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Data curation deals with managing the data by applying different tasks such as extraction, enrichment, cleaning to fit the purpose of use. Indeed, nowadays, there is an increasing need to implement such tasks in the big data era to maintain data management. Big data is involved in decision processes to perform analysis, visualization, prediction, etc. Thus, there is a dependency between the generated outcomes and the input data of such a process. Therefore, decision process features (e.g., decision context, user constraints, and requirements) need to be taken into account during the data management process, including the data curation phase. Although the proposed curation approaches in the literature are diverse, most of them are static and do not consider the decision process features. Moreover, most of the proposals are dedicated to curating a specific data source format (e.g., structured/unstructured data source). To overcome these limitations, we propose a new approach ACUSEC (Adaptive CUration SErvice Composition) that ensures adaptive curation services composition by considering different features: the source type, the user constraints and preferences, and the decision context. To do so, we rely on AI and machine learning mechanisms such as reinforcement learning. Following the approach's definition, we conducted experiments that show encouraging results in overall execution time and adaptation to the above features.

Data analytics based on the produced data from the Internet of Things (IoT) devices is expected to improve the individuals’ quality of life. However, ensuring security and privacy in the IoT data aggregation process is a non-trivial task. Generally, the IoT data aggregation process is based on centralized servers. Yet, in the case of distributed approaches, it is difficult to coordinate several untrustworthy parties. Fortunately, the blockchain may provide decentralization while overcoming the trust problem. Consequently, blockchain-based IoT data aggregation may become a reasonable choice for the design of a privacy-preserving system. To this end, we propose PrivDA, a Privacy-preserving IoT Data Aggregation scheme based on the blockchain and homomorphic encryption technologies. In the proposed system, each data consumer can create a smart contract and publish both terms of service and requested IoT data. Thus, the smart contract puts together into one group potential data producers that can answer the consumer’s request and chooses one aggregator, the role of which is to compute the group requested result using homomorphic computations. Therefore, group-level aggregation obfuscates IoT data, which complicates sensitive information inference from a single IoT device. Finally, we deploy the proposal on a private Ethereum blockchain and give the performance evaluation.

In this paper, we propose an approach CropWaterNeed in order to estimate and predict the future water needs and maximize the productivity in the irrigated areas. Unfortunately, we have not identified data available to be employed in such machine learning process in order to predict plants water needs. The proposed approach consists of extending the classic machine learning process. Particularly, we define a process to build dataset that contains plant water requirements. To collect data, we extract meteorological data from Climwat database and plants water requirements using Cropwat Tool. Then, we aggregate the extracted data into a dataset. Subsequently, we use the dataset to perform the learning process using XGBRegressor, Decision Tree, Random Forest and Gradiant Boost Regressor. Afterward, we evaluate the model generated by each algorithm by measuring the performance measures such as MSE, RMSE and MAE. Our work shows that the model generated by XGBRegressor is the most efficient in our case while Random Forest is the least efficient. As future work, we aim to apply the proposed process to test the performance of other regression algorithms and to test the impact of using deep learning techniques with the extracted data.

This paper presents thingsourcing to enable thing collaboration in the context of IoT. Compared to crowdsourcing that refers to a crowd of persons, there is limited research in thingsourcing which deprives things from participating in complex business applications. In this paper, thingsourcing is associated with a platform that acts as an IoT marketplace where things sign-up and sign-off looking for opportunities to complete users’ demands. The platform also has a set of mechanisms that allow to describe, search for, and “glue” things together. For demonstration purposes a car service center is used illustrating how things like service bays and vehicles collaborate in compliance with scripts defined in ComPOS (Composition language for Palcom Oblivious Services).

