Cloud Computing, as a distributed computing paradigm, consists of the provisioning of infrastructure, platform, and software resources as services. This paradigm is being increasingly used for the deployment and execution of service-based business processes. To efficiently manage them according to the autonomic computing paradigm, service-based business processes can be associated with autonomic managers that monitor these processes, analyze monitoring data, plan configuration actions, and execute these actions on these processes. Although, during these last years, autonomic management of cloud services has received increasing attention, the optimization of autonomic managers to be assigned to cloud services remains not well explored. In fact, almost all the existing solutions on autonomic computing have been interested in modeling and implementing autonomic mechanisms without making any effort to optimize the number of used autonomic managers. Moreover, when it comes to large service-based business processes, optimization of management resources becomes a critical issue. To overcome this issue, we present in this paper a novel approach to determine how many autonomic managers to use for the management of large service-based business processes in order to minimize their cost while avoiding management bottlenecks. Experiments conducted on three different types of datasets highlight the effectiveness of our approach.

The Service-Oriented Computing (SOC) paradigm has evolved over the years to be a comprehensive, interdisciplinary methodology for modern software development.It has gone beyond just a "software componentization technology" to embody and express the software manifestation of a trend that transforms our society from an industrial, production-centric economy into a digital, service-centric economy.Indeed, SOC has already emerged as the principle methodology for software engineering of large complex web-based systems, including cloud-and grid-based systems (Bouguettaya et al. 2013).Nowadays, the SOC paradigm is, however, facing new challenges imposed by the Internet of Things (IoT) that has received significant attention both in industry and in the academic community.IoT enables us to turn a tangible entity into a node on the Internet.It is estimated that more than 50 billion Internet-connected things will be in use worldwide by 2020.Consequently, theoretical foundations and engineering methodologies and techniques for SOC that have been developed for "traditional" systems and environments are more and more questioned when it comes to their application to the IoT systems (Bouguettaya et al. 2017;Qin et al. 2016).IoT poses several fundamental challenges on service-management tasks.Resource constraints are the first concern for most IoT devices and traditional SOC standards (e.g., SOAP and BPEL) are too heavyweight to be applicable in IoT.In addition, unlike the traditional service settings, in the Internet of Things environment, functionality of system components is typically heterogeneous, multi-layered (e.g., IoT devices, data, services), dynamic, and context-aware, bringing significant complexity for service management in IoT.This special issue focuses on techniques for establishing and maintaining IoT infrastructures, platforms and applications based on the SOC paradigm, addressing questions around the design,

With the proliferation of Cloud computing and itsincreasing adoption by research communities and IT companies,providing elastic processes has become a new research issuechallenging businesses and researchers. Ensuring processes elasticityhelps organizations to face highly variable service demandsituations or uncertain financial environments. This consist inacquiring and/or releasing resources dynamically to ensure therequired QoS and reduce expenses. Elasticity management haswitnessed a lot of attention from IT community as a pivotalissue for finding the right tradeoffs between QoS levels andoperational costs by working on developing new methods andmechanisms. However, there is a lack of solutions that supportthe evaluation of elasticity strategies used to ensure the elasticityof processes at service-level and which consider differentrequirements for different requests. In this paper, we propose aformal elasticity approach for service-based processes that allowsto evaluate and verify elasticity strategies before using them in thecloud. It is composed of an elasticity model that considers thedistinguish requirements for requests and elasticity operationsfor hybrid scaling. Additionally, we present the use of ourproposed approach to evaluate different elasticity strategies usingan Elasticity Controller. Our contribution makes it possible todefine and evaluate strategies that specify different requirementsfor different requests

Deployment mechanisms in Cloud environments are becoming more and more attractive to developers that find them easy and convenient to deploy their applications in just few steps. These mechanisms reduced the development cycles from weeks to hours. In this context, elasticity plays an important role in coping with the dynamic nature of these environments. Elasticity mechanisms allow adding or retrieving application instances to deal with the changing number of incoming queries. Determining the optimal number of instances needed in a given horizon is really challenging, since we are dealing with a random number of incoming queries and given that the number of queries fulfilled by a single instance is random as well. Also, there is a trade-off between deploying too many instances and thus paying unnecessary deployment costs and deploying too few of them, and thus paying penalties for not being able to fulfill all in-coming queries on-time. In this paper, we propose a stochastic programming method that determines the optimal number of instances needed in a given planning horizon, putting in mind the uncertain parameters of the problem. In our approach, we learn from the historical behavior of the system to predict the probability distributions of the unknown data, and then formulate a stochastic programming model that optimizes the aforementioned trade-off and outputs the optimal provisioning plan.

