Domain-Specific Service Selection for Composite Services

With the rapid development of e-commerce over Internet, web services have attracted much attention in recent years. Nowadays, enterprises are able to outsource their internal business processes as services and make them accessible via the Web. Then they can dynamically combine individual services to provide new value-added services. With the increasing number of web services having equivalent functionality, the binding procedure is driven by some non-functional, Quality of Service (QoS) criteria, such as the money cost, response time, reputation, reliability or a trade-off between them. Thus, an important problem is, given QoS constraints, how to aggregate and leverage individual service’s QoS information to derive the optimal QoS of the composite service. In this paper, we propose a novel QoS model for performing flexible service selection. The key idea of the model is to relax users’ QoS constraints and try to find the most possible services satisfying users’ QoS requirements. Based on the proposed QoS framework, we develop various algorithms for making service selection on individual and composite services. We also introduce a top-k ranking strategy to reflect a user’s personalized requirements. Experimental evaluation shows the proposed QoS model is efficient and practical.

Edge computing is a new computing paradigm after cloud computing. Edge service scheduling and composition (ESC) has been well recognized as a convenient and flexible way of services sharing and integrating in industrial application fields. The ESC aims at selecting a set of existing edge service candidates with different Quality of Service (QoS) attributes (e.g., price), then compositing them to accomplish a complex task to meet users' QoS requirements, where each edge service may have multiple functionally equivalent, but different QoS metrics. A grand research challenge of the ESC based on QoS is to select proper service candidates to maximize QoS of the composited edge service and meanwhile meet the global QoS requirements. In this article, we focus on this challenge and propose a hierarchical solution for ESC. Specifically, we classify service candidates into specified grades based on their QoS attributes, and use hierarchical model to address service selection problem. Furthermore, in order to expand the flexibility of our approach, we design a near-optimal solution by decomposing the global end-to-end QoS constraints into local QoS constraints and adopting local service selecting and updating strategy based on the hierarchical model. The results of simulation-based experiments are conducted to show our approach is more efficient and valid compared to other existing approaches.

A web service is an interface of the software component that can be accessed by standard Internet protocols. The web service technology enables an application to application communication and interoperability. The increasing number of web service providers throughout the globe have produced numerous web services providing the same or similar functionality. This necessitates the use of tools and techniques to search the suitable services available over the Web. UDDI (universal description, discovery and integration) is the first initiative to find the suitable web services based on the requester's functional demands. However, the requester's requirements may also include non-functional aspects like quality of service (QoS). In this paper, the authors define a QoS model for QoS aware and business driven web service publishing and selection. The authors propose a QoS requirement format for the requesters, to specify their complex demands on QoS for the web service selection. The authors define a tree structure called quality constraint tree (QCT) to represent the requester's variety of requirements on QoS properties having varied preferences. The paper proposes a QoS broker based architecture for web service selection, which facilitates the requesters to specify their QoS requirements to select qualitatively optimal web service. A web service selection algorithm is presented, which ranks the functionally similar web services based on the degree of satisfaction of the requester's QoS requirements and preferences. The paper defines web service provider qualities to distinguish qualitatively competitive web services. The paper also presents the modelling and selection mechanism for the requester's alternative constraints defined on the QoS. The authors implement the QoS broker based system to prove the correctness of the proposed web service selection mechanism.

Component-based development (CBD) techniques have been widely used to enhance the productivity and reduce the cost for software systems development. However, applying CBD techniques to embedded software development faces additional challenges. For embedded systems, it is crucial to consider the quality of service (QoS) attributes, such as timeliness, memory limitations, output precision, battery constraints. Frequently, multiple components implementing the same functionality with different QoS properties can be used to compose a system. Also, software components may have parameters that can be configured to satisfy different QoS requirements. Composition analysis, which is used to determine the most suitable component selections and parameter settings to best satisfy the system QoS requirement, is very important in embedded software development process. In this paper, we present a model and the methodologies to facilitate composition analysis. We define QoS requirements as constraints and objectives. Composition analysis is performed based on the QoS properties and requirements to find solutions (component selections and parameter settings) that can optimize the QoS objectives while satisfying the QoS constraints. We use a multiobjective concept to model the composition analysis problem and use an evolutionary algorithm to determine the Pareto-optimal solutions efficiently.

With the proliferation of Web services as a business solution to enterprise application integration, ranking and selecting the best Web services among the providers become an important factor in the success of the business solution. Quality of service (QoS) determines the quality and usability of a service including its price, performance, reliability, integrity, accessibility, availability, interoperability, and security. Given a set of QoS attributes from a variety of sources, it is a challenge to sort through all of them and be able to get the best services that meet QoS requirement. In this paper, we describe a novel method by which Web services can be ranked and selected automatically based on a number of observed QoS parameters and feedback responses learned from prior knowledge. This new approach treats the observed Web services QoS attributes and target Web services relationship, represented by a matrix, as a statistical problem. Using singular value decomposition (SVD) technique, and an user assisted weighting system, implicit higher order correlations among Web services and their associated QoS attributes are extracted and used to estimate the selection of recommended Web services.

