The IT system of manufacturing enterprises usually has many problems, such as complex industrial software, different development languages, diverse communication protocols, and complex operation environment. Cloud service bus (CSB) technology based on service model encapsulates various applications existing in enterprises by means of the integration of cloud service bus and micro services, which can realize the rapid cloud migration and deployment of heterogeneous industrial application software. Theoretically, after the production system is connected to CSB, it can be arranged arbitrarily by service choreography technology to produce any possible products. However, in the context of industrial Internet, the production system connected to CSB corresponds to the equipment, materials, personnel, and other resources on the production line one by one. These production nodes need to consider the production capacity and cost of production service nodes and the output value of the whole production network, and cannot be combined arbitrarily. Therefore, when integrating production service nodes, we should not only consider the technical integration, but also consider whether the production conditions support this integration. To solve the problem of production node integration in CSB, a dynamic collaboration model of production network based on cloud service bus is proposed in this paper. The model takes the capacity, cost, and production relationship of production nodes as constraints, and the overall efficiency of production network as the optimization goal. The model can calculate the new creation, modification, deletion, and other scheduling operations of production line services in real time and give the production plan with the highest resource utilization and the greatest value in the current production network. The model can improve the rationality and economy of service choreography and give full play to the value of production network. Taking an enterprise with 11 production nodes and 5 production lines as an example, this paper discusses in detail how to use this model to calculate the optimal production organization scheme and the maximum output value of the enterprise.
Subsidy of urban public transport is very important to institutional arrangements for supplying public traffic service. As a government intervention means, it reflects profound relation with local authority and operating enterprises of public transport. In such sense, the subsidy reform can be regarded as reconstructing relationship with government and enterprises and regenerating mode of operating, which is a part of the reforms of China's transition to a socialist market economy. This paper treats the subsidy as an incentive design, analyses the problems of traditional framework of subsidy mechanism for urban public transport in China, discusses the relationship between public transport enterprises and government, tries to reconstruct framework of subsidy mechanism, and studies on institutional arrangement of subsidy with applying competitive franchising system. As a result, the goal of promoting the development of china's urban public transport in the future, decreasing government public financial supports and maximizing the social efficiency can be realized.
With public emergencies’ frequent occurrences and mobile internet’s fast developments, emergency information managements under mobile Internet environment become a hotspot of study.This paper applies the complex network theory to the study on emergency information’s spread under mobile internet environment. This paper constructs the emergency information’s spread model with different clustering coefficient under mobile internet environment to study emergency information’s spread trend. The result shows that under mobile internet environment there is high relevance between the emergency information’s spread trend and the topological network’s clustering coefficient. Governments can adjust the clustering coefficient to improve the management of emergency information under mobile internet environment.
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