Purpose The quality of a Business Process (BP) model is vital for the successful accomplishment of all its lifecycle phases. Indeed, a high-quality BP model makes its implementation, execution and evaluation easier. In the literature, the improvement of BP model quality has been dealt with using several techniques. For instance, modeling guidelines, refactoring techniques, and transformation rules are the most used ones. The purpose of this paper is to exploit existing initiatives in this field to help designers improve their BP models. Design/methodology/approach This paper draws up a systematic inventory of the existing approaches to improve the quality of BP models. Moreover, it provides a comparative evaluation with the aim of identifying the particularities of each approach as well as the common gaps in the state of the art. Finally, it proposes a guiding framework, called BP-Quality, that supports designers in improving the quality of their BP models. Findings The usability of BP-Quality is illustrated through a case study and a set of experiments. The preliminary experimental evaluation of this guiding framework shows encouraging results. Originality/value The proposed guiding framework has the merit of exploiting existing initiatives in the field of BP quality improvement. In addition, it customizes and optimizes the quality improvement process according to the particularities of each BP model.

Nowadays, with the increasing number of data sources, especially in environmental domain, earth observation programs face major challenges for environmental data exploitation, mainly due to data sources heterogeneity of different types such as access techniques, used protocols, languages, data formats, etc. Although typical solutions abstract from this heterogeneity with a layer of data services, the development of such systems remains tedious in this context. In this paper, we propose an approach based on Model-Driven Engineering (MDE) combined with semantic annotations, to automate data service development on top of data sources. Our work contributes to the development of integrated service-based architectures driven by automatic service generation, data integration from existing environmental systems and automatic service annotations. Our solution, applied to the detection of natural disasters, provides 1) appropriate modelling of data sources and services to apply model-to-text (M2T) transformations, 2) automatic generation of Representational State Transfer (REST) data service code template, 3) automatic generation of semantically annotated Hypermedia-based descriptors of these services. We have implemented and evaluated our solution with a set of real data sources provided by the Sahara and Sahel Observatory (OSS), OpenWeatherMap and CHIRPS.

International audience; Internet of Things-based environments collect and generate huge amounts of data about users, their activities, and their surroundings , which can disclose some sensitive information and threaten their privacy. Hence, the user's collected and handled data by IoT-based applications need to be exploited and secured in an appropriate way to protect personal data and user's privacy. Therefore, we aim at improving the data ownership, transparency, and auditability for users. To this end, we propose an end-to-end privacy-preserving framework for the IoT data using blockchain technology. The smart contract use in our framework will hence enforce the privacy requirement compliance according to the user's (i.e., data owner) privacy preferences and end-user's (i.e., data consumer) requests. To do so, we detail the design of the system architecture by introducing its core components and functionalities and highlight through an example of how it operates in a real-world use-case.

International audience; The increasing volume of data generated by earth observation programs such as Copernicus, NOAA, and NASA Earth Data, is overwhelming. Although these programs are very costly, data usage remains limited due to lack of interoperability and data linking. In fact, multi-source and heterogeneous data exploitation could be significantly improved in different domains especially in the natural disaster prediction one. To deal with this issue, we introduce the PREDICAT project that aims at providing a semantic service-oriented platform to PREDIct natural CATastrophes. The PREDICAT platform considers (1) data access based on web service technology; (2) ontology-based interoperability for the environmental monitoring domain; (3) data integration and linking via big data techniques; (4) a prediction approach based on semantic machine learning mechanisms. The focus in this paper is to provide an overview of the PREDICAT platform architecture. A scenario explaining the operation of the platform is presented based on data provided by our collaborators, including the international intergovernmental Sahara and Sahel Observatory (OSS).

Like any software product, the quality of Business Process (BP) models is an important issue that must be addressed. Indeed, a poor-quality BP model can disturb its implementation and execution as well as its performance. In the literature, different studies focused on the evaluation of BP model's quality using quality metrics. The common challenge highlighted by these studies is the lack of a consensus on the thresholds of the used quality metrics and the difficulty of interpreting the values of these metrics. In this paper, we propose an approach that uses existing quality metrics to evaluate the quality of BP models in terms of comprehensibility and modifiability. Besides, we determine the thresholds of the different quality metrics through decision tree technique. Decision tree also produces a set of decision rules that are useful to determine the quality level of BP model. The approach is validated through a tool named BP-Quality that calculates the values of the quality metrics and deduces the comprehensibility and modifiability levels based on calculated values and the aforementioned thresholds.

