Yong-Yi Fanjiang

A Survey on Automated Service Composition Methods and Related Techniques

As a promising, low-cost, and agile way to develop software, in recent years automatic service composition has been a popular research topic receiving a lot of attentions. For this topic, upon our long-term study and paper reviewed, we present technical survey and observation in this paper, including indispensable background and preliminary knowledge. The survey assumes under traditional composition context. Moreover, following the survey and observation, we suggest two approach patterns and point out possible future challenge as well as direction, especially to the influence of the mature of mobile devices and environment.

Modeling imprecise requirements with XML

Abstract Fuzzy theory is suitable to capture and analyze the informal requirements that are imprecise in nature, meanwhile, XML is emerging as one of the dominant data formats for data processing on the internet. In this paper, we have developed a fuzzy object-oriented modeling technique (FOOM) schema based on XML to model requirements specifications and incorporated the notion of stereotype to facilitate the modeling of imprecise requirements. FOOM schema is also transformed into a set of application programming interfaces (APIs) in an automatic manner. A schema graph is proposed to serve as an intermediate representation for the structure of FOOM schema to bridge the FOOM schema and APIs for both content validation and data access for the XML documents.

Towards a Genetic Algorithm Approach to Automating Workflow Composition for Web Services with Transactional and QoS-Awareness

Service-oriented architecture implemented by Web Services is one of the most popular and promising software development paradigm that has brought some challenging research issues today. One of the most important issues is how to automate web service composition at design phase. Currently, there are many researchers concentrating on service composition problem that can be partitioned into three parts, dynamic workflow composition, QoS-aware, and transaction-aware service selection. This paper addresses the issue of automatic composing Web Services into an executable workflow not only according to user¡¦s functional requirements but also to their transactional properties and QoS characteristics. We propose an automatic composition approach through genetic algorithm to satisfy user¡¦s functional requirements, QoS criteria, and transactional requirements automatically at the same time. Experimental results are presented.

Genetic algorithm for QoS-aware dynamic web services composition

Nowadays, the Service-Oriented Architecture (SOA) as well as orchestration technology becomes trend of software development. The benefit of SOA is that we will save cost and time extremely due to the services utilized are already exist and reuse those services as well as integrate them. Currently, the main issues of SOA are how to define workflow as well as how to select the suitable services to perform this workflow with QoS. Many approaches separate workflow defined and services with QoS selected, therefore, will sacrifice the users feasibility. In this paper, we provide an approach to deal with the dynamic service composition issue based on the genetic algorithm and cases-based reasoning. This approach can support the flexible service workflow according to the users requirements and compose the workable services to complete this workflow.

Semantic-based automatic service composition with functional and non-functional requirements in design time

ContextIn recent years, the composition of ready-made and loosely coupled services into desired systems is a common industrial approach and a widely followed research topic in academia. In the field, the current research trend is to automate this composition; however, each of the existing efforts automates only a component of the entire problem. Therefore, a real automation process that addresses all composition concerns is lacking. ObjectiveThe objective is to first identify the present composition concerns and subsequently to devise a compositional approach that covers all concerns. Ultimately, we conduct a number of experiments to investigate the proposed approach. MethodWe identify the current composition concerns by surveying and briefly describing the existing approaches. To include all of the identified concerns, the solution space that must be searched is highly dimensioned. Thus, we adopt a genetic algorithm (GA) due to its ability to solve problems with such characteristics. Proposed GA-based approach is designed with four unusual independent fitness functions. Additionally, experiments are carried out and discussions are presented for verification of the design, including the necessity for and correctness of the independence and priority of the four fitness functions. ResultsThe case studies demonstrate that our approach can automatically generate the required composite services and considers all identified concerns simultaneously. The results confirm the need for the independence of the fitness function and also identify a more efficient priority for these functions. ConclusionsIn this study, we present an all-inclusive automatic composer that does not require human intervention and effort during the composition process and is designed for users who must address multiple composition concerns simultaneously, including requirements for overall functionality, internally workable dataflow, and non-functional transaction and quality-of-service considerations. Such multiple and complex composition requirements cannot be satisfied by any of the previous single-concern composition approaches.