Service-oriented grid system requires an underpinning quality of service (QoS) support. It is an effective way to guarantee QoS requirements for discovering and selecting grid services using QoS properties. Matching services fast through comparing QoS parameters and accomplishing SLA negotiation is a very important work in service selection. In this paper, we define some basic QoS parameters for grid service which can satisfy users' QoS requirements and put forward a new concept of service quality number (SQN). SQN can well describe quantifiable metrics of service QoS. To make service matching fast and successful, we present a relevant strategy and a price model of grid service. Finally, corresponding discussion and analysis are also done in this paper

This study empirically evaluated two models of service quality pertaining to recreationists who visited a Pacific Northwest National Forest. The use of service quality ratings to measure an agency's provision of recreation services, facilities, information, experiences and so forth has grown substantially over the past decade. Greater examination of an overall measure of service quality is needed, as well as a better understanding of what specific items and service quality dimensions best predict overall service quality. In this study, the dependent variable (overall service quality) was operationalised by creating an index of quality domains. The results showed that the quality items were very good predictors of their respective domains, and that the same items were very good predictors of overall service quality. Overall these models were found to be excellent predictive models that accounted for a very high proportion of the variance. The first model, regressing the quality items on the quality dimensions, accounted for 28–50% of the variance, while about 71% of the variance was accounted for when regressing the quality items on the overall service quality measure. The results of this study add to the body of literature suggesting the use of a multiple-item index as a dependent measure of overall service quality rather than a single-item indicator of overall service quality. Additionally, the service quality items and dimensions used in this study contribute to a larger body of literature focused on developing a model of service quality that can be practically applied in an outdoor recreation setting.

Quality of service (QoS) is an important criterion for Web service selection. The work in this paper is based on QoS IC (QoS Information & Computation) framework in Taher, L. et al., (2005). QoS IC framework supports QoS-based service selection in service oriented architecture (SOA). In this paper, we extend the functionality of QoS manager component of QoS IC framework with QoS-constraints model. QoS-constraints establish association relationship between different QoS properties and are used to govern the QoS matchmaking process in the underlying QoS matchmaking algorithm. The matchmaking process maps QoS requirements of consumers with the published QoS information of providers. We enhance the matchmaking algorithm to accommodate QoS-constraints.

Der Ausdruck Quality of Service (QoS) beschreibt die Güte eines erbrachten Dienstes. QoS beschreibt Eigenschaften wie Antwortzeit, Verfügbarkeit, den Grad der Nachrichten-Verschlüsselung oder den Durchsatz. QoS ist sowohl für Multi-Media Anwendungen (Audio- und Video-Übertragung) als auch für Geschäftsanwendungen wichtig. Die vorgelegte Arbeit konzentriert sich dabei auf das Feld der Geschäftsanwendungen. Solche Anwendungen arbeiten mit Transaktionen wie etwa dem Bestellen eines Produkts oder der Überweisung von Geld zwischen Konten. QoS Eigenschaften solcher Anwendungen sind beispielsweise die Anzahl an Transaktionen während eines Zeitintervalls, die maximale Anzahl gleichzeitig mit dem System arbeitender Nutzer, oder die zu erwartende Verfügbarkeit. Durch Middleware kann die Realisierung von Verteilung vor dem Programmierer verborgen werden. In einer idealen Welt würde Middleware dasselbe für QoS leisten. Das heißt, der Entwickler spezifiziert nur die gewünschte Dienstgüte und kümmert sich nicht darum, wie sie realisiert wird. Das ist so aber nicht möglich, denn die zu erbringende Dienstgüte hat massive Auswirkungen auf das Design einer Applikation. Daher muss QoS schon in der Design-Phase angegangen werden, was mit einer rein Middleware-gestützten Herangehensweise nicht möglich ist. Die vorgelegte Arbeit zeigt, wie dieses Problem durch einen modellgetriebenen Ansatz behoben werden kann. Die Entwicklung beginnt dann mit einem Plattform-unabhängigen Modell (PIM), welches das Verhalten und die QoS Eigenschaften der Applikation beschreibt. Dieses Modell wird automatisch durch eine Modell-Transformation in ein Plattform-spezifisches Modell (PSM) umgewandelt. Das PSM beschreibt das Design einer Implementierung für eine spezifische Plattform und berücksichtigt dabei die im PIM beschriebenen QoS-Eigenschaften. Um dieses Szenario in der Praxis anwenden zu können, müssen zwei Probleme gelöst werden: das Modellieren von QoS Eigenschaften und die Modell-Transformation. Gegenwärtig erfordert das Erstellen einer Modell-Transformation detailliertes Wissen über die Modellierungssprache und ihre Interna. Um das zu vereinfachen, wurde im Rahmen dieser Arbeit die visuelle Regelbasierte Transformationssprache Kafka entwickelt. Kafka und die zugehörigen Werkzeuge bauen auf Graphtransformations-Theorie auf. Kafka vereinfacht das Erstellen von Transformationen weil es auf der Notation des PIM und PSM aufbaut. Daher muss der Entwickler nichts von den Interna (etwa dem Meta-Modell) verstehen. Um PIMs von QoS-fähigen Applikationen zu erstellen, wurde die Modellierungssprache PIQML entwickelt, welche auf UML 2.0 Komponenten, Hierarchischen Nachrichten Sequenz Diagrammen (HMSCs) und einer neuen Meta-Modell Erweiterung für QoS Verträge basiert. Die vorgelegte Arbeit zeigt, wie PIQML Modelle auf verschiedene Zielplattformen (Programmiersprachen und Middleware Produkte) abgebildet werden können. Basierend auf PIQML und Kafka wurde das Werkzeug Kase entwickelt, welches das Editieren von PIQML Modellen (PIMs), UML Modellen (PSMs) und Kafka Transformationen integriert. Das Ergebnis ist eine integrierte Werkzeug-Kette für das modellgetriebene Entwickeln QoS-fähiger verteilter Applikationen.