Composite software as a service (SaaS)-based SOA offers opportunities for enterprises to offer value-added services. The cornerstone for such a business is service level agreements between Cloud customers and Cloud providers. In spite of the hype surrounding composite SaaS, standardized methods that enable a reliable management of service level agreements starting from the SLA derivation from the customer requirements to the SLA establishment between the two stockholders are still missing. To overcome such a drawback, we propose a method for SLA establishment guided by QoS for composite SaaS. Our method provides: (1) a requirement specification language for the Cloud customer to define the composition schemas of the requested services along with its QoS constraints; (2) a Cloud provider offer specification language and method to help in identifying the services and resources that satisfy the customer requirements; and (3) an SLA document definition language and method to specify a deployable composite SaaS on the Cloud. Our approach for SLA establishment embraces model-driven architecture principles to automate the SLA document generation from the customer requirements document. The automation is handled through model transformations along with enrichment algorithms to ensure the generation of complete SLA documents.

The Internet of Things paradigm has brought opportunities to meet several challenges by interconnecting IoT resources, such as sensors, actuators, and gateways on a massive scale. The IoT gateways play an important role in the IoT applications to bridge between sensor networks and the external environment through the Internet. Typically, the IoT gateways collect and send the data collected from sensors and actuators to external platforms where they will be remotely analyzed. However, the users desire a more adapted IoT gateway that can improve the IoT data privacy preservation before sending them to these external platforms. Thus, an IoT gateway that enables a better control over the set of private IoT resources and protects the collected personal data and their privacy is required. For this purpose, we propose a Semantic IoT Gateway that helps implement a dynamic and flexible privacy-preserving solution for the IoT domain. First, it enables to match between the data consumer’s terms of service and the data owner’s privacy preferences by generating an adapted privacy policy. Second, it converts the privacy policy into a custom smart contract. Finally, it connects a set of private IoT resources to a distributed network using the blockchain technology to host the generated smart contracts. A smart contract is an executable code that runs on top of the blockchain to facilitate, execute and enforce an agreement between untrusted parties without the involvement of a trusted third party. Our proposal, which is highlighted through an example and experimentation on a real-world use-case, has given the expected results.

International audience; The Internet of Things (IoT) emerged as a paradigm in which smart things collaborate among them and with other physical and virtual objects using the Internet in order to perform high level tasks. These things appear in a variety of application domains, including smart grid, health care and smart spaces where several parties share data in order to tackle specific tasks. Data in such domains are rich in sensitive data and data owner-specific habits. Thus, IoT raises concerns about privacy and data protection. This paper reports on a systematic literature review of privacy preserving solutions used in Cooperative Information Systems (CIS) in the IoT field. To do so, and after retrieving scientific productions on the subject, we classify the results according to several facets. In this paper, we consider a subset of them: (i) data life cycle, (ii) privacy preserving techniques and (iii) ISO privacy principles. We combine the facets then express and analyze the results as bubble charts. We analyze the proposed solutions in terms of the techniques they deployed and the privacy principles they covered according to the ISO standard and the data privacy laws and regulations of the European Commission on the Protection of Personal Data. Finally, we identifies recommendations to involve privacy principle coverage and security requirement fulfillment in the IoT applications.

