach to business process modelling). Once this is done, it is possible to ensure that there are no inherent errors in the model (verification) and that it fulfils the business requirements (validation), thus ensuring that the business process and the security policies are compatible and that they are aligned with the business security requirements.This work has been supported by Project PID2020-112540RB-C44 funded by MCIN/AEI/ 10.13039/501100011033, Project TIN2017-87610-R funded by MCIN/AEI/10.13039/501100011033 and FEDER “Una manera de hacer Europa”, Project 2017-SGR-1749 by the Generalitat de Catalunya, Projects COPERNICA (P20 01224) and METAMORFOSIS by the Junta de Andalucía.Peer ReviewedPostprint (published version

Elastic Cloud Services Compliance with Gustafson’s and Amdahl’s Laws

Proceedings of: Third International Workshop on Sustainable Ultrascale Computing Systems (NESUS 2016). Sofia (Bulgaria), October, 6-7, 2016.The speedup that can be achieved with parallel and distributed architectures is limited at least by two laws: the Amdahl’s and Gustafson’s laws. The former limits the speedup to a constant value when a fixed size problem is executed on a multiprocessor, while the latter limits the speedup up to its linear value for the fixed time problems, which means that it is limited by the number of used processors. However, a superlinear speedup can be achieved (speedup greater than the number of used processors) due to insufficient memory, while, parallel and, especially distributed systems can even slowdown the execution due to the communication overhead, when compared to the sequential one. Since the cloud performance is uncertain and it can be influenced by available memory and networks, in this paper we investigate if it follows the same speedup pattern as the other traditional distributed systems. The focus is to determine how the elastic cloud services behave in the different scaled environments. We define several scaled systems and we model the corresponding performance indicators. The analysis shows that both laws limit the speedup for a specific range of the input parameters and type of scaling. Even more, the speedup in cloud systems follows the Gustafson’s extreme cases, i.e. insufficient memory and communication bound domains.This work is partially supported by the European Union’s Horizon 2020 research and innovation programme under the grant agreements 644179 ENTICE: dEcentralized repositories for traNsparent and efficienT vIrtual maChine opErations (first two authors) and 643946, CloudLightning: Selforganizing, self-managing Heterogeneous Clouds (fourth author). The authors would like to acknowledge networking support by the COST programme Action IC1305, Network for Sustainable Ultrascale Computing (NESUS).European Commissio