Nowadays, a number of web services available on the internet have been increasing rapidly. Similarly functional services are offered by different service providers. Quality of Service (QoS) has becomes an important factor to determine the most suitable service provider. Many existing QoS models use uncertain QoS attributes which vary over time and depend on service environment. The service chosen by those models may not provide a QoS as expected. In this paper, we present a QoS model using the uncertain attributes: response time, availability and reliability. In order to accurately selecting a suitable service from these uncertain attributes, our model uses a Non-parametric Test technique which tests historical QoS information that measured from client side.

The service industries are mostly customer driven and their survival in the competitive environment largely depends on quality of the services provided by them. Due to the increasing competition in the service sector, customer service is an important part of the organizational growth. The key lies in improving the service selectively, paying attention to more critical attributes as a part of improved customer satisfaction. A large number of research studies for service quality take place in the context of developing countries. There are various models suggested by many authors in relation to service quality but no model take all attributes of service quality. The main objective of this paper is to critically appraise various service quality models and identify issues for future research based on the critical analysis of literature. This study aims at evaluating the different service quality models given by different authors and identifies the need for developing a new model in today’s scenario. This study examines 19 models of service quality. Findings of the study explore new model and direction in service quality improvement for different sectors. Data for this study is collected from secondary sources. The empirical findings not only priorities different parameters of service quality but also provide guidelines to focus on the other parameters on which the marketer need to improve.

Cloud service capabilities can always be clearly indicated by Quality of Service (QoS) properties. The quality and effectiveness of cloud services can be measured at both client and server sides. The parameters such as response time, throughput and failure rate influence the QoS properties at the client side. These parameters may differ with the utilization of the application for the same service. The proposed Bayesian Personalized Ranking-based Rank Prediction Scheme (BPR-RPS) provides rank prediction of QoS properties on the client side, since client-side properties vary with the usage of the application. The proposed rank prediction framework provides ranking to the services when particular cloud services are requested by the client. Personalization of cloud providers and customers is made possible by concentrating on the item recommendation imposed on the cloud by creating user-specific ranking for a set of items. The past response of the user with respect to the item aids in decision-making. The proposed ranking framework includes the following modules: Computation of similarity index between the active and ad hoc users and finding of identical users based on similarity index values.

Research on dynamic business composition based on web service proxies

Wireless mobile radio systems have to serve users with different quality of service (QoS) requirements. Scheduling algorithms like weighted proportional fair (WPF) have been proposed considering channel gains to improve the system capacity in terms of sector throughput as well as user priorities to fulfill QoS requirements. These scheduling algorithms allow assigning different priority factors to users and services so that different QoS requirements can be fulfilled. This paper provides an analysis of the influence of users with different priorities on the sector and user throughput. It is shown analytically and by system level simulations that the average user throughput can be adjusted by choosing a specific priority factor. Furthermore, it is shown that the sector throughput decreases if WPF scheduling for users with different priorities and full buffer model are considered compared to a scenario with users having equal priority. If QoS requirements for realistic traffic models, e.g. FTP, have to be fulfilled, for each high priority user low priority users have to be removed from the system in order not to exceed an acceptable number of unsatisfied users. It is shown that the decrease in sector throughput with a realistic traffic model and QoS requirements is higher than for the full buffer model.

In an uncertain and changing environment, a composite service needs to continuously optimize its business process and service selection through runtime adaptation. To achieve the overall satisfaction of stakeholder requirements, quality tradeoffs are needed to adapt the composite service in response to the changing environments. Existing approaches on service selection and composition, however, are mostly based on quality preferences and business processes decisions made statically at the design time. In this paper, we propose a requirements-driven self-optimization approach for composite services. It measures the quality of services (QoS), estimates the earned business value, and tunes the preference ranks through a feedback loop. The detection of unexpected earned business value triggers the proposed self-optimization process systematically. At the process level, a preference-based reasoner configures a requirements goal model according to the tuned preference ranks of QoS requirements, reconfiguring the business process according to its mappings from the goal configurations. At the service level, selection decisions are optimized by utilizing the tuned weights of QoS criteria. We used an experimental study to evaluate the proposed approach. Results indicate that the new approach outperforms both fixed-weighted and floating-weighted service selection approaches with respect to earned business value and adaptation flexibility.