International audience; A configurable process model is a generic model from which an enterprise can derive and execute process variants that meet its specific needs and contexts. With the advent of cloud computing and its economic pay-per-use model, enterprises are increasingly outsourcing partially or totally their process variants to cloud providers, and recently to cloud federations. A main challenge in this regard is to allocate optimally cloud resources to the process variants' activities. More specifically, an enterprise may be interested in outsourcing only those that result in an optimal deployment. Due to the diversity of the enterprise QoS requirements, the heterogeneity of resources offered by the cloud federation and the large number of possible configurations in a configurable process model, finding the optimal process variant deployment becomes a highly challenging problem. In this paper, we propose a novel approach to solve this problem through a binary/(0-1) linear program with a quadratic objective function under a set of constraints pertinent to both the enterprise and cloud federation requirements. Our prototypical implementation demonstrates the feasibility and the results of our experiments highlight the effectiveness of our proposed solution

The anterior temporal lobes (ATLs) have been consistently associated with semantic processing which, in turn, has a key role in reading aloud single words. This study aimed to investigate (1) the reading abilities in patients with the semantic variant of primary progressive aphasia (svPPA), and (2) the relationship between gray matter (GM) volume of the left ATL and word reading performance using voxel-based morphometry (VBM). Three groups of participants (svPPA, Alzheimer’s Disease, AD and healthy elderly adults) performed a reading task with exception words, regular words and pseudowords, along with a structural magnetic resonance imaging scan. For exception words, the svPPA group had a lower accuracy and a greater number of regularization errors as compared to the control groups of healthy participants and AD patients. Similarly, for regular words, svPPA patients had a lower accuracy in comparison with AD patients, and a greater number of errors related to complex orthography-to-phonology mappings (OPM) in comparison to both control groups. VBM analyses revealed that GM volume of the left ATL was associated with the number of regularization errors. Also, GM volume of the left lateral ATL was associated with the number of errors with complex OPM during regular word reading. Our results suggest that the left ATL might play a role in the reading of exception words, in accordance with its role in semantic processing. Results further support the involvement of the left lateral ATL in combinatorial processes, including the integration of semantic and phonological information, for both exception and regular words.

Cloud computing has been recently empowered with a new service offering called Containers-as-a-Service (CaaS). This offers horizontally scalable, deployable systems and it bypasses high-performance challenges of traditional hypervisors when deploying applications. This paper assists in using CaaS for business process outsourcing to the cloud–an emerging trend that still faces several problems. In particular, this paper concentrates on the resource allocation problem from an enterprise perspective and proposes a linear program (LP) that finds out the optimal deployment of a business process on cloud containers. The herein reported experimental results show the effectiveness and performance of the LP compared to both the classic deployment (VM-based deployment) and the container First Fit strategy.

International audience; Cloud computing is transforming the way enterprises purchase and manage computing resources, on the one hand and increasing robustness, scalability and security aspects (Gartner, 2012), on the other hand. Recently, providers have been moving towards multi-clouds, inter-cloud or cloud-of-clouds environments. Multi-cloud computing promised to support very large-scale, worldwide, distributed applications using multiple and independent cloud environments. However, multi-cloud computing has to face several key challenges such as interoperability, portability, provisioning, elasticity, high availability and security. These challenges increase the call for security governance in such environments. Even though some researches have been achieved in the multi-cloud security field, it is necessary to assess the current state of research and practice its security governance. This paper aims to categorize the existing works about related to the security governance in multi-cloud environments by applying a systematic mapping study methodology in order to identify trends and future directions. Our results prove that multi-clouds security governance seems to be a promising area in the multi-cloud research and evaluation.

The ability to develop flexible business applications is one of the ultimate objectives behind the use of Web services. Before taking part in such applications, each Web service should be modeled so that service engineers can monitor its execution and identify and address design problems early on. The authors propose a novel approach for modeling Web services that distinguishes operational behavior, which defines the business logic underpinning the Web service's functioning, and control behavior, which guides the operational behavior's execution progress by identifying the actions to take and the constraints to satisfy. The authors' prototype system assists service engineers in specifying, enforcing, and monitoring these behaviors, thereby achieving a better design.

