Porównanie wydajności wybranych technologii tworzenia usług sieciowych w aspekcie zastosowań w aplikacjach internetowych

The article presents a comparative analysis of selected web service development technology. The analysis consists on a comparison of services using SOAP with RESTful web service and frameworks support the creation of web service in Java: Apache CXF, Spring WS, Jersey. In the first the analysis is based on a static metrics, compares the sample applications. In the second stage, the analysis raise the issue of performance, and compares the selected technologies in terms response time service.Artykuł przedstawia analizę porównawczą wybranych technologii tworzenia usług sieciowych. Analiza polega na porównaniu usług wykorzystujący protokół SOAP z usługami typu RESTful oraz szablonów wspomagających tworzenie usług w języku Java: Apache CXF, Spring WS, Jersey. W pierwszej kolejności analiza bazuje na metrykach statycznych porównując przykładowe aplikacje. W drugim etapie analiza skupia się na kwestii wydajności i porównuje wybrane technologie pod kątem czasu odpowiedzi usługi

A Feedback-corrected Collaborative Filtering for Personalized Real-world Service Recommendation

The emergence of Internet of Things (IoT) integrates the cyberspacewith the physical space. With the rapid development of IoT, large amounts of IoTservices are provided by various IoT middleware solutions. So, discovery and selectingthe adequate services becomes a time-consuming and challenging task. This paperproposes a novel similarity-measurement for computing the similarity between servicesand introduces a new personalized recommendation approach for real-world servicebased on collaborative filtering. In order to evaluate the performance of proposedrecommendation approach, large-scale of experiments are conducted, which involvesthe QoS-records of 339 users and 5825 real web-services. The experiments resultsindicate that the proposed approach outperforms other compared approaches in termsof accuracy and stability

An adaptive trust based service quality monitoring mechanism for cloud computing

Cloud computing is the newest paradigm in distributed computing that delivers computing resources over the Internet as services. Due to the attractiveness of cloud computing, the market is currently flooded with many service providers. This has necessitated the customers to identify the right one meeting their requirements in terms of service quality. The existing monitoring of service quality has been limited only to quantification in cloud computing. On the other hand, the continuous improvement and distribution of service quality scores have been implemented in other distributed computing paradigms but not specifically for cloud computing. This research investigates the methods and proposes mechanisms for quantifying and ranking the service quality of service providers. The solution proposed in this thesis consists of three mechanisms, namely service quality modeling mechanism, adaptive trust computing mechanism and trust distribution mechanism for cloud computing. The Design Research Methodology (DRM) has been modified by adding phases, means and methods, and probable outcomes. This modified DRM is used throughout this study. The mechanisms were developed and tested gradually until the expected outcome has been achieved. A comprehensive set of experiments were carried out in a simulated environment to validate their effectiveness. The evaluation has been carried out by comparing their performance against the combined trust model and QoS trust model for cloud computing along with the adapted fuzzy theory based trust computing mechanism and super-agent based trust distribution mechanism, which were developed for other distributed systems. The results show that the mechanisms are faster and more stable than the existing solutions in terms of reaching the final trust scores on all three parameters tested. The results presented in this thesis are significant in terms of making cloud computing acceptable to users in verifying the performance of the service providers before making the selection

Genetic Programming for QoS-Aware Data-Intensive Web Service Composition and Execution

Web service composition has become a promising technique to build powerful enterprise applications by making use of distributed services with different functions. In the age of big data, more and more web services are created to deal with a large amount of data, which are called data-intensive services. Due to the explosion in the volume of data, providing efficient approaches to composing data-intensive services will become more and more important in the field of service-oriented computing. Meanwhile, as numerous web services have been emerging to offer identical or similar functionality on the Internet, web service composition is usually performed with end-to-end Quality of Service (QoS) properties which are adopted to describe the non-functional properties (e.g., response time, execution cost, reliability, etc.) of a web service. In addition, the executions of composite web services are typically coordinated by a centralized workflow engine. As a result, the centralized execution paradigm suffers from inefficient communication and a single point of failure. This is particularly problematic in the context of data-intensive processes. To that end, more decentralized and flexible execution paradigms are required for the execution of data-intensive applications. From a computational point of view, the problems of QoS-aware data-intensive web service composition and execution can be characterised as complex, large-scale, constrained and multi-objective optimization problems. Therefore, genetic programming (GP) based solutions are presented in this thesis to address the problems. A series of simulation experiments are provided to demonstrate the performance of the proposed approaches, and the empirical observations are also described in this thesis. Firstly, we propose a hybrid approach that integrates the local search procedure of tabu search into the global search process of GP to solving the problem of QoS-aware data-intensive web service composition. A mathematical model is developed for considering the mass data transmission across different component services in a data-intensive service composition. The experimental results show that our proposed approach can provide better performance than the standard GP approach and two traditional optimization methods. Next, a many-objective evolutionary approach is proposed for tackling the QoS-aware data-intensive service composition problem having more than three competing quality objectives. In this approach, the original search space of the problem is reduced before a recently developed many-objective optimization algorithm, NSGA-III, is adopted to solve the many-objective optimization problem. The experimental results demonstrate the effectiveness of our approach, as well as its superiority than existing single-objective and multi-objective approaches. Finally, a GP-based approach to partitioning a composite data-intensive service for decentralized execution is put forth in this thesis. Similar to the first problem, a mathematical model is developed for estimating the communication overhead inside a partition and across the partitions. The data and control dependencies in the original composite web service can be properly preserved in the deployment topology generated by our approach. Compared with two existing heuristic algorithms, the proposed approach exhibits better scalability and it is more suitable for large-scale partitioning problems

Service recommendation and selection in centralized and decentralized environments.

