Chi-Chun Lo

A Fuzzy Model for Selection of QoS-Aware Web Services

With the increasing popularity of employing Web services, quality of service (QoS) measure of service becomes a significant concern for service consumers and providers. However, current technologies are poor to identify the relative importance of nonfunctional QoS criteria for Web services and they are not fitting well for selecting the appropriate service. In this paper, a new scheme for right selection of QoS-aware of Web services which exploits fuzzy logic to locate and select the right service based on customers preference or satisfaction degree. The aim is to compute both functional and non-functional weightings of QoS criteria and to assist customers to make the right choice for Web services

On optimal decision for QoS-aware composite service selection

The increasing popularity of employing web services for distributed systems contributes to the significance of service discovery. However, duplicated and similar functional features existing among services require service consumers to include additional aspects to evaluate the services. Generally, the service consumers would have different view on the quality of service (QoS) of service attributes. How to select the best composite service in theory among available service (WS) candidates for consumers is an interesting practical issue. This work proposes a QoS-aware service selection model based on fuzzy linear programming (FLP) technologies, in order to identify their dissimilarity on service alternatives, assist service consumers in selecting most suitable services with consideration of their expectations and preferences. This approach can obtain the optimal solution of consensual weight of QoS attribute and fuzzy positive ideal solution (FPIS) by extending LINMAP method, developed by Srinivasan and Shocker. Finally, two numerical examples are given to demonstrate the process of QoS-aware web service selection. The experimental results demonstrated that it is a feasible and supplementary manner in selecting the of web services.

Fuzzy matchmaking for Web services

To fully realise the potential of Web services it is necessary to develop viable dynamic discovery and composition techniques. Matchmaking is considered as one of the crucial factors to ensure dynamic discovery and composition of Web services. Current matchmaking methods are inadequate given their inability to abstract and classify the underlying data of Web services. Instead, they classify Web services based on the capability of services, software signatures, and so on. This paper proposes a novel framework which exploits fuzzy logic in order to abstract and classify the underlying data of Web services as fuzzy terms and rules. The aim is to increase the efficiency of the discovery of Web services and to allow imprecise or vague terms in the search query.

A hybrid information security risk assessment procedure considering interdependences between controls

Risk assessment is the core process of information security risk management. Organizations use risk assessment to determine the risks within an information system and provide sufficient means to reduce these risks. In this paper, a hybrid procedure for evaluating risk levels of information security under various security controls is proposed. First, this procedure applies the Decision Making Trial and Evaluation Laboratory (DEMATEL) approach to construct interrelations among security control areas. Secondly, likelihood ratings are obtained through the Analytic Network Process (ANP) method; as a result, the proposed procedure can detect the interdependences and feedback between security control families and function in real world situations. Lastly, the Fuzzy Linguistic Quantifiers-guided Maximum Entropy Order-Weighted averaging (FLQ-MEOWA) operator is used to aggregate impact values assessed by experts, applied to diminish the influence of extreme evaluations such as personal views and drastic perspectives. A real world application in a branch office of the health insurance institute in Taiwan was examined to verify the proposed procedure. By analyzing the acquired data, we confirm the proposed procedure certainly detects the influential factors among security control areas. This procedure also evaluates risk levels more accurately by coping with the interdependencies among security control families and determines the information systems safeguards required for better security, therefore enabling organizations to accomplish their missions.

Service Selection Based on Fuzzy TOPSIS Method

With rapid development of service-oriented architecture and cloud computing, web services have been widely adopted for developing various kinds of applications. A set of non-functional requirements such as QoS has become important criteria for service selection. The nature of QoS based service selection can be treated as a multiple criteria group decision making (MCDM) problem. This article presents an evaluation method based on the technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) to help service consumers and providers to analyze available web services with fuzzy opinions. A set of pre-defined linguistic variables parameterized by triangular fuzzy numbers, are used by the group to evaluate the weights of various criteria and the ratings of each alternative web service. As a result, the available alternative web services can be ordered according to group preference. Finally, a numerical example is provided to demonstrate the computational efficiency of the proposed fuzzy TOPSIS method.

A multiobjective hybrid genetic algorithm for the capacitated multipoint network design problem

The capacitated multipoint network design problem (CMNDP) is NP-complete. In this paper, a hybrid genetic algorithm for CMNDP is proposed. The multiobjective hybrid genetic algorithm (MOHGA) differs from other genetic algorithms (GAs) mainly in its selection procedure. The concept of subpopulation is used in MOHGA. Four subpopulations are generated according to the elitism reservation strategy, the shifting Prufer vector, the stochastic universal sampling, and the complete random method, respectively. Mixing these four subpopulations produces the next generation population. The MOHGA can effectively search the feasible solution space due to population diversity. The MOHGA has been applied to CMNDP. By examining computational and analytical results, we notice that the MOHGA can find most nondominated solutions and is much more effective and efficient than other multiobjective GAs.