The co-occurrence of semantic impairment and surface dyslexia in the semantic variant of primary progressive aphasia (svPPA) has often been taken as supporting evidence for the central role of semantics in visual word processing. According to connectionist models, semantic access is needed to accurately read irregular words. They also postulate that reliance on semantics is necessary to perform the lexical decision task under certain circumstances (for example, when the stimulus list comprises pseudohomophones). In the present study, we report two svPPA cases: M.F. who presented with surface dyslexia but performed accurately on the lexical decision task with pseudohomophones, and R.L. who showed no surface dyslexia but performed below the normal range on the lexical decision task with pseudohomophones. This double dissociation between reading and lexical decision with pseudohomophones is in line with the dual-route cascaded (DRC) model of reading. According to this model, impairments in visual word processing in svPPA are not necessarily associated with the semantic deficits characterizing this disease. Our findings also call into question the central role given to semantics in visual word processing within the connectionist account.

Face to the increasingly stringent business competition, Small and Medium Sized Enterprises (SMEs) strive to excel in the marketplace by adopting different strategies and solutions. Outsourcing their business processes to the Cloud is considered as a widely adopted strategy. Among others, SMEs outsource their related business process to improve their performance. However, this strategy is not without inconvenience especially when the decision is taken without being aware of the business process requirements and the experts preferences. This paper's major contributions are: the proposition of a monitoring tool to identify the defaulting activities causing the degradation of the business process performance. These information are used later to favor the outsourcing of defaulting activities as the Cloud environment may be a better alternative environment instead of the enterprise one as it can provide a better IT infrastructure with lower cost compared to the in-house one. Furthermore, we propose a decision model using the Analytic Hierarchy Process (AHP) to assist experts in the fastidious task of selecting suitable activity to be outsourced according to the identified requirements and the experts preferences. It resorts essentially to commonly used standards which make it a powerful tool for both IT and business experts. An evaluation of the results is elaborated to insure the utility of the elaborated tool using the CloudSim toolkit.

When outsourcing BPEL process in the Cloud, the decentralization of its execution can resolve any QoS degradation inherent to the centralized execution. Each task within the BPEL process can be executed on a virtual machine (VM) then all tasks are orchestrated together to respect the business process logic constraint represented through the tasks’ dependencies and communication requirements. The BPEL process decentralization must account for a set of contextual information such as the dynamic availability of the Cloud provider’s resources and the customer QoS preferences. So, in this paper, we present a decentralization approach which accounts for several essential factors that best represent the context of the BPEL process when it is outsourced into the Cloud in order to dynamically adapts its initial configuration.

Blending Web 2.0 technologies with enterprise information systems is setting up the stage for a new generation of information systems that will help enterprises open up new communication channels with their stakeholders. Contrary to traditional enterprises with top-down command flow and bottom-up feedback flow, the same flows in Enterprise 2.0 cross all levels and in all directions bringing people together in the development of creative and innovative ideas. The power of Web 2.0 technologies stems from their ability to capture real-world phenomena such as collaboration, competition, and partnership that can be converted into useful and structured information sources from which enterprises can draw information about markets’ trends, consumers’ habits, suppliers’ strategies, etc. This paper discusses the research efforts that our international research group has put into the topic of Enterprise 2.0 (aka Social Enterprise). In particular, our research group advocates that existing practices for managing enterprise information systems need to be re-visited in a way that permits to capture social relations that arise inside and outside the enterprise, to establish guidelines and techniques to assist IT practitioners integrate social relations into their design, development, and maintenance efforts of these information systems, and last but not least to identify and tackle challenges that prevent capturing social relations.

International audience; Cloud computing is a revolutionary paradigm which enables on-demand provisioning of computing resources. Resources are delivered to cloud consumers in the form of infrastructure, platform and software services. These resources are deployed on three different models: private clouds, public clouds and hybrid clouds. In hybrid cloud context, private clouds externalize resources and invoke services from a public cloud when needed. However, in such a specific inter-cloud environment risks may arise. In fact, private cloud users often interact with cloud providers for services provisioning such as infrastructure, platforms and software. However, they are not sufficiently assured about how credible the data computed by these resources they have entrusted. This is due to clouds autonomy preservation, difference in control policy definitions and lack of transparency in clouds. In this paper, we propose a preventive/detective approach for assessing private cloud to select a trustworthy public cloud service. The solution is based on a mediation as a service that ensures the role of trust manager for the private cloud.

