Quantitative assessment of workflow performance through PH reduction

Copyright © 2016 EAI. Workflows are logical abstraction of processes widely adopted in several contexts. Design and operation of workflows are critical stages where issues not manifested by the single block arise from compositions. To deal with such issues, proper techniques and tools should be implemented as support for workflow designers and operators. This paper proposes a solution for the evaluation of the workflow performance starting from the components' ones. Based on the stochastic characterization of the workflow tasks, phase type distributions and stochastic workflow reduction rules, our approach allows to overcome the limits of existing solutions, considering general response time distributions while providing parametric analysis on customer usage profiles and design alternatives. To demonstrate the effectiveness of the proposed solution an example from literature is evaluated

Web Service Composition with Uncertain Non-functional Parameters

Part 3: Service OrientationInternational audienceThe problem of service composition is of key importance in the Internet of Things paradigm. A composite Web Service can clearly determine how real life objects described as Web Services could interact with each other. This article proposes a non-functional parameters aggregation algorithm, used in composite service plan optimisation stage, taking into account the uncertainty of the nonfunctional parameters. Also, an optimisation algorithm, using the proposed aggregation method, is presented to show the complete solution for the problem. In this proposition, the algorithm focuses on composite service plan optimisation with uncertain parameters with the given uncertainty description on example of uncertainty parameter. However, the proposed algorithm can be generalized, so it can be used also with other uncertain parameter

QUALITY OF PROCESS ? A BUSINESS PROCESS PERSPECTIVE ON QUALITY OF SERVICE

The fundamental paradigm shift from a product- to a service-oriented economy implies novel technical and organizational challenges. The resulting dynamic of the technical infrastructure and the increasing development towards requesting external business services to be integrated into end-to-end business processes requires mechanisms ensuring the reliability of the organization?s composed services, workflows and business processes. From a business perspective, QoS characteristics defined based on technical services within the infrastructural layer have to be aggregated to more business-relevant Key Performance Indicators on business process layer to express the Quality of Process. These KPIs represent quality that is highly related to the business?s performance (e.g. processing time of a business service) and are crucial for achieving predefined goals in order to stay competitive in the market. The contribution of this paper is threefold: We (i) provide an in-depth requirements analysis for such a holistic quality management framework, we (ii) develop a holistic aggregation framework which enables service level aggregation incorporating the loosely coupled structure of business processes with invoked systems and services in an instance based manner. To demonstrate the expressive power of our framework we (iii) provide an exemplary industrial application scenario and illustrate the functioning and interplay of the designed artifacts

Fuzzy logic based qos optimization mechanism for service composition

Increase emphasis on Quality of Service and highly changing environments make management of composite services a time consuming and complicated task. Adaptation approaches aim to mitigate the management problem by adjusting composite services to the environment conditions, maintaining functional and quality levels, and reducing human intervention. This paper presents an adaptation approach that implements self-optimization based on fuzzy logic. The proposed optimization model performs service selection based on the analysis of historical and real QoS data, gathered at different stages during the execution of composite services. The use of fuzzy inference systems enables the evaluation of the measured QoS values, helps deciding whether adaptation is needed or not, and how to perform service selection. Experimental results show significant improvements in the global QoS of the use case scenario, providing reductions up to 20.5% in response time, 33.4% in cost and 31.2% in energy consumption

Using Domain Ontology for Service Replacement Tasks: An Empirical Evaluation

Organizations increasingly use information technology (IT) to integrate their business processes into the processes of their suppliers, customers, and other third parties. An important IT approach is the realization of composite services that organize elementary software services under a shared workflow. Any failure of an elementary service can severely impact the process. The failed service must be examined and, ultimately, be replaced. In solving that task, the process designer must consider the quality-of-service (QoS) of the process. However, the heterogeneity of service descriptions puts the burden on the designer. This research empirically evaluates how designers can use a domain ontology, namely the QoS aggregation ontology, for the replacement task. We report on a laboratory experiment to compare the effectiveness and efficiency of using the ontology vis-à-vis an aggregation table. The results provide evidence for the usefulness of the domain ontology that specifies problem-solving knowledge required for a time-critical task

Quality of Service (QoS) in SOA Systems. A Systematic Review

In the last recent years a new technology called Web Services has emerged. The main characteristic of a web service is that it is a piece of software that the user can utilize but doesn’t own, that is, the user doesn’t install the software but uses it through the internet and standard protocols. With this new technology, a new architecture paradigm called SOA (Service Oriented Architecture) has appeared. This architecture is based on combining several web services, each one responsible to develop a concrete task, in order to obtain full‐operational software. The web services that compose a SOA System might be able to perform a task in a certain time, might be unavailable in some cases, might have security policies, etc. All this attributes, named Quality attributes, are essential in order to choose the appropriate web service for a SOA System. The objective of this Master Thesis is focused on two different but related subjects: (1) The development of a review regarding to the Quality Attributes for web services in a systematic manner and the development of a tool for monitoring SOA Systems capable to be used in several frameworks such as for Self‐Adaptive SOA Systems and for Web Service Discovery Systems

