Key Technology Research On Business Collaboration For Smart Government

Smart city construction’s goals mainly include three aspects:public services will be more popular and favorable; social management will be more efficient; and industrial systems will be more optimized. The realization of smart government is the foundation of smart city construction. The construction of smart government mainly includes the following aspects:the unified management of the e-government cloud infrastructure; integration and sharing of information and resources; business collaboration and cooperation; application and service of wisdom; and intelligent decisions based on large data processing and safety guarantee system, etc. Based on the e-government, smart government is to integrate multi-sectoral information resources in a wide range, integrate a variety of business functional systems, and to provide intelligence services according to the combination of dynamic needs. Its key technology is the deep integration of the heterogeneous information resources, and dynamic collaboration between heterogeneous systems, etc., while the existing integration method based on the middleware has been unable to solve these problems completely. Expanding of the service oriented architecture (SOA) and Web service technology will make them charactered by formal description of function and data, semantic self-recognition, and combination of semantic conformity, etc., which will bring extensive practical and theoretical value to the smart government construction.Taking the smart government cloud platform design of Wuhan as the background, this paper was to solve the key problems of business collaboration and cooperation in the construction of smart government in our country, which were widespread across domains and across time and space. The existing SOA and Web services techno logies were faced with challenges in business collaboration and system integration, the reason of which was the great coverage of the smart government, and to ask for a service on customization and combination of needs. How to find the positioning service function, and how to quickly combine multiple services to meet the demand of new applications were the two main problems to be solved. The main research work in this paper was to apply semantic technology to deal with four basic problems in the smart government system:a precise semantic description of business services to provide accurate identification service; Using reasoning technology to accurately find and locate services; Using semantic information to assist service composition; Using semantic technology service to realize replacement and invocation.According to the characteristics of the e-government and semantic technology development, this paper presented a semantic model of e-government Web services, and presented the ontology definition. In order to effectively organize and manage a large number of services, this paper studied the establishment of a smart government business classification model and ontology. At the same time, based on the needs of describing services function semantics, according to the relevant national standards to develop smart government information resources classification ontology and public data elements onotology, the paper was to provide the basis for annotating service10semantics and use the general mechanism of OWL DL to describe the PE semantics of the service function. In order to guarantee the service with accurate and enough semantic information, this paper designed the semantic register service interface. Through what mentioned above, this paper solved the problem of the service semantic modeling, and created foundation for the solution of service discovery and combination.Service discovery based on semantic reasoning could accurately locate service, but due to the inherent complexity of reasoning technology, in the face of the great smart government service space, the efficiency of reasoning was unacceptable. This paper introduced a relational query technology, and used relational database to store management service registration information, which first conducted semantic retrieval based on keywords for fast shrinking of service quantity, and then conducted semantic reasoning to accurately locate the candidate services in this relatively small space. Because of the efficient retrieval of relational database, this method could be a very good balance between positioning accuracy and efficiency of service discovery.For another key issue in the business collaboraion of smart government-service composition, this paper took the search algorithm based on "AND/OR graph", namely the combination problem was converted to AND/OR graph solution. Because there existed high time complexity in AND/OR graph search algorithms, it had to reduce the size of problem searching space to improve the practicability of the method. In constructing the service composition problem state diagram, it did not directly use the registration service to generate, but to extract the abstract service to construct according to the business categories, which could effectively reduce the searching size of state diagram and maintain stability. With the problem that AND/OR graph could be only used to describe the IO semantics of the service but could not be used to depict PE semantics, service composability model was introduced, which comprehensively studied service grammatical and semantic composability among services, and by calculating the candidate combination degree, which could guarantee the semantic consistency between the component services. Another purpose of composability model was that as an important reference indicator replacing the service selection, it could examine the success rate of the combination of service execution after replacement.This paper studied the key problems in the process of smart government system integration and business collaboration. In view of the difficulties of using the SOA and Web services technologies to solve these problems, the author of this paper put forward an effective solution and applied these studies in the planning and design of cloud computing platform of Wuhan smart government.