Poster based on accepted short paper

Abstract Cloud environments are being increasingly used for the deployment and execution of complex applications and particularly component-based ones. They are expected to provide elasticity, among other characteristics, in order to allow a deployed application to rapidly change the amount of its allocated resources in order to meet the variation in demand while ensuring a given Quality of Service (QoS). However, establishing a correct elastic component-based application is not guaranteed in Cloud. Indeed, applying elasticity mechanisms should preserve functional properties and improve non-functional properties related to QoS, performance and resource consumption. In this paper, we propose an approach for the verification and deployment of elastic component-based applications. Our approach is based on the Event-B formal method. In fact, we formally model the component artifacts using Event-B and we define the Event-B events that model the elasticity mechanisms (scaling up and down) for component-based applications. Furthermore, we formally verify that our approach preserves the semantics of the component-based applications by using the proof obligations and the ProB animator. Once the elastic component-based applications are validated, they can be deployed in a Cloud environment using an elastic deployment framework which we have developed.

Cloud providers offer services at different levels of abstraction from infrastructure to applications. The quality of Cloud services is a key determinant of the overall service level a provider offers to its customers. Service Level Agreements (SLAs) are (1) crucial for Cloud customers to ensure that promised levels of services are met, (2) an important sales instrument and (3) a differentiating factor for providers. Cloud providers and services are often selected more dynamically than in traditional IT services, and as a result, SLAs need to be set up and their monitoring implemented to match the same speed. In this context, managing SLAs is complex: different Cloud providers expose different management interfaces and SLA metrics differ from one provider to another. In this paper, we will analyze how IT service quality has been defined and managed over time, discuss how to manage SLAs in today’s multi-layer, multi-sourced Cloud environments, and what to expect going forward. A particular focus will be made on the rSLA framework that enables fast setup of SLA monitoring in dynamic and heterogeneous Cloud environments. The rSLA framework is made up of three main components: the rSLA language to formally represent SLAs, the rSLA Service, which interprets the SLAs and implements the behavior specified in them, and a set of Xlets-lightweight, dynamically bound adapters to monitoring and controlling interfaces. rSLA has been tested in the context of a real pilot and found to reduce the client on-boarding process from months to weeks.

In geo-distributed cloud systems, a key challenge faced by cloud providers is to optimally tune and configure the underlying cloud infrastructure. An important problem in this context, deals with finding an optimal virtual machine (VM) placement, minimizing costs, while at the same time, ensuring good system performance. Moreover, due to the fluctuations of demand and traffic patterns, it is crucial to dynamically adjust the VM placement scheme over time. It should be noted that most of the existing studies, however, dealt with this problem either by ignoring its dynamic aspect or by proposing solutions that are not suitable for a geographically distributed cloud infrastructure. In this paper, exact as well as heuristic solutions based on Integer Linear programming (ILP) formulations are proposed. Our work focuses also on the problem of scheduling the VM migration by finding the best migration sequence of intercommunicating VMs that minimizes the resulting traffic on the backbone network. The proposed algorithms execute within a reasonable time frame to readjust VM placement scheme according to the perceived demand. Our aim is to use VM migration as a tool for dynamically adjusting the VM placement scheme while minimizing the network traffic generated by VM communication and migration. Finally, we demonstrate the effectiveness of our proposed algorithms by performing extensive experiments and simulation.

The quality of Cloud services is a key determinant of the overall service level a provider offers to its customers. Service Level Agreements (SLAs) are crucial for Cloud customers to ensure that promised levels of services are met, and an important sales instrument and a differentiating factor for providers. Cloud providers offer services at different levels of abstraction, from infrastructure to applications. Also, Cloud providers and services are often selected more dynamically than in traditional IT services, and as a result, SLAs need to be set up and monitoring implemented to match this speed. This paper presents the rSLA language for specifying and enforcing SLAs for Cloud services, allowing for dynamic instrumentation of heterogeneous Cloud services and instantaneous deployment of SLA monitoring. This is predicated on formal representations of SLAs in the language. We describe how the rSLA language and its supporting framework as well as underlying SLA execution model enable the fast deployment of custom SLAs in heterogeneous and hybrid Cloud environments.