Reaching consensus: A moderated fuzzy web services discovery method

Web services are used for developing and integrating highly distributed and heterogeneous systems in different domains such as e-business, grid services, and e-government systems. Web services discovery is a key to dynamically locating desired web services across the Internet. Prevailing research trend is to dynamically discover and compose web services in order to develop composite services that provide enhanced functionality. Existing discovery techniques do not take into account the diverse preferences and expectations of service consumers and providers which are generally used for searching or advertising web services. This paper presents a moderated fuzzy web service discovery approach to model subjective and fuzzy opinions, and to assist service consumers and providers in reaching a consensus. The method achieves a common consensus on the distinct opinions and expectations of service consumers and providers. This process is iterative such that further fuzzy opinions and preferences can be added to improve the precision of web service discovery. The proposed method is implemented as a prototype system and is tested through various experiments. Experimental results demonstrate the effectiveness of the proposed method.

An evidence-based scheme for web service selection

Existing studies on the web service selection problem focus mainly on the functional QoS properties of the service rather than the consumer satisfaction and trust aspects. While a good QoS enhances the reputation of a service, different consumers invariably hold differing views of the service contents. Some service reputation approaches primarily consider the consumer’s prior experience of the service via opinion feedback system, may neglect the effect of social trust transition in the recommendations of others. As a result, the problem of reaching consensus on the level of consumer trust regarding service becomes one of key issues in service selection. This study proposes a trust-based service selection model to estimate the degree of consumer trust in a particular service based on the consumers’ direct experience and indirect recommendation of the service. In the proposed approach, the degree of consumer trust is correctly estimated by extending Dempster–Shafer evidence reasoning theory to the reputation computation using consumers’ direct experience and incorporating Jøsang’s belief model for solving the trust transition problem in the indirect recommendation of the service. The proposed model effectively enables deception detection by means of existing bodies of evidence, and therefore excludes the fraudulent evidence of malicious evaluators from the selection process. In addition, a quality index is proposed to help third party (TTP) examine the body of evidence and make the outranking result more reliable. Importantly, the quality index is based not only on the confidence degree of the evidence, but also on the support degree, and therefore discovers the effects of intentional negative assessments. The validity of the proposed approach is demonstrated numerically by means of two service selection examples.

Consumer-centric QoS-aware selection of web services

There exist many web services which exhibit similar functional characteristics. It is imperative to provide service consumers with facilities for selecting required web services according to their non-functional characteristics or quality of service (QoS). However, the selection process is greatly complicated by the distinct views of service providers and consumers on the services QoS. For instance, they may have distinct views of the service reliability-wherein a consumer considers that a service is reliable if its success rate is higher than 99%, while a provider may consider its service as reliable if its success rate is higher than 90%. The aim of this paper is to resolve such conflicts and to ensure consensus on the QoS characteristics in the selection of web services. It proposes a QoS Consensus Moderation Approach (QCMA) in order to perform QoS consensus and to alleviate the differences on QoS characteristics in the selection of web services. The proposed approach is implemented as a prototype tool and is tested on a case study of a hotel booking web service. Experimental results show that the proposed approach greatly improves the service selection process in a dynamic and uncertain environment of web services.

A user centric service-oriented modeling approach

With rapid development of service-oriented architecture and cloud computing, web services have been widely employed on the Internet. Quality of Service (QoS) is a very important criterion for service consumers to measure and select services. The selection of web services with respect to non-functional QoS criteria can be considered as a Multiple Criteria Decision Making (MCDM) problem when multiple consumers need to share a number of services. This paper describes a new user centric service-oriented modeling approach which is featured by integrating fuzzy Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) and Service Component Architecture (SCA) to facilitate web service selection and composition and to effectively satisfy a group of service consumers’ subjective requirements and preferences in the dynamic environment. The main contribution of this method is able to translate a group of users’ fuzzy requirements to services as well as model different levels of hardware and software as services to meet the requirements. We also design a simulated environment that includes 8*8 LED matrix on a circuit board that corresponds to an office with different appliances to demonstrate the dynamic service selection and binding. The simulation is used to assess the computational efficiency of the fuzzy TOPSIS method and the effectiveness of the proposed system.