Passive observation-based architectures for management of web services

Web Services technologies are emerging as the standard paradigm for program-to-program interactions over the Internet. A Web Service is any application that offers its functionalities through the Internet by publishing a description of its interfaces. Web Services are gaining more and more momentum and their utilization is being spread and even standardized in many areas including e -Government, e -Telecomm, e -Health, and digital imaging. The management of Web Services will play an important role for the success of this emerging technology and its adoption by both providers and consumers. As the technology matures and spreads, consumers are likely to be very picky and restrictive with regards to the quality of the offered Web Services. Another challenging factor for the management of Web Services is related to the diversity of platforms on which Web Services are developed and deployed. In this thesis, the focus is on the management of Web Services using passive observation with the intent to have open and platform-independent management architectures capable of assessing both functional and non-functional aspects of Web Services. The bulk of the observation process is carried out by model-based entities known as observers. These observers make use of formal model such as Finite State Machines, Communicating Finite State Machines, and Extended Finite State Machines. The proposed architectures include observers developed and deployed as Web Services: mono-observer architecture and multi-observer architectures. A single observer is enough for observation of a non-composite Web Service while a network of observers is preferred when observing a composite Web Service. Passive observation requires traces' collection mechanisms which are thoroughly studied and their performance compared for all architectures. A new approach for online observation based on Extended Finite State Machine is proposed to accelerate misbehaviors' detection. This approach proposes backward and forward walks in the model to reduce possible sets of states and values of variables. I adopted a pragmatic evaluation approach to assess each of my contributions: analytical analysis and proof, implementation, and real case studies. All components of management architectures have been studied, their complexities determined, developed, and deployed. The use cases used for the evaluation of the effectiveness of the architecture, including simple and composite Web Services, are also fully implemented and deployed

Evaluation of e-learning web sites using fuzzy axiomatic design based approach

High quality web site has been generally recognized as a critical enabler to conduct online business. Numerous studies exist in the literature to measure the business performance in relation to web site quality. In this paper, an axiomatic design based approach for fuzzy group decision making is adopted to evaluate the quality of e-learning web sites. Another multi-criteria decision making technique, namely fuzzy TOPSIS, is applied in order to validate the outcome. The methodology proposed in this paper has the advantage of incorporating requirements and enabling reductions in the problem size, as compared to fuzzy TOPSIS. A case study focusing on Turkish e-learning websites is presented, and based on the empirical findings, managerial implications and recommendations for future research are offered

Final report on the evaluation of RRM/CRRM algorithms

Deliverable public del projecte EVERESTThis deliverable provides a definition and a complete evaluation of the RRM/CRRM algorithms selected in D11 and D15, and evolved and refined on an iterative process. The evaluation will be carried out by means of simulations using the simulators provided at D07, and D14.Preprin

An Intelligent QoS Identification for Untrustworthy Web Services Via Two-phase Neural Networks

QoS identification for untrustworthy Web services is critical in QoS management in the service computing since the performance of untrustworthy Web services may result in QoS downgrade. The key issue is to intelligently learn the characteristics of trustworthy Web services from different QoS levels, then to identify the untrustworthy ones according to the characteristics of QoS metrics. As one of the intelligent identification approaches, deep neural network has emerged as a powerful technique in recent years. In this paper, we propose a novel two-phase neural network model to identify the untrustworthy Web services. In the first phase, Web services are collected from the published QoS dataset. Then, we design a feedforward neural network model to build the classifier for Web services with different QoS levels. In the second phase, we employ a probabilistic neural network (PNN) model to identify the untrustworthy Web services from each classification. The experimental results show the proposed approach has 90.5% identification ratio far higher than other competing approaches.Comment: 8 pages, 5 figure

Towards an evaluation framework for medical web applications

Copyright @ 2013 EMCIS.The main aim of this study is to review and analyse various evaluation frameworks used to assess the operational effectiveness of various Information Technology (IT) processes/applications and identify their strengths in order to form a new holistic framework for economic evaluation of web applications. This research aims to address the need for a new holistic evaluation framework for the purpose of the evaluation of the medical web applications. Over the last decade more and more, companies used accountancy techniques such as the frameworks analysed in this research. This new holistic framework that was developed will include also steps regarding the indirect and intangible costs and benefits identification and their incorporation in the evaluation process. Moreover the new emerging market of the medical websites and the embedded on them web applications requires also a new evaluation framework that will provide accurate results in the estimation of the efficiency of an investment on them. The paper first presents an introduction about why economic evaluation is important when evaluating the Information Technology in organizations. Various studies are reviewed, which highlight the ever increasing importance of integrating economic evaluation processes, such as Cost Benefit Analysis (CBA) and Return on Investment (ROI), into systems and processes of organizations and economic organizations, and analyse the factors that govern their role. Finally, the evaluation frameworks and methods that are found in these studies should be used as a part of a proactive systematic action plan that the organizations could use to avoid budget reduction due to incorrect planning. The next part of this study includes a comprehensive presentation and review of past frameworks used to evaluate Information Technology. The frameworks that are reviewed are the Framework for evaluation of information systems, the Information Technology Adoption Model (ITAM), the Total Evaluation and Acceptance Methodology (TEAM) framework, the ROI Process Model and HOT-fit evaluation framework for Health Information Systems