In this work, we tackle the problem of VM migration scheduling in geodistributed DCs while considering fixed lifetime for VMs. We propose both exact and heuristic solutions that aim to find the best migration and placement decisions in a dynamic cloud environment. We consider networking VMs and we try to minimize the backbone traffic. The conducted experiments show the impact of the VM's lifetime on the migration decisions and prove the effectiveness of our heuristic solution in terms of maintaining of system stability.

Service level agreements (SLAs) are considered not only a central tool for managing QoS compliance, but also a differentiating factor between service implementations. In today's application environments with fast instrumentation deployment cycles in hybrid Cloud platforms, managing QoS compliance poses tremendous challenges, including how to deliver solutions that live up to promised QoS properties and preemptively identify provisioning risks before they lead to violations. Current approaches are usually reactive, i.e. the application infrastructure reacts to changes in QoS metrics, with a huge focus on compliance enforcement after violations have occurred. Cloud service provisioning demands a proactive approach to QoS management, with support for robust predictive scaling of service capacity based on multiple metrics, including business goals as well as infrastructure-level and QoS metrics. This paper presents an approach for adaptive service provisioning in the Cloud based on QoS analytics. A major contribution of the approach is the development of an analytics engine for predictive elasticity management of Cloud service provisioning that integrates in-depth mining of SLA compliance history with knowledge of business context, e.g. workload variability, a customer's business goals, application performance, and service operational context. In this work-in-progress report, we describe the proposed framework and discuss possible implementation and deployment scenarios.

This paper presents OCCI simulation extension, a generic simulator for any kind of resources. To achieve that, we first study the position of cloud simulator entities against OCCI model. Afterward, we define an OCCI extension simulation. In order to study the usefulness of this extension, we implement in the second time a module for Eclipse IDE to define OCCI configuration graphically. This tool uses the proposed extension. From the generated OCCI configuration, cloud resources are extracted and used by Cloud Sim simulator upon OCCI metamodel. Multiple experiments with different configuration were conducted to validate the generality of the proposed simulation extension.

Due to the complexity of managing virtual machines arrival and departure in a geographic distributed Cloud, we tackle the dynamic placement and migrations of VMs with simulation techniques. In this work, we present the study of VMs placement policies in geographically distributed data centers (DCs) using the cloud simulator Cloud Sim. We have extended the simulator to take into consideration the inter-DCs communication and migration. Through simulations, we show an example of aVMs placement and migration approach and discuss the obtained results.

Managing service quality in heterogeneous Cloud environments is complex: different providers expose different management interfaces for monitoring and configuration actions that can occur at the infrastructure, platform and application levels. To manage Service Level Agreements (SLAs) in this context, we have developed the rSLA Manager for enabling fast setup of SLA monitoring in dynamic, heterogeneous Cloud environments. In this paper, we demonstrate the use of the rSLA Manager to manage the response time behavior of an image scaling service on the IBM Blue mix platform. We show how the system enables SLA violation reduction by facilitating platform-level adaptation (e.g., adding application instances) and application-level behavior configuration (e.g., changing image scaling quality) based on different service level objectives as well as current application configuration and workload.

The proliferation of Cloud Computing platforms has led to the emergence of a large number of heterogeneous platform resources, services, application programming interfaces and supported frameworks and technologies. On one hand, supported frameworks vary from one Platform-as-a-Service (PaaS) to another depending on their implementations and capacities. On the other hand, each PaaS provides a specific and proprietary scenario to provision adequate resources and to deploy applications. In this paper, we propose a new PaaS-independent approach to provision in a unified way, appropriate PaaS resources for applications deployment in Cloud platforms. Our approach aims at addressing vendor lock-in restrictions and applications portability issues in existing Cloud platforms. To that end, we define a unified description model based on the Open Cloud Computing Interface (OCCI) core model that allows describing and managing an abstract Cloud resource. Our defined model consists of two main parts: (1) an OCCI platform extension which describes PaaS resources that can be provisioned by a PaaS to set-up an appropriate environment and (2) an OCCI application extension which describes application resources to deploy an application in this environment. We show the feasibility of our approach with an implementation and a use case of a realistic deployment scenario in Cloud Foundry PaaS.