This paper discusses how social Web services are held responsible for the actions they take at run time. Compared to (regular) Web services, social Web services perform different actions, for instance establishing and maintaining networks of contacts and forming with some privileged contacts strong and long lasting collaborative groups. Assessing these actions' outcomes, to avoid any violation, occurs through commitments that the social Web services are required to bind to. Two types of commitments are identified: social commitments that guarantee the proper use of the social networks in which the social Web services sign up, and business commitments that guarantee the proper development of composite Web services in response to users' requests. Detecting commitment violation and action prohibition using monitoring results in imposing sanctions on the “guilty” social Web services and taking corrective actions. A system for commitment management in terms of definition, binding, monitoring, and violation detection is also discussed in this paper.

Existing approaches on Web services privacy dominate solutions from a users’ perspective, giving little consideration to the preferences of Web service providers. The integration of service providers’ preferences into Web services’ operations is discussed in this paper. A Web service provider indicates peer Web services that it could interact with as well as the data that they could exchange with. We focus on Privacy and (trust) Partnership preferences based on which, we develop a Specification for Privacy and Partnership Preferences (S3P). This specification suggests a list of exceptional actions to deploy at run-time when these preferences are not met. An integration model of these preferences into Web services design is illustrated throughout a running scenario, and an implementation framework proves the S3P concept. Index Terms—Composition, Partnership, Privacy, Preference, Web service.

This paper examines capacity-driven Web services from a transactional perspective. Such services are empowered with different sets of operations that are selectively triggered in response to requirements posed on them and hence, need to be satisfied. Each set of operations forms a capacity that either fails or succeeds at run-time. In case of failure and for the sake of business continuity, a capacity driven Web service binds to some transactional properties such as pivot, retriable, and compensatable, and behaves in accordance with the guidelines that each transactional property sets. This paper, also, shows that the particular nature of capacity-driven Web services calls for reviewing these transactional properties’ guidelines.

International audience; This paper presents the concepts, definitions, issues, and solutions that revolve around the adoption of capacity-driven Web services. Because of the intrinsic characteristics of these Web services compared to regular (i.e., mono-capacity) Web services, they are examined in a different way and across four steps denoted by description, discovery, composition, and enactment. Implemented as operations to execute at run-time, the capacities that empower a Web service are selected with respect to requirements put on this Web service such as data quality and network bandwidth, and hence need to be satisfied through these capacities. In addition, this paper reports on first, the experiments that were conducted to demonstrate the feasibility of capacity-driven Web services and second, the research opportunities that will be pursued in the future.

Web services are increasingly becoming the de facto implementation for the service-oriented architecture paradigm for enterprises due to their ease of use. Nevertheless, discovering these Web services is still hindered by many challenges that are partially attributed to shortcomings found in the discovery registry models (e.g., UDDI) used nowadays. These registries do not, for example, capture the rich information resulting from the various types of interactions between Web services. To address these shortcomings, and inspired by the conventional human social networks on the net, like Facebook and Twitter, we develop LinkedWS , a social networks discovery model to capture the different interactions that occur between Web services. Based on these interactions, specialized relationships are spawned and discerned. Examples of these relationships are collaboration and substitution. This paper describes LinkedWS and its potential, and reports on its implementation status.

International audience; Since the beginning of the Service-Oriented Architecture (SOA) paradigm, with its various implementation technologies such as Web services, the focus of industrial communities has been on providing tools that would allow seamless and flexible application integration within and across enterprises' boundaries. In this paper, the authors present a Context-based, Service-oriented Modeling and Analysis (CSMA) method that guides service engineers in their choices of identifying, defining, and analyzing adaptable business services. The proposed method is business centric and comprises a set of structured steps grouped in two phases. Besides, the CSMA embraces Model-Driven Architecture (MDA) principles to model and refine adaptable business services models in the PIM level. The results from a pilot validation of CSMA for SOA enablement of a realistic enterprise training solutions are also presented.