With the increasing use of web services in everyday tasks we are entering an era of Internet of Services (IoS). Service discovery and selection in both centralized and decentralized environments have become a critical issue in the area of web services, in particular when services having similar functionality but different Quality of Service (QoS). As a result, selecting a high quality service that best suits consumer requirements from a large list of functionally equivalent services is a challenging task. In response to increasing numbers of services in the discovery and selection process, there is a corresponding increase of service consumers and a consequent diversity in Quality of Service (QoS) available. Increases in both sides leads to a diversity in the demand and supply of services, which would result in the partial match of the requirements and offers. Furthermore, it is challenging for customers to select suitable services from a large number of services that satisfy consumer functional requirements. Therefore, web service recommendation becomes an attractive solution to provide recommended services to consumers which can satisfy their requirements.In this thesis, first a service ranking and selection algorithm is proposed by considering multiple QoS requirements and allowing partially matched services to be counted as a candidate for the selection process. With the initial list of available services the approach considers those services with a partial match of consumer requirements and ranks them based on the QoS parameters, this allows the consumer to select suitable service. In addition, providing weight value for QoS parameters might not be an easy and understandable task for consumers, as a result an automatic weight calculation method has been included for consumer requirements by utilizing distance correlation between QoS parameters. The second aspect of the work in the thesis is the process of QoS based web service recommendation. With an increasing number of web services having similar functionality, it is challenging for service consumers to find out suitable web services that meet their requirements. We propose a personalised service recommendation method using the LDA topic model, which extracts latent interests of consumers and latent topics of services in the form of probability distribution. In addition, the proposed method is able to improve the accuracy of prediction of QoS properties by considering the correlation between neighbouring services and return a list of recommended services that best satisfy consumer requirements. The third part of the thesis concerns providing service discovery and selection in a decentralized environment. Service discovery approaches are often supported by centralized repositories that could suffer from single point failure, performance bottleneck, and scalability issues in large scale systems. To address these issues, we propose a context-aware service discovery and selection approach in a decentralized peer-to-peer environment. In the approach homophily similarity was used for bootstrapping and distribution of nodes. The discovery process is based on the similarity of nodes and previous interaction and behaviour of the nodes, which will help the discovery process in a dynamic environment. Our approach is not only considering service discovery, but also the selection of suitable web service by taking into account the QoS properties of the web services. The major contribution of the thesis is providing a comprehensive QoS based service recommendation and selection in centralized and decentralized environments. With the proposed approach consumers will be able to select suitable service based on their requirements. Experimental results on real world service datasets showed that proposed approaches achieved better performance and efficiency in recommendation and selection process.N/

Integration und Konnexion : Tagungsband zur 26. AKWI-Jahrestagung vom 15. bis 18.09.2013 an der Technischen Hochschule Mittelhessen

Das aufgerufene Thema „Herausforderungen an die Wirtschaftsinformatik: Integration und Konnexion“ provozierte Beiträge, die thematisch ein sehr breites Spektrum abdecken. Neben theoretischen Betrachtungen und Definitionen des sicher noch nicht final geprägten Begriffs der Konnexion gab es auch sehr praktische Beiträge wie die Darstellung von konkreten prototypischen Entwicklungsvorhaben. Auch das ist ein Indiz für die lebendige Landschaft der Wirtschaftsinformatik an den deutschsprachigen Hochschulen für Angewandte Wissenschaften

Extending Web Service Architecture with a Quality Component: Web Service Architecture and Quality Component

The Web service technology provides standard mechanisms for describing the interface of the services available on the Web, as well as protocols for locating such services and invoking them. Each Web service has an associated Web Services Description Language (WSDL) document which describes how it works and how to invoke it. Such document is registered at a Universal Description, Discovery and Integration (UDDI) registry that provides a discovery service for the WSDL descriptions. The Web services architecture consists of three components: Service Provider, Service Requester and UDDI Registry, and the interactions between them through publish, find, and bind operations. Between finding and binding steps there is another crucial step, which is not fully considered by current approaches. This is the step of selection. The UDDI service registry hosts hundreds of similar Web services, which makes it difficult for the service requesters to choose from them, as the selection is based on the functional properties only. However, many similar services are differentiated by their quality criteria. Therefore, quality criteria are important to be considered in the web service selection. This thesis proposes a quality-based Web service architecture (QWSA) that extends the current Web service architecture with a quality server. The quality server consists of four main components: quality manager, quality matchmaker, quality report analyzer, and quality database. The main purpose of quality server is to assist service requester to select the best available service that fulfils his/her preference by matching between a service requester’s quality requirement and the service providers’ quality specifications. In addition, this thesis reports the development of a quality matchmaking process (QMP) based on the proposed architecture by building a quality service selection system (QSSS). This QSSS has been verified and validated using a case study of Amazon E-commerce service (ECS)