Enterprises are more and more using hybrid cloud environments to deploy and run applications. This consists in providing and managing software and hardware resources within the enterprise and getting additional resources provided externally by public clouds whenever this is needed. In this later case, deployment of new applications consists in choosing a placement of some components in the private cloud and some others in the public cloud. To tackle this NP-hard problem, we have proposed in a previous work an approximate approach based on communication and hosting costs induced by the deployment of components in the public cloud. In this paper, we go further and propose a new efficient algorithm adapted for service-based applications modelled that can be not only described as behavior-based but also as architecture-based compositions of services.

Open Cloud Computing Interface (OCCI) proposes one of the first widely accepted, community-based, open standards for managing any kinds of cloud resources. But as it is specified in natural language, OCCI is imprecise, ambiguous, incomplete, and needs a precise definition of its core concepts. Indeed, the OCCI Core Model has conceptual drawbacks: an imprecise semantics of its type classification system, a nonextensible data type system for OCCI attributes, a vague and limited extension concept and the absence of a configuration concept. To tackle these issues, this paper proposes a precise metamodel for OCCI. This metamodel defines rigourously the static semantics of the OCCI core concepts, of a precise type classification system, of an extensible data type system, and of both extension and configuration concepts. This metamodel is based on the Eclipse Modeling Framework (EMF), its structure is encoded with Ecore and its static semantics is rigourously defined with Object Constraint Language (OCL). As a consequence, this metamodel provides a concrete language to precisely define and exchange OCCI models. The validation of our metamodel is done on the first world-wide dataset of OCCI extensions already published in the literature, and addressing inter-cloud networking, infrastructure, platform, application, service management, cloud monitoring, and autonomic computing domains, respectively. This validation highlights simplicity, consistency, correctness, completeness, and usefulness of the proposed metamodel.

Summary Cloud computing is becoming more and more an essential component in the cyberspace system. In this context, Cloud providers offer a multitude of resources and services that constitute a heterogeneous ecosystem and a new economic model. However, several issues remain to be addressed so that the Cloud becomes an efficient part of the cyber‐physical system. In this paper, we propose to address a platform as‐a‐service (PaaS) drawback that we noted as part of our work on service‐based applications deployment in Cloud platforms. To deal with that, we propose a new approach that we called SPD approach to provision appropriate platform resources and ensure hosting and deployment of applications based on Service Component Architecture or business process orchestration (Business Process Execution Language) specifications in Cloud platforms. The SPD approach stands for the three main steps of the process that we have defined, that is, (1) slice the application deployables into a set of elementary services, (2) package them into our already developed service micro‐containers, and then (3) deploy the obtained service micro‐containers in a target PaaS provider. Our approach is a PaaS‐independent approach that allows developers to deploy service‐based applications on any PaaS regardless of its capabilities. To illustrate our approach and to experiment its performances, we provide two realistic use cases scenarios, that is, a Service Component Architecture‐based application and a Business Process Execution Language‐based process deployment in Cloud Foundry PaaS. Copyright © 2014 John Wiley & Sons, Ltd.

In this work, we focus on the problem of virtual machines (VMs) placement in geographically distributed data centers. We consider communicating VMs assigned to data centers that are connected over an IP-over-WDM network. We aim to plan and optimize the placement of VMs in data centers so as to minimize the IP-traffic within the backbone network. Thus, we propose first, a formulation which can be considered as a variant of the Hub Location problem modeling and we show its extreme difficulty for medium and large size instances. In order to overcome this difficulty, we reformulate the problem by multi-commodity flow, adopt variable aggregating methods and add valid inequalities to strengthen this new formulation. The different experiments that we present show the effectiveness of our last model in terms of running time and computational resources.

Control and data dependencies represent prominent information for modeling, managing, testing and optimizing service based business processes (SBPs). BPMN 2.0, as a twofold-purpose language, can be used to both mode land execute these SBPs. However, there is neither tailored support nor implemented tool for dependency ananlysis of such processes. Therefore, in this paper, we designed and implemented DAT, a dependency analysis tool for SBPs inBPMN. Then, we show the usability of this tool using a realistic case study.