This chapter discusses the use of social networks in Web services with focus on the discovery stage that characterizes the life cycle of these Web services. Other stages in this life cycle include description, publication, invocation, and composition. Web services are software applications that end users or other peers can invoke and compose to satisfy different needs such as hotel booking and car rental. Discovering the relevant Web services is, and continues to be, a major challenge due to the dynamic nature of these Web services. Indeed, Web services appear/disappear or suspend/resume operations without prior notice. Traditional discovery techniques are based on registries such as Universal Description, Discovery and Integration (UDDI) and Electronic Business using eXtensible Markup Language (ebXML). Unfortunately, despite the different improvements that these techniques have been subject to, they still suffer from various limitations that could slow down the acceptance trend of Web services by the IT community. Social networks seem to offer solutions to some of these limitations but raise, at the same time, some issues that are discussed in this chapter. The contributions of this chapter are three: social network definition in the particular context of Web services; mechanisms that support Web services build, use, and maintain their respective social networks; and social networks adoption to discover Web services.

This paper introduces a novel approach for modelling and specifying behaviors of Web services. This approach excludes Web services from any composition scenario and sheds the light on two types of behaviors: control and operational. The control behavior illustrates the business logic that underpins the functioning of a Web service, and the operational behavior regulates the execution progress of this control behavior by stating the actions to carry out and the constraints to put on this progress. To synchronize both behaviors at run-time, conversational messages are developed and permit conveying various details between these two behaviors. A prototype showing the use of these conversational messages is presented in this paper as well.

International audience; This paper discusses Web services synchronization at the composition level. Synchronization aims at assisting independent parties coordinate their actions and thus, avoid conflicts. Our previous work on synchronization primarily focussed on the component level and shed the light on two types of behaviors related to specifying Web services. The operational behavior defines the business logic that underpins the functioning of a Web service, and the control behavior regulates the execution progress of this operational behavior by stating the actions to carry out and the constraints to put on this progress. Operational and control behaviors continue to be used to specify composite Web services with respect to the orchestration schemas that these composite Web services have to comply with whether centralized or peer-to-peer. As a result, various types of messages to achieve synchronization are developed per type of orchestration schema. Experiments showing the use of these messages are reported in this paper as well.

Smart homes can assist their inhabitants with mental and physical tasks, and monitor their safety and health. However, the systems that empower such homes use sensitive information that could be misused by external systems resulting in violations of the inhabitants' privacy. In this paper, we introduce a Web services-centric solution to handle privacy concerns. Web services provide the functionalities that allow users remotely interact with the systems empowering the smart homes. In addition the solution uses policies to control how Web services handle privacy concerns and penalize those Web services that do not bind to these policies. Moreover the solution uses trust and reputation to select the most trustworthy Web services.

Nowadays, a Service Oriented Architecture (SOA) seems to be one of the most promising paradigms for leveraging enterprise information systems. SOA creates opportunities for enterprises to provide value added service tailored for on demand enterprise collaboration. With the emergence and rapid development of Web services technologies, SOA is being paid increasing attention and has become widespread. In spite of the popularity of SOA, a standardized framework for modeling and implementing business services are still in progress. For the purpose of supporting these service-oriented solutions, we adopt a model driven development approach. This paper outlines the Contextual Service Oriented Modeling and Analysis (CSOMA) methodology and presents UML profiles for the PIM level service-oriented architectural modeling, as well as its corresponding meta-models. The proposed PIM (Platform Independent Model) describes the business SOA at a high level of abstraction regardless of techniques involved in the application employment. In addition, all essential service-specific concerns required for delivering quality and context-aware service are covered. Some of the advantages of this approach are that it is generic and thus not closely allied with Web service technology as well as specifically treating the service adaptability during the design stage.