QoS awareness and adaptation in service composition

The dynamic nature of a Web service execution environment generates frequent variations in the Quality of Service offered to the consumers, therefore, obtaining the expected results while running a composite service is not guaranteed. When combining this highly changing environment with the increasing emphasis on Quality of Service, management of composite services turns into a time consuming and complicated task. Different approaches and tools have been proposed to mitigate the impacts of unexpected events during the execution of composite services. Among them, self-adaptive proposals have stood out, since they aim to maintain functional and quality levels, by dynamically adapting composite services to the environment conditions, reducing human intervention. The research presented in this Thesis is centred on self-adaptive properties in service composition, mainly focused on self-optimization. Three models have been proposed to target self-optimization, considering various QoS parameters, the benefit of performing adaptation, and looking at adaptation from two perspectives: reactive and proactive. They target situations where the QoS of the composition is decreasing. Also, they consider situations where a number of the accumulated QoS values, in certain point of the process, are better than expected, providing the possibility of improving other QoS parameters. These approaches have been implemented in service composition frameworks and evaluated through the execution of test cases. Evaluation was performed by comparing the QoS values gathered from multiple executions of composite services, using the proposed optimization models and a non-adaptive approach. The benefit of adaptation was found a useful value during the decision making process, in order to determine if adaptation was needed or not. Results show that using optimization mechanisms when executing composite services provide significant improvements in the global QoS values of the compositions. Nevertheless, in some cases there is a trade-off, where one of the measured parameters shows an increment, in order to improve the others

Sélection contextuelle de services continus pour la robotique ambiante

La robotique ambiante s'intéresse à l'introduction de robots mobiles au sein d'environnements actifs où ces derniers fournissent des fonctionnalités alternatives ou complémentaires à celles embarquées par les robots mobiles. Cette thèse étudie la mise en concurrence des fonctionnalités internes et externes aux robots, qu'elle pose comme un problème de sélection de services logiciels. La sélection de services consiste à choisir un service ou une combinaison de services parmi un ensemble de candidats capables de réaliser une tâche requise. Pour cela, elle doit prédire et évaluer la performance des candidats. Ces performances reposent sur des critères non-fonctionnels comme la durée d'exécution, le coût ou le bruit. Ce domaine applicatif a pour particularité de nécessiter une coordination étroite entre certaines de ses fonctionnalités. Cette coordination se traduit par l'échange de flots de données entre les fonctionnalités durant leurs exécutions. Les fonctionnalités productrices de ces flots sont modélisées comme des services continus. Cette nouvelle catégorie de services logiciels impose que les compositions de services soient hiérarchiques et introduit des contraintes supplémentaires pour la sélection de services. Cette thèse met en évidence la présence d'un important couplage non-fonctionnel entre les performances des instances de services de différents niveaux, même lorsque les flots de données sont unidirectionnels. L'approche proposée se concentre sur la prédiction de la performance d'une instance de haut-niveau sachant son organigramme à l'issue de la sélection. Un organigramme regroupe l'ensemble des instances de services sollicitées pour réaliser une tâche de haut-niveau. L'étude s'appuie sur un scénario impliquant la sélection d'un service de positionnement en vue de permettre le déplacement d'un robot vers une destination requise. Pour un organigramme considéré, la prédiction de performance d'une instance de haut-niveau de ce scénario introduit les exigences suivantes : elle doit (i)être contextuelle en tenant compte, par exemple, du chemin suivi pour atteindre la destination requise, (ii) prendre en charge le remplacement d'une instance de sous-service suite à un échec ou, par extension, de façon opportuniste. En conséquence, cette sélection de services est posée comme un problème de prise de décision séquentielle formalisé à l'aide de processus de décision markoviens à horizon fini. La dimensionnalité importante du contexte en comparaison à la fréquence des déplacements du robot rend inadaptées les méthodes consistant à apprendre directement une fonction de valeur ou une fonction de transition. L'approche proposée repose sur des modèles de dynamique locaux et exploite le chemin de déplacement calculé par un sous-service pour estimer en ligne les valeurs des organigrammes disponibles dans l'état courant. Cette estimation est effectuée par l'intermédiaire d'une méthode de fouille stochastique d'arbre, Upper Confidence bounds applied to TreesAmbient robotics aims at introducing mobile robots in active environments where the latter provide new or alternative functionalities to those shipped by mobile robots. This thesis studies the competition between robot and external functionalities, which is set as a service selection problem. Service selection consists in choosing a service or a combination of services among a set of candidates able to fulfil a given request. To do this, it has to predict and evaluate candidate performances. These performances are based on non-functional requirements such as execution time, cost or noise. This application domain requires tight coordination between some of its functionalities. Tight coordination involves setting data streams between functionalities during their execution. In this proposal, functionalities producing data streams are modelled as continuous services. This new service category requires hierarchical service composition and adds some constraints to the service selection problem. This thesis shows that an important non-functional coupling appears between service instances at different levels, even when data streams are unidirectional. The proposed approach focuses on performance prediction of an high-level service instance given its organigram. This organigram gathers service instances involved in the high-level task processing. The scenario included in this study is the selection of a positioning service involved in a robot navigation high-level service. For a given organigram, performance prediction of an high-level service instance of this scenario has to: (i) be contextual by, for instance, considering moving path towards the required destination, (ii) support service instance replacement after a failure or in an opportunist manner. Consequently, this service selection is set as a sequential decision problem and is formalized as a finite-horizon Markov decision process. Its high contextual dimensionality with respect to robot moving frequency makes direct learning of Q-value functions or transition functions inadequate. The proposed approachre lies on local dynamic models and uses the planned moving path to estimate Q-values of organigrams available in the initial state. This estimation is done using a Monte-Carlo tree search method, Upper Confidence bounds applied to TreesPARIS-EST-Université (770839901) / SudocSudocFranceF