In this work, we focus on the problem of virtual machines (VMs) placement in geographically distributed data centers, where tenants may require a set of networking VMs. The aim of the present work is to plan and optimize the placement of tenant's VMs in a distributed Cloud environment while considering location and system performance constraints. Thus, we propose ILP formulations which have as objective the minimization of traffic generated by networking VMs and circulating on the backbone network. The different experiments conducted on the proposed formulations show the effectiveness of our model for large-scale Cloud systems in terms of running time and computational resources.

PROMASC Track report

The study we have conducted of existing cloud platforms shows that their operating requires the use of specific and proprietary APIs. This PaaS providers' policy is hampering the interactions between different clouds. If appropriate solutions are not considered, this issue would for instance slow down the democratization of clouds federation and cooperation. In this paper, we propose (i) a unified description model that allows the representation of applications independently of the targeted PaaS for their hosting and (ii) a generic PaaS application provisioning and management API (called COAPS API). Our proposed solution applies the separation of concerns principle by separating the provisioning and the management API from the defined description model. We motivate our solution with real use case scenarios and an implementation to show its feasibility.

Cloud computing is a recent paradigm in information technology enabling an economic model for virtual resources provisioning. For this paradigm, service oriented Architecture (SOA) is a pillar block to build applications. To efficiently manage service-based applications in the cloud, monitoring and reconfiguration remain important tasks but it is still a challenge to find a solution that reconciles the scalability, the memory consumption, and the efficiency. In this paper, we propose a framework that adds monitoring and reconfiguration facilities to services of a service-based application and deploys them in the cloud using a scalable micro-container. Unlike the existing initiatives, our framework adds dynamically these facilities to services that were not designed to be monitored or reconfigured. This makes the developers' task easier, letting them focusing on the business of their services instead of the non functional property of monitoring and reconfiguration. Moreover, our framework uses a scalable micro-container for services' deployment in the cloud to be inline with the scalability of this environment. The evaluation that we performed proves the efficiency and the flexibility of our approach for service-based applications in the cloud.

Cloud Computing involves typically provisioning of virtualized and often dynamically scalable resources for IT services operating. Study of developed Cloud platforms shows that they present limitation related to deployment and running of service-based applications that are built from heterogeneous services (programming languages, communication protocols and/or hosting frameworks). In this paper, we present CloudServ, a Platform as-a-Service (PaaS), that is dedicated to service-based applications. Its model extends the Open Cloud Computing Interface (OCCI) specification that is mainly dedicated to IaaS resources. In CloudServ, PaaS resources are continuously provisioned along with the arrival of deployment requests of service-based applications. Experiments of CloudServ demonstrate its good behaviour and highlights its scalability for a huge number of deployed services in Cloud context comparing to classical Cloud platforms.

Cloud environments are being increasingly used for the deployment and execution of service-based business processes (SBPs). Among other properties, cloud provides elasticity in order to guarantee provisioning of necessary resources that ensure a smooth functioning of cloud services despite changes in solicitations. Provisioning of elastic infrastructures and platforms is not sufficient to provide elasticity of the deployed SBP. Therefore, SBPs should be provided with elasticity mechanisms to ensure their adaptation to the workload changes. In this paper, we propose a formal model, using timed Petri nets, for SBPs elasticity considering temporal constraints and an approach for time-based evaluation of SBPs elasticity strategies.

Monitoring and reconfiguration are critical issues in Cloud environments. Monitoring allows to detect violations and specific events, while reconfiguration allows to activate corrective mechanisms or runtime modifications. In this paper we propose an extension for Open Cloud Computing Interface (OCCI) to enable monitoring and reconfiguration. The extension describes the needed elements to manage (i.e., to monitor and reconfigure) cloud resources on demand. The definition entails the introduction of new OCCI Resources, Links and Mixins. We define on the one hand new types needed to monitor metrics based on a previously established SLA. On the other hand we define the needed types to reconfigure our managed resources when needed. The newly added elements are OCCI entities defined as generic Kinds, that are specialized using OCCI Mixins. Using these elements, the user is provided with a monitoring and reconfiguration infrastructure on demand. We propose herein, a real use case based on HTTP rendering showing how to establish and link the described elements of the infrastructure.

