With the management refinement of heating supply, the district heating system deploys a large number of meters or sensors to monitor and control the operating status of the heating network. It often... Show More

With the management refinement of heating supply, the district heating system deploys a large number of meters or sensors to monitor and control the operating status of the heating network. It often needs to process real-time streaming data and coordinate the related enterprise business systems to make low-latency, intelligent decisions on the changes of heating network in time. Therefore, the automatic collection, on-demand dissemination and fusion of real-time sensing data play an increasingly important role in district heating systems. This article proposed an event-driven SOA based district heating system architecture with complex event processing capability, which can easily support the on-demand dissemination and aggregation of monitoring information and realize the event-driven service coordination cross different service domains. Finally, a deployed District Heating Control and Information Service System (DHCISS) in Beijing validates the effectiveness of our approach.

The convergence of information technology and diverse business requirements is making the organization information systems more complex. Quickly integrating existing systems and developing new... Show More

The convergence of information technology and diverse business requirements is making the organization information systems more complex. Quickly integrating existing systems and developing new applications to serve the requirement of flexible business environments have become a key factor for organizations to gain a competitive edge. To meet this challenge, the concept of Service Oriented Architecture (SOA) has been proposed and widely lauded as an innovative business oriented solution. To better utilize SOA's advantages, several research problems should be attached much importance among which service lifecycle management is a notable one, which is one of the critical mechanisms leading to higher service quality. A large number of service lifecycle models have been proposed in the literature while few of them clearly indicate the integration of the lifecycle processes with stakeholders. In this research, a conceptual stakeholder identification and analysis framework is proposed by which stakeholders are analyzed within different service lifecycle stages. It is believed that this method can offer the researchers in the community further insight into service lifecycle management from the stakeholder's perspective.

Service computing has become a key-enabling technology to support collaboration and interaction among business partners and customers. With the development of new emerging service-related computing... Show More

Service computing has become a key-enabling technology to support collaboration and interaction among business partners and customers. With the development of new emerging service-related computing paradigms such as Cloud Computing and Mobile Internet, more and more services are provided by different providers. These services are becoming increasingly complex. Aiming at recommending high-quality and trustful services in the complex service computing environment, this paper presents a trust-aware search engine by integrating service functionalities, QoS (quality of service) and service trust. The proposed search engine primarily contains four components: keyword-based service matching, service QoS evaluation, service reputation evaluation and a hybrid ranking method which combines the results yielded by the previous three components to produce final service recommendations. To evaluate the performance of the authors' service search engine, comprehensive experiments are conducted using a real Web service dataset. The experimental results show that our approach outperforms conventional QoS-based service selection methods. Finally, a prototype is also presented to validate the authors' trust-aware Web service search engine.

With the development of information technology, data on the Internet is growing even faster than Moore's Law. At the age of big data, more and more services are created to deal with big data, which... Show More

With the development of information technology, data on the Internet is growing even faster than Moore's Law. At the age of big data, more and more services are created to deal with big data, which are called data-intensive services. In most cases, multiple data-intensive services are assembled into a service composition to meet complicated requirements. Since the big-data transmission, which is occurred among component services as well as between a service and a data center, has great influence on the overall performance of a composition, deploying those services cannot be considered independently. This paper proposes an optimal deployment method based on a negative selection algorithm for a data-intensive service composition to reduce the cost of the data transmission. When making a deployment schedule, it considers not only the cost of data transmission among component services, but also the load balance of data centers where component services are deployed. It models the deployment problem as a combination optimization problem and extends a negative selection algorithm to get an optimal deployment plan. A series of experiments are carried out to evaluate the performance of the proposed method using different settings as well as to compare with other methods. The results show that the method outperforms others for the problem of data-intensive service composition deployment.

Hosting services on mobile devices has been considered as the key solution for domains that have special requirement on portability, timeliness, and flexibility on service deployment. Typical... Show More

Hosting services on mobile devices has been considered as the key solution for domains that have special requirement on portability, timeliness, and flexibility on service deployment. Typical examples include, among many others, military, music, healthcare, gaming, and data sharing. Despite the recent boom of mobile computing makes service deployment in mobile environment possible, significant challenges arise due to the limitations in existing mobile hardware/software capable of managing resource intensive applications. The situation gets worse when managing complex services that allow concurrent clients and requests. This paper addresses the issue related specifically to concurrency control improvement in mobile web servers to support the mobile deployment of complex services. The authors identify key factors that affect a system to respond a request, including request related factors, system resource related factors, and context. Based on this, the authors propose a dynamic heavy request classification model (DHRC) to estimate the heaviness of an incoming request using machine-learning methods. The heavy request will be detected, which requires relatively heavy system resources of the mobile server to generate a response. The authors design a dynamic request management strategy (DRMS), which reduces the number of discarded requests by adding heavy requests to a queue and processing them asynchronously. The proposed solution is implemented on Android-based mobile devices as an extension of I-Jetty web server. Experimental studies are conducted and the result indicates the effectiveness of our solution.