International audience; Examining interactions between Web services is of paramount importance to the success of service composition. We have previously proposed a 2-layer framework for modeling, analyzing, and managing these interactions. Interactions are assigned to two layers: business logic and support. The business-logic layer comprises control and transactional flows, whereas the support layer comprises exception and message flows. This paper continues this research effort by focusing on the synchronization of the four flows at run-time. In particular, we discuss the synchronization mechanisms integrated into the 2-layer framework and report our preliminary experiments on the implementation.

International audience; This paper is an overview of how capacity-driven Web services are defined and put into action. Because of the specificities of these Web services compared to regular (i.e., mono-capacity) Web services, the way they are looked into is different and occurs through four steps known as description, discovery, composition, and enactment. A Web service that is empowered with several capacities, that are in fact operations to execute, has to know which capacity out of several it has to choose and then, trigger at run-time. For this purpose, this Web service takes into account the requirements like data and network that are put on each capacity it was empowered with. A feasibility discussion on the implementation of capacity-driven Web services is presented in this paper, as well.

ISBN: 978-1-59593-937-1; International audience; Web services are becoming an essential support for inter-enterprise collaborative business process. Nevertheless, in spite of the crucial progress in Web service technologies there is some shortage especially in the discovery and selection phase. In fact, Web services are selected based on functional criteria. But, in the case of business process collaboration there is a need to consider more pragmatic criteria such as context parameters. In this work we present a framework for collaboration process creation. It enables Web services selection based on contextual description. For this end, we present a novel categorization for the context suitable to the inter-enterprise collaboration. The context categorization is represented using a flexible and dynamic ontology-based model. In order to enhance Web service selection and to improve the manageability of a high number of Web services, we use the community concept in order to gather specific domain Web services. The presented framework uses abstract templates called Goal templates to insure an abstract description of required web services. Goal templates gather both functional and contextual parameters used to select suitable services.

Advanced Information Systems Engineering,; International audience; This paper proposes an architecture for a high-level structure called Service Domain which orchestrates a set a of related IT services based on BPEL specification. Service Domain was developed to enhance the Web service concept to suit e-business collaboration. Service Domains are developed to be context aware. Our approach highlights the benefits of bringing Aspect Oriented Programming to ensure context aware services. Thus, context awareness is guaranteed by enhancing BPEL execution using Aspect oriented paradigms. The proposed approach is illustrated with a running example that shows how Service Domain presents different behaviours according to the context changes.

This paper looks into the coordination of web services following their acceptance to participate in a composition scenario. We identify two types of behaviours associated with component web services: operational and control behaviours. These behaviours are used to specify composite web services that are built upon component web services. In term of orchestration a composite web service could be either centralised or peer-to-peer. To support component/composite web services coordination per type of orchestration schema, various types of messages are exchanged between these web services. Experiments showing the use of these messages are reported in this paper as well.

Web service composition builds a new value-added web service using existing web services. A web service may have many implementations, all of which have the same functionality, but may have different Quality of Service (QoS) values. Hence, a challenging issue of web service composition is how to meet QoS and to fulfil cloud customers' expectations and preferences in the inherently dynamic environment of the Cloud. Addressing the QoS based web service selection and resource allocation is the focus of this paper. This challenge is a multi-objective optimization problem. To tackle this complex problem, we propose a new Penalty Genetic Algorithm (PGA) to help a Cloud provider quickly determine a set of services that compose the workflow of the composite web service. The proposed approach aims to, at the one hand, meet QoS constraints prioritized by the Cloud customer and, at the other hand, respect the resource constraints of the Cloud provider. To the best of our knowledge, this is the first attempt to handle the problem of the optimal selection of web services while taking into account the resource allocation in order to guarantee the QoS imposed by the Cloud customer and to maximize the profit of the Cloud provider. The experimental results of Penalty Genetic Algorithm show that it outperforms the Integer Programming method when the number of web services and the number of resources are large.