For automatically composing Web services in a correct manner, information about their behaviors (an abstract model) has to be published in a repository. This abstract model must be sufficient to decide whether two, or more, services are compatible (the composition is possible) is possible without including any additional information that can be used to disclose the privacy of these services. The compatibility property is defined by different variants of the well known soundness property on open workflow nets. These properties guarantee the absence of livelocks, deadlocks and other anomalies that can be formulated without domain knowledge. In this paper we address the automatic abstraction of Web services and the checking of their compatibility using their abstract models only. To abstract Web services, we use the symbolic observation graph (SOG) approach that preserves necessary information for service composition and hides private information. We show how the SOG can be adapted and used so that the verification of different variants of compatibility can be performed on the composition of the abstract models (SOGs) of Web services instead of the original composite service.

The tremendous growth in the amount of available web services (WS) impulses many researchers on proposing recommender systems to help users discover services. Most of the proposed solutions analyzed query strings and web service descriptions to generate recommendations. However, text based recommendations approaches depend mainly on user's perspective, languages and notations which easily decrease recommendation's efficiency. In this paper, we propose to take into account user's behaviors instead of text based analysis. We apply collaborative filtering technique on user's interactions. We propose and implement two algorithms based on Vector Space Model and Latent Semantic Indexing to validate our approach. We also provide evaluation methods with different datasets in order to compare and assert the efficiency of our two algorithms.

Cloud Computing is a new supplement, consumption, and delivery model for IT services based on Internet protocols. It typically involves provisioning of dynamically scalable and often virtualized resources. In this environment, there are several issues related to the inadequacies of hosting platforms and mechanisms to ensure the smooth running of service-based applications (communication protocols, ESB, Service containers, etc.). In particular, architectures and implementations of service containers are not adapted to Cloud environments. In this paper, we present a new service container dedicated to one deployed service that avoids the processing limits of classical services containers. Our approach addresses scalability by reducing memory consumption and response time. The proposed service container is evaluated in several situations against well known services containers within a real Cloud Computing network.

In this paper, we propose to use communities as a mean to organize Web services registries in a multi-registry environment. First, we propose a semantic model for Web services registry description (WSRD). A WSRD description depicts the functionalities offered by services advertised by a given registry. Thereafter, we propose an implicit approach for building communities based on the WSRD descriptions using a fuzzy clustering technique. Eventually, this clustering will be helpful for selecting an adequate registry for service requesters. Provided experiments in this paper show the feasibility of our approach.

In a service oriented B2B context, companies aiming to cooperate and interact with others have to make their services available through private service registries. Since the number of registries can be as large as the number of companies, the resulting registry network has to be organized to assist and improve the service discovery process. In this paper, we propose to use communities as a means to organize Web services registries in such a context. First, we propose a semantic model for Web services registry description (WSRD). A WSRD description is a semantic model depicting the functionalities offered by services advertised by a given registry. Thereafter, we propose an implicit approach for building communities based on the registries WSRD descriptions using a fuzzy clustering technique. Eventually, this clustering will be helpful for selecting an adequate registry for service requesters. Provided experimental evaluations in this paper show that our approach is efficient in realistic situations.

In response to increasing economical constraints, enterprise organization has evolved toward new structures such as networked enterprise, supply chains, virtual enterprise, or collaborative business organizations. This structural organization requires the interoperability of business processes (BPs)and information systems. Dealing with interoperability often leads to the deployment of Service-Oriented Architecture (SOA) based on Enterprise Service Bus (ESB) to design agile collaborative BPs and publish and compose new services. In order to protect each partner's own interests, security strategies must be developed and integrated in the service environment. Unfortunately, traditional security approaches deal with security concerns from a technical perspective (i.e., data transmission or authentication, etc.) and do not support end-to-end security in a distributed environment of business services and collaborative processes. In this paper, we attempt to improve end-to-end security by annotating service descriptions with security objectives used to generate convenient quality of protection (QoP) agreements between partners. Conversely, agreements are processed by a dedicated matching module with respect to security requirements and preferences to select business services, and then, compose their appropriate technical security services.

