Measuring the understandability of WSDL specifications, web service understanding degree approach and system

Web Services (WS) are fundamental software artifacts for building service oriented applications and they are usually reused by others. Therefore they must be analyzed and comprehended for maintenance tasks: identification of critical parts, bug fixing, adaptation and improvement. In this article, WSDLUD a method aimed at measuring a priori the understanding degree (UD) of WSDL (Web Service Description Language) descriptions is presented. In order to compute UD several criteria useful to measure the understanding’s complexity of WSDL descriptions must be defined. These criteria are used by LSP (Logic Scoring of Preference), a multicriteria evaluation method, for producing a Global Preference value that indicates the satisfaction level of the WSDL description regarding the evaluation focus, in this case, the understanding degree. All the criteria information required by LSP is extracted from WSDL descriptions by using static analysis techniques and processed by specific algorithms which allow gathering semantic information. This process allows to obtain a priori information about the comprehension difficulty which proves our research hypotheses that states that it is possible to compute the understanding degree of a WSDL description.info:eu-repo/semantics/publishedVersio

Orchestration de web services fiables

L’Informatique Orienté Services représente un paradigme pour construire des applications distribuées sur Internet. L’Architecture Orientée Services(SOA) est un style architectural qui permet le développement de ces applications à base de services. Au cours de la dernière décennie, l’orchestration des services Web est devenue un domaine très actif dans la recherche scientifique et académique. Bien que de nombreux défis liés à l’orchestration aient été abordés, la fiabilité de l’orchestration et de sa vérification restent encore un sujet ouvert, prérequis et important de fait que ces orchestrations affectent aujourd’hui plusieurs activités quotidiennes. Cette thèse focalise sur le sujet d’orchestration des Services Web Fiables. En particulier, elle contribue avec un ensemble d’approches, de techniques et d’outils pour améliorer la sélection et l’orchestration des services web fiables. Premièrement, elle affine les phases du cycle de vie d’orchestration de services web afin d’assurer une vérification continuée de fiabilité lors des phases de conception et d’exécution. En outre, elle propose une architecture conceptuelle basée sur un registre de service amélioré, pour la mise en œuvre d’orchestrations fiables. Deuxièmement, elle présente une approche de mesure de similarité entre les services web. L’approche repose sur la comparaison des interfaces WSDL de services. L’approche sert à identifier les relations de similarité, de substituabilité et de composabilité entre services. L’outil WSSIM a été développé pour mettre en œuvre l’approche proposée. Pour validation, l’outil a été expérimenté avec un ensemble important de services web réels. Troisièmement, la thèse contribue avec une approche pour l’identification des substituts de services simples et complexes. L’approche utilise les techniques de mesure de similarité, la classification de service avec FCA et l’analyse de fiabilité pour identifier et sélectionner les meilleures substitutes. Un ensemble d’algorithmes aient été proposés pour décrire le processus d’identification. Quatrièmement, pour examiner la réputation des services comme un autre critère de fiabilité, la thèse introduit un Framework et un modèle mathématique pour la gestion de réputation de service We

Robustness estimation and optimisation for semantic web service composition with stochastic service failures

Service-oriented architecture (SOA) is a widely adopted software engineering paradigm that encourages modular and reusable applications. One popular application of SOA is web service composition, which aims to loosely couple web services to accommodate complex goals not achievable through any individual web service. Many approaches have been proposed to construct composite services with optimized Quality of Service (QoS), assuming that QoS of web services never changes. However, the constructed composite services may not perform well and may not be executable later due to its component services' failure. Therefore, it is important to build composite services that are robust to stochastic service failures. Two challenges of building robust composite services are to efficiently generate service composition with near-optimal quality in a large search space of available services and to accurately measure the robustness of composite services considering all possible failure scenarios. This article proposes a novel two-stage GA-based approach to robust web service composition with an adaptive evolutionary control and an efficient robustness measurement. This approach can generate robust composite service at the design phase, which can cope with stochastic service failures and maintain high quality at the time of execution. We have conducted experiments with benchmark datasets to evaluate the performance of our proposed approach. Our experiments show that our method can produce highly robust composite services, achieving outstanding performance consistently in the event of stochastic service failures, on service repositories with varying sizes

An Investigation into Dynamic Web Service Composition Using a Simulation Framework

