Web Services in China

This chapter examines Web services in China. More specifically, it examines the state-of-the-art of China's Web services in terms of cloud services, mobile services, and social networking services through exploring several leading Web service providers in the ICT industry, including Alibaba, Tencent, China Mobile, and Huawei. This research reveals that the Chinese culture has played an important role in the success of China's Web services. The trade-off ideology and communication conventions from Chinese traditional culture, as well as Mao Zedong thought, greatly influenced the development of China's Web services. The findings of this chapter might facilitate the research and development of Web services and better understanding of the growth in China's ICT industry, as well as future trends.

A Practical Approach to Enhancement of Accuracy of Similarity Model Using WordNet towards Semantic Service Discovery

Semantic Web service discovery provides high retrieval accuracy. However, it imposes an implicit constraint to service clients that the clients must express their queries with the same domain ontologies as used by the service providers. Fulfilling this criterion is very tedious. Hence, a WordNet (general ontology)-based similarity model is proposed for service discovery, and its accuracy is enhanced to a level comparable to the accuracy of computing similarity using service specific ontologies. This is done by optimizing similarity threshold, which refers to a minimum similarity that is required to decide whether a given pair of services is similar or not. The proposed model is implemented and results are presented. The approach warrants clients to express their queries without specifying any ontology and alleviates the problem of maintaining complex domain ontologies. Moreover, the computation time of WordNet-based model is very low when compared to specific ontology-based model.

Generalized Demand-Driven Web Services

Highly developed economies are based on the knowledge society. A variety of software tools are used in almost every aspect of human life. Service-oriented architectures are limited to corporate-related business solutions. This chapter proposes a novel approach aimed to overcome the differences between real life services and software services. Using the design approaches for the current service-oriented architecture, a solution that can be implemented in open source systems has been proposed. As a result, a new approach to creating an agent for service composition is introduced. The agent itself is created by service composition too. The proposed approach might facilitate the research and development of Web services, service-oriented architectures, and intelligent agents.

A Demand-Driven Cloud-Based Business Intelligence for Healthcare Decision Making

Technology development for process enhancement has been a topic to many health organizations and researchers over the past decades. In particular, on decision support aids of healthcare professional, studies suggest paramount interests for developing technological intervention to provide better decision-support options. This chapter introduces a combined requirement of developing intelligent decision-support approach through the application of business intelligence and cloud-based functionalities. Both technological approaches demonstrate their usage to meet growing end users' demands through their innovative features in healthcare. As such, the main emphasis in the chapter goes after outlining a conceptual approach of demand-driven cloud-based business intelligence for meeting the decision-support needs in a hypothetical problem domain in the healthcare industry, focusing on the decision-support system development within a non-clinical context for individual end-users or patients who need decision support for their well-being and independent everyday living.

Approaching the Internet of Things through Integrating SOA and Complex Event Processing

The Internet of Things (IoT) provides a large amount of data, which can be shared or consumed by thousands of individuals and organizations around the world. These organizations can be connected using Service-Oriented Architectures (SOAs), which have emerged as an efficient solution for modular system implementation allowing easy communications among third-party applications; however, SOAs do not provide an efficient solution to consume IoT data for those systems requiring on-demand detection of significant or exceptional situations. In this regard, Complex Event Processing (CEP) technology continuously processes and correlates huge amounts of events to detect and respond to changing business processes. In this chapter, the authors propose the use of CEP to facilitate the demand-driven detection of relevant situations. This is achieved by aggregating simple events generated by an IoT platform in an event-driven SOA, which makes use of an enterprise service bus for the integration of IoT, CEP, and SOA. The authors illustrate this approach through the implementation of a case study. Results confirm that CEP provides a suitable solution for the case study problem statement.

Adoption of Social Media Services

The increasing diffusion of social media is attracting government organizations worldwide, including local government. Social media can help local government improve the manner in which it is engaged with community and its responsiveness whilst offering cost savings and flexibility. Yet, there is paucity of research in relation to the adoption of social media Web services in local government organizations. The aim of this chapter is to investigate the factors that drive the adoption of social media Web services within Australian local government. Using qualitative evidence, the authors find technological, organizational, and environmental factors that drive the decisions of local government organizations to adopt social media Web services. In addition to extending the existing body of knowledge, this chapter offers insight concerning important managerial implications for helping local governments to better understand social media adoption in their organizations.

Declarative Service Modeling through Adaptive Case Management

Adaptive case management addresses the shift away from the prescriptive process-centric view of operations towards a declarative framework for operational descriptions that promotes dynamic task selection in knowledge-intensive operations. A key difference between prescriptive services and declarative services is the way by which control flow is defined. Repeatable and straight-thru processes have been successfully used to model and optimise simple activity-based value chains. Increasingly, traditional process modeling techniques are being applied to knowledge intensive activities with often poor outcomes. By taking an adaptive case management approach to knowledge-intensive services, it is possible to model and execute workflows such as medical protocols that have previously been too difficult to describe with typical BPM frameworks. In this chapter, the authors describe an approach to design-level adaptive case management leveraging off existing repositories' semantically annotated business process models.

Multi-Agent Active Services for Online Social Networks

This chapter has the goal of showing how multi-agent systems can be a suitable means for supporting the development and the composition of services in dynamic and complex environments. In particular, the chapter copes with the problem of developing services in the field of social networks. After an introduction on the relationships between multi-agent systems, services, and social networks, the chapter describes how multi-agent systems can support the interaction and the collaboration among the members of a social network through a set of active services.

Artificial Neural Network for Industrial and Environmental Research via Air Quality Monitoring Network

Industrial and environmental research will always involve the study of the cause-effect relationship between emissions and the surrounding environment. The techniques of artificial intelligence such as artificial neural network can be applied in the industrial and environmental research. Chemical facilities have high risks to originate air emission events (e.g. intensive flaring and toxic gas release). They are caused by various uncertainties like equipment failure, false operation, nature disaster, or terrorist attack. Through an air-quality monitoring network, data integration is applied to identify the possible emission source and dynamic emission profiles. In this chapter, the above-mentioned application has been illustrated. It has the capability to identify the potential emission profile and characterize spatial-temporal pollutant dispersion. It provides valuable information for accidental investigations and root cause analysis for an emission event; meanwhile, it helps evaluate the regional air quality impact caused by such an emission event.

Design of Web Services for Mobile Monitoring and Access to Measurements

Provisioning of applications and value-added services for mobile (remote) monitoring and access to measurements data is supported by advanced communication models such as Internet of Things (IoT). IoT provides ubiquitous connectivity anytime and with anything. IoT applications are able to communicate with the environment, to receive information about its status, to exchange and use the information. Identification of generic functions for monitoring management, data acquisition, and access to information provides capabilities to define abstraction of transport technology and control protocols. This chapter presents an approach to design Web Services Application Programming Interfaces (API) for mobile monitoring and database access. Aspects of the Web Services implementation are discussed. A traffic model of Web Services application server is described formally. The Web Services application server handles traffic of different priorities generated by third party applications and by processes at the database server's side. The traffic model takes into account the distributed structure of the Web Services application server and applies mechanisms for adaptive admission control and load balancing to prevent overload. The utilization of Web Services application server is evaluated through simulation.