Fuzzy Reasoning Approach for Predicting Web Services QoS/QoE with ANFIS

Nowadays, the web service (WS) usage in information systems (IS) includes determining a feasible WS that fulfils a set of non-functional requirements of Quality of Services (QoS) and user’s needs of Quality of Experience (QoE). While most existing studies evaluate WS from one perspective, i.e., users, and are based on data-driven approach, which employs a numerical dataset to learn a reasoning model, they overlook that users express their needs in a non-numerical form. To address these issues, we propose a new fuzzy reasoning approach for predicting WS QoS/QoE with the adaptive neuro-fuzzy inference system (ANFIS) that encompasses multiple viewpoints and perspectives, and is also suitable for linguistic terms. To verify the efficiency, we implemented the proposed approach, conducted two experiments and compared them. The results show a good performance of the proposed approach for predicting WS QoS/QoE, and, consequently, it can be considered a suitable tool for predicting

A Review on Framework and Quality of Service Based Web Services Discovery

Selection of Web services (WSs) is one of the most important steps in the application of different types of WSs such as WS composition systems and the Universal Description, Discovery, and Integration (UDDI) registries. The more available these WSs on the Internet are, the wider the number of these services whose functions match the various service requests is. Selecting WSs with higher quality largely depends on the quality of service (QoS) since it plays a significant role in selecting such services. In achieving this selection of the best WSs, the potential WSs are ranked according to the user’s necessities on service quality. In many cases, the value of QoS ontology is realized by its support for nonfunctional features of WSs. This ontology is also capable of providing solutions to the interoperability of QoS description. Moreover, based on the QoS ontology, it becomes more possible to develop a framework of semantic WS discovery. The framework enhances the automatic discovery of WSs and can improve the users’ efficiency in finding the best web services. Thus, Web Services are software functionalities publish and accessible through the Internet. Different protocols and web mechanism have been defined to access these Services

Dynamic Formation and Strategic Management of Web Services Communities

In the last few years, communities of services have been studied in a certain numbers of proposals as virtual pockets of similar expertise. The motivation is to provide these services with high chance of discovery through better visibility, and to enhance their capabilities when it comes to provide requested functionalities. There are some proposed mechanisms and models on aggregating web services and making them cooperate within their communities. However, forming optimal and stable communities as coalitions to maximize individual and group efficiency and income for all the involved parties has not been addressed yet. Moreover, in the proposed frameworks of these communities, a common assumption is that residing services, which are supposed to be autonomous and intelligent, are competing over received requests. However, those services can also exhibit cooperative behaviors, for instance in terms of substituting each other. When competitive and cooperative behaviors and strategies are combined, autonomous services are said to be "coopetitive". Deciding to compete or cooperate inside communities is a problem yet to be investigated. In this thesis, we first identify the problem of defining efficient algorithms for coalition formation mechanisms. We study the community formation problem in two different settings: 1) communities with centralized manager having complete information using cooperative game-theoretic techniques; and 2) communities with distributed decision making mechanisms having incomplete information using training methods. We propose mechanisms for community membership requests and selections of web services in the scenarios where there is interaction between one community and many web services and scenarios where web services can join multiple established communities. Then in order to address the coopetitive relation within communities of web services, we propose a decision making mechanism for our web services to efficiently choose competition or cooperation strategies to maximize their payoffs. We prove that the proposed decision mechanism is efficient and can be implemented in time linear in the length of the time period considered for the analysis and the number of services in the community. Moreover, we conduct extensive simulations, analyze various scenarios, and confirm the obtained theoretical results using parameters from a real web services dataset