[Motivation] Web Services technology has emerged as a promising solution for creat- ing distributed systems with the potential to overcome the limitation of former distrib- uted system technologies. Web services provide a platform-independent framework that enables companies to run their business services over the internet. Therefore, many techniques and tools are being developed to create business to business/business to customer applications. In particular, researchers are exploring ways to build new services from existing services by dynamically composing services from a range of resources. [Aim] This thesis aims to identify the technologies and strategies cur- rently being explored for organising the dynamic composition of Web services, and to determine how extensively each of these has been demonstrated and assessed. In addition, the thesis will study the matchmaking and selection processes which are essential processes for Web service composition. [Research Method] We under- took a mapping study of empirical papers that had been published over the period 2000 to 2009. The aim of the mapping study was to identify the technologies and strategies currently being explored for organising the composition of Web services, and to determine how extensively each of these has been demonstrated and assessed. We then built a simulation framework to carry out some experiments on composition strategies. The rst experiment compared the results of a close replication of an ex- isting study with the original results in order to evaluate our close replication study. The simulation framework was then used to investigate the use of a QoS model for supporting the selection process, comparing this with the ranking technique in terms of their performance. [Results] The mapping study found 1172 papers that matched our search terms, from which 94 were classied as providing practical demonstration of ideas related to dynamic composition. We have analysed 68 of these in more detail. Only 29 provided a `formal' empirical evaluation. From these, we selected a `baseline' study to test our simulation model. Running the experiments using simulated data- sets have shown that in the rst experiment the results of the close replication study and the original study were similar in terms of their prole. In the second experiment, the results demonstrated that the QoS model was better than the ranking mechanism in terms of selecting a composite plan that has highest quality score. [Conclusions] No one approach to service composition seemed to meet all needs, but a number has been investigated more. The similarity between the results of the close replication and the original study showed the validity of our simulation framework and a proof that the results of the original study can be replicated. Using the simulation it was demonstrated that the performance of the QoS model was better than the ranking mechanism in terms of the overall quality for a selected plan. The overall objectives of this research are to develop a generic life-cycle model for Web service composition from a mapping study of the literature. This was then used to run simulations to replicate studies on matchmaking and compare selection methods

A COGNITIVE ARCHITECTURE FOR AMBIENT INTELLIGENCE

L’Ambient Intelligence (AmI) è caratterizzata dall’uso di sistemi pervasivi per monitorare l’ambiente e modificarlo secondo le esigenze degli utenti e rispettando vincoli definiti globalmente. Questi sistemi non possono prescindere da requisiti come la scalabilità e la trasparenza per l’utente. Una tecnologia che consente di raggiungere questi obiettivi è rappresentata dalle reti di sensori wireless (WSN), caratterizzate da bassi costi e bassa intrusività. Tuttavia, sebbene in grado di effettuare elaborazioni a bordo dei singoli nodi, le WSN non hanno da sole le capacità di elaborazione necessarie a supportare un sistema intelligente; d’altra parte senza questa attività di pre-elaborazione la mole di dati sensoriali può facilmente sopraffare un sistema centralizzato con un’eccessiva quantità di dettagli superflui. Questo lavoro presenta un’architettura cognitiva in grado di percepire e controllare l’ambiente di cui fa parte, basata su un nuovo approccio per l’estrazione di conoscenza a partire dai dati grezzi, attraverso livelli crescenti di astrazione. Le WSN sono utilizzate come strumento sensoriale pervasivo, le cui capacità computazionali vengono utilizzate per pre-elaborare i dati rilevati, in modo da consentire ad un sistema centralizzato intelligente di effettuare ragionamenti di alto livello. L’architettura proposta è stata utilizzata per sviluppare un testbed dotato degli strumenti hardware e software necessari allo sviluppo e alla gestione di applicazioni di AmI basate su WSN, il cui obiettivo principale sia il risparmio energetico. Per fare in modo che le applicazioni di AmI siano in grado di comunicare con il mondo esterno in maniera affidabile, per richiedere servizi ad agenti esterni, l’architettura è stata arricchita con un protocollo di gestione distribuita della reputazione. È stata inoltre sviluppata un’applicazione di esempio che sfrutta le caratteristiche del testbed, con l’obiettivo di controllare la temperatura in un ambiente lavorativo. Quest’applicazione rileva la presenza dell’utente attraverso un modulo per la fusione di dati multi-sensoriali basato su reti bayesiane, e sfrutta questa informazione in un controllore fuzzy multi-obiettivo che controlla gli attuatori sulla base delle preferenze dell’utente e del risparmio energetico.Ambient Intelligence (AmI) systems are characterized by the use of pervasive equipments for monitoring and modifying the environment according to users’ needs, and to globally defined constraints. Furthermore, such systems cannot ignore requirements about ubiquity, scalability, and transparency to the user. An enabling technology capable of accomplishing these goals is represented by Wireless Sensor Networks (WSNs), characterized by low-costs and unintrusiveness. However, although provided of in-network processing capabilities, WSNs do not exhibit processing features able to support comprehensive intelligent systems; on the other hand, without this pre-processing activities the wealth of sensory data may easily overwhelm a centralized AmI system, clogging it with superfluous details. This work proposes a cognitive architecture able to perceive, decide upon, and control the environment of which the system is part, based on a new approach to knowledge extraction from raw data, that addresses this issue at different abstraction levels. WSNs are used as the pervasive sensory tool, and their computational capabilities are exploited to remotely perform preliminary data processing. A central intelligent unit subsequently extracts higher-level concepts in order to carry on symbolic reasoning. The aim of the reasoning is to plan a sequence of actions that will lead the environment to a state as close as possible to the users’ desires, taking into account both implicit and explicit feedbacks from the users, while considering global system-driven goals, such as energy saving. The proposed conceptual architecture was exploited to develop a testbed providing the hardware and software tools for the development and management of AmI applications based on WSNs, whose main goal is energy saving for global sustainability. In order to make the AmI system able to communicate with the external world in a reliable way, when some services are required to external agents, the architecture was enriched with a distributed reputation management protocol. A sample application exploiting the testbed features was implemented for addressing temperature control in a work environment. Knowledge about the user’s presence is obtained through a multi-sensor data fusion module based on Bayesian networks, and this information is exploited by a multi-objective fuzzy controller that operates on actuators taking into account users’ preference and energy consumption constraints