Search based approach to forecasting QoS attributes of web services using genetic programming

ContextCurrently, many service operations performed in service-oriented software engineering (SOSE) such as service composition and discovery depend heavily on Quality of Service (QoS). Due to factors such as varying loads, the real value of some dynamic QoS attributes (e.g., response time and availability) changes over time. However, most of the existing QoS-based studies and approaches do not consider such changes; instead, they are assumed to rely on the unrealistic and static QoS information provided by service providers, which may seriously impair their outcomes. ObjectiveTo predict dynamic QoS values, the objective is to devise an approach that can generate a predictor to perform QoS forecasting based on past QoS observations. MethodWe use genetic programming (GP), which is a type of evolutionary computing used in search-based software engineering (SBSE), to forecast the QoS attributes of web services. In our proposed approach, GP is used to search and evolve expression-based, one-step-ahead QoS predictors. To evaluate the performance (accuracy) of our GP-based approach, we also implement most current time series forecasting methods; a comparison between our approach and these other methods is discussed in the context of real-world QoS data. ResultsCompared with common time series forecasting methods, our approach is found to be the most suitable and stable solution for the defined QoS forecasting problem. In addition to the numerical results of the experiments, we also analyze and provide detailed descriptions of the advantages and benefits of using GP to perform QoS forecasting. Additionally, possible validity threats using the GP approach and its validity for SBSE are discussed and evaluated. ConclusionsThis paper thoroughly and completely demonstrates that under a realistic situation (with real-world QoS data), the proposed GP-based QoS forecasting approach provides effective, efficient, and accurate forecasting and can be considered as an instance of SBSE.

Dynamic Service Composition Using Core Service Identification

Service selection and binding for building composite services is a critical but difficult to resolve issue in the domain of service-oriented computing. This paper proposes an innovative approach to address this issue, in which every abstract component service in the composition is assigned a weight value to represent its importance according to designer scoring and basis path analysis, thereby generating a weighted service flow. Composite services, including the selected concrete component services, are produced according to the weighted service flow and genetic algorithms. The generated composite service ensures acceptable quality level and guarantees that the core component services, which are most likely to influence the overall service flow, are more robust than the others. Besides, a novel fault handling method based on the identified core services is proposed to enhance the availability of composite services. Experimental results demonstrate that the proposed approach can effectively maintain the quality of core component services.

Robust Little Flame Detection on Real-Time Video Surveillance System

This study proposed a method to detect the little flame in the early stage of fire combustion. The foreground object was extracted by motion detection and YCb Cr color clues. To avoid the noise of motion detection in different resolution videos, background edge model is used to eliminate noise instead of morphology. Next, with the help of fire characteristics, the foreground object is identified. A fire object is determined by compactness, corner flicker rate, and growth rate. The experiment can be applied to any resolution video and complex scene, both indoors and outdoors, such as squares, where people walk around and vehicles pass by. The outcome of experiment, using this proposed method, can detect the fire object accurately and exclude the undangerous fire.

University Timetabling through Conceptual Modeling

A number of approaches have been proposed in tackling the timetabling problem, such as operational research, human‐machine interaction, constraint programming, expert systems, and neural networks. However, there are still several key challenges to be addressed: easily reformulated to support changes, a generalized framework to handle various timetabling problems, and ability to incorporate knowledge in the timetabling system. In this article, we propose an automatic software engineering approach, called task‐based conceptual graphs, to addressing the challenges in the timetabling problem. Task‐based conceptual graphs provide the automation of software development processes including specification, verification, and automatic programming. Maintenance can be directly performed on the specifications rather than on the source code; moreover, hard and soft constraints can be easily inserted or removed. A university timetabling system in the Department of Computer Science and Information Engineering at National Central University is used as an illustrative example for the proposed approach.

A software engineering approach to university timetabling

We propose an automated software engineering approach, called task-based conceptual graphs (TBCG), to solving the university timetabling problem. Task-based conceptual graphs provides the automation of software development processes including specification acquisition, verification, and automatic programming. Modification can be directly performed on the specifications rather than on the source code, moreover, hard and soft constraints can be easily inserted or removed. Hence, our approach offers a certain degree of flexibility to support changes. A university timetabling system in the Department of Computer Science and Information Engineering at National Central University is used as an illustrative example for the proposed approach.