In this paper, we present new algorithms for matching Web services described in YASA4WSDL (YASA for short). We have already defined YASA, a semantic description of services that overcomes some issues in WSDL or SAWSDL. In this paper, we continue on our contribution and show how YASA Web services are matched based on the specificities of YASA descriptions. Our matching algorithm consists of three variants based on three different semantic matching degree aggregations. This algorithm was implemented in YASA-M, a new Web service matchmaker. YASA-M is evaluated and compared to well known approaches for service matching. Experiments show that YASA-M provides better results, in terms of precision, response time, and scalability, than a well known matchmaker.

The discovery of suitable Web services for a given task is one of the central operations in Service-Oriented Architectures, and research on Web services (WS)s aims at automating this step. For the large amount of available WSs that can be expected in real-world settings, the efficiency of automated discovery becomes important. For this, we propose to exploit previous discovery results to reduce the search space in distributed registry environment. The architecture we adopt consists in structuring registries of WSs into communities. Then, we propose to adapt recommendation techniques to ease the services discovery process. This consists of (1) the selection of communities of registries using semantic matching and (2) the recommendation of registries within these communities using user-characterization based technique. To put our proposed distributed registry architecture in practise and to test the efficiency of recommendation-based discovery, we propose to implement a Peer-to Peer (P2P) registries environment on top of JXTA platform.

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.

The lack of semantics in Web Services Description Language (WSDL) prevents automatic discovery and hence automatic invocation and composition. In our work, we are interested in extending existing approaches for the description of Semantic Web Services. Previously, we have extended the W3C recommendation on Semantics for Web Services (SAWSDL) and have proposed the use of two types of ontologies: a Technical Ontology type containing concepts defining semantics of services, their QoS,etc. and a Domain Ontology type containing the concepts defining the semantics of the business domain. The aim of this paper is to present Yet Another Semantic Annotation for WSDL (YASA4WSDL) and define a technical service ontology for YASA4WSDL. This ontology integrates useful concepts of WSDL meta-model, and OWL-S and WSMO ontologies. The integration of these ontologies is based on different matching techniques according to an ontology mapping process. The resulting ontology covers specific Web services semantic concepts.

In this paper, we discuss the suitability of using recommendation techniques for Web service discovery in distributed registry environments. The architecture we adopt consists in structuring registries of Web services into groups. We propose to adapt existing techniques for recommendation to ease the services discovery process. This consists of (1) recommendation of groups of registries using semantic matching and (2) recommendation of registries within these groups using user-characterization based technique. To put our proposed distributed registry architecture in practise and to test the efficiency of recommendation-based discovery, we propose to simulate a peer-to-peer (P2P) registries environment on top of JXTA platform.

In a context of short-term cooperation, enterprises with complementary skills are dynamically interconnected according to their needs. To deal with requirements in a such cooperation, we present in this paper CoopFlow that aims at providing a useful artifact for preservation of the privacy of workflows partners, pre-established workflows and pre-established workflow management systems. CoopFlow consists of three steps: workflow abstraction and advertisement, workflow matching and interconnection, and workflow cooperation. To preserve the privacy of partners, the first step of the approach includes an abstraction procedure allowing a partial visibility of the partners' workflows. The second step consists of interconnecting existing workflows of partners with complementary skills attributing to a matching procedure that allows checking both behaviors and business semantics of partners' workflows. Finally, the last step of CoopFlow consists of controlling the inter-enterprise workflows cooperation allowing cooperation partners to integrate the existing workflows and to check whenever they can cooperate and change their partners, which frequently leads to support spontaneous, dynamic and short-term cooperation. With this intention, we developed a platform that manages inter-operability by integrating pre-established workflow management systems. The proof of concept is provided by integrating three heterogeneous and open workflow management systems to the CoopFlow platform.

Web services provide standard means to promote interoperability and extensibility among software applications, as well as to allow them to be combined in order to perform more complex operations. Therefore web services have to be described, published, discovered, invoked and composed. Within this process describing Web services using ontology will enhance service discovery. The "quality" of that discovery depends on the used algorithms and techniques. In this paper we propose a novel approach to enhance web service discovery based on, among others, requesters' preferences. First of all, we propose a way to express preferences of request elements. Then we introduce a matching algorithm that takes into account theses preferences in the discovery process.