Value- and debt-aware selection and composition in cloud-based service-oriented architectures using real options

This thesis presents a novel model for service selection and composition in Cloud-based Service-Oriented Architectures (CB-SOA), which is called CloudMTD, using real options, Dependency Structure Matrix (DSM) and propagation-cost metrics. CB-SOA architectures are composed of web services, which are leased or bought off the cloud marketplace. CB-SOA can improve its utility and add value to its composition by substituting its constituent services. The substitution decisions may introduce technical debt, which needs to be managed. The thesis defines the concept of technical debt for CB-SOA and reports on the available technical debt definitions and approaches in the literature. The formulation of service substitution problem and its technical debt valuation is based on options, which exploits Binomial Options Analysis. This thesis looks at different option types under uncertainty. This thesis is concerned with some scenarios that may lead to technical debt, which are related to web service selection and composition that has been driven by either a technical or a business objective. In each scenario, we are interested in three decisions (1) keep, (2) substitute or (3) abandon the current service. Each scenario takes into consideration either one or more QoS attribute dimension (e.g. Availability). We address these scenarios from an option-based perspective. Each scenario is linked to a suitable option type. A specific option type depends on the nature of the application, problem to be investigated, and the decision to be taken. In addition, we use Dependency Structure Matrix (DSM) in order to represent dependencies among web services in CB-SOA. We introduce time and complexity sensitive propagation-cost metrics to DSM to solve the problem. In addition, CloudMTD model informs the time-value of the decisions under uncertainty based on behavioral and structural aspects of CB-SOA

Monitoring and Optimization of ATLAS Tier 2 Center GoeGrid

The demand on computational and storage resources is growing along with the amount of infor- mation that needs to be processed and preserved. In order to ease the provisioning of the digital services to the growing number of consumers, more and more distributed computing systems and platforms are actively developed and employed. The building block of the distributed computing infrastructure are single computing centers, similar to the Worldwide LHC Computing Grid, Tier 2 centre GoeGrid. The main motivation of this thesis was the optimization of GoeGrid perfor- mance by efficient monitoring. The goal has been achieved by means of the GoeGrid monitoring information analysis. The data analysis approach was based on the adaptive-network-based fuzzy inference system (ANFIS) and machine learning algorithm such as Linear Support Vector Machine (SVM). The main object of the research was the digital service, since availability, reliability and ser- viceability of the computing platform can be measured according to the constant and stable provisioning of the services. Due to the widely used concept of the service oriented architecture (SOA) for large computing facilities, in advance knowing of the service state as well as the quick and accurate detection of its disability allows to perform the proactive management of the com- puting facility. The proactive management is considered as a core component of the computing facility management automation concept, such as Autonomic Computing. Thus in time as well as in advance and accurate identification of the provided service status can be considered as a contribution to the computing facility management automation, which is directly related to the provisioning of the stable and reliable computing resources. Based on the case studies, performed using the GoeGrid monitoring data, consideration of the approaches as generalized methods for the accurate and fast identification and prediction of the service status is reasonable. Simplicity and low consumption of the computing resources allow to consider the methods in the scope of the Autonomic Computing component

SERVICE-BASED AUTOMATION OF SOFTWARE CONSTRUCTION ACTIVITIES

The reuse of software units, such as classes, components and services require professional knowledge to be performed. Today a multiplicity of different software unit technologies, supporting tools, and related activities used in reuse processes exist. Each of these relevant reuse elements may also include a high number of variations and may differ in the level and quality of necessary reuse knowledge. In such an environment of increasing variations and, therefore, an increasing need for knowledge, software engineers must obtain such knowledge to be able to perform software unit reuse activities. Today many different reuse activities exist for a software unit. Some typical knowledge intensive activities are: transformation, integration, and deployment. In addition to the problem of the amount of knowledge required for such activities, other difficulties also exist. The global industrial environment makes it challenging to identify sources of, and access to, knowledge. Typically, such sources (e.g., repositories) are made to search and retrieve information about software unitsand not about the required reuse activity knowledge for a special unit. Additionally, the knowledge has to be learned by inexperienced software engineers and, therefore, to be interpreted. This interpretation may lead to variations in the reuse result and can differ from the estimated result of the knowledge creator. This makes it difficult to exchange knowledge between software engineers or global teams. Additionally, the reuse results of reuse activities have to be repeatable and sustainable. In such a scenario, the knowledge about software reuse activities has to be exchanged without the above mentioned problems by an inexperienced software engineer. The literature shows a lack of techniques to store and subsequently distribute relevant reuse activity knowledge among software engineers. The central aim of this thesis is to enable inexperienced software engineers to use knowledge required to perform reuse activities without experiencing the aforementioned problems. The reuse activities: transformation, integration, and deployment, have been selected as the foundation for the research. Based on the construction level of handling a software unit, these activities are called Software Construction Activities (SCAcs) throughout the research. To achieve the aim, specialised software construction activity models have been created and combined with an abstract software unit model. As a result, different SCAc knowledge is described and combined with different software unit artefacts needed by the SCAcs. Additionally, the management (e.g., the execution of an SCAc) will be provided in a service-oriented environment. Because of the focus on reuse activities, an approach which avoids changing the knowledge level of software engineers and the abstraction view on software units and activities, the object of the investigation differs from other approaches which aim to solve the insufficient reuse activity knowledge problem. The research devised novel abstraction models to describe SCAcs as knowledge models related to the relevant information of software units. The models and the focused environment have been created using standard technologies. As a result, these were realised easily in a real world environment. Softwareengineers were able to perform single SCAcs without having previously acquired the necessary knowledge. The risk of failing reuse decreases because single activities can be performed. The analysis of the research results is based on a case study. An example of a reuse environmenthas been created and tested in a case study to prove the operational capability of the approach. The main result of the research is a proven concept enabling inexperienced software engineers to reuse software units by reusing SCAcs. The research shows the reduction in time for reuse and a decrease of learning effort is significant

Model-Driven Online Capacity Management for Component-Based Software Systems

Capacity management is a core activity when designing and operating distributed software systems. It comprises the provisioning of data center resources and the deployment of software components to these resources. The goal is to continuously provide adequate capacity, i.e., service level agreements should be satisfied while keeping investment and operating costs reasonably low. Traditional capacity management strategies are rather static and pessimistic: resources are provisioned for anticipated peak workload levels. Particularly, enterprise application systems are exposed to highly varying workloads, leading to unnecessarily high total cost of ownership due to poor resource usage efficiency caused by the aforementioned static capacity management approach. During the past years, technologies emerged that enable dynamic data center infrastructures, e. g., leveraged by cloud computing products. These technologies build the foundation for elastic online capacity management, i.e., adapting the provided capacity to workload demands based on a short-term horizon. Because manual online capacity management is not an option, automatic control approaches have been proposed. However, most of these approaches focus on coarse-grained adaptation actions and adaptation decisions are based on aggregated system-level measures. Architectural information about the controlled software system is rarely considered. This thesis introduces a model-driven online capacity management approach for distributed component-based software systems, called SLAstic. The core contributions of this approach are a) modeling languages to capture relevant architectural information about a controlled software system, b) an architecture-based online capacity management framework based on the common MAPE-K control loop architecture, c) model-driven techniques supporting the automation of the approach, d) architectural runtime reconfiguration operations for controlling a system’s capacity, e) as well as an integration of the Palladio Component Model. A qualitative and quantitative evaluation of the approach is performed by case studies, lab experiments, and simulation

Design and implementation of a secure wide-area object middleware

Tanenbaum, A.S. [Promotor]Crispo, C.B. [Copromotor