DD-FoG: Intelligent Distributed Dynamic FoG Computing Framework

Nowadays, 5G networks are emerged and designed to integrate all the achievements of mobile and fixed communication networks, in which it can provide ultra-high data speeds and enable a broad range of new services with new cloud computing structures such as fog and edge. In spite of this, the complex nature of the system, especially with the varying network conditions, variety of possible mechanisms, hardware, and protocols, makes communication between these technologies challenging. To this end, in this paper, we proposed a new distributed and fog (DD-fog) framework for software development, in which fog and mobile edge computing (MEC) technologies and microservices approach are jointly considered. More specifically, based on the computational and network capabilities, this framework provides a microservices migration between fog structures and elements, in which user query statistics in each of the fog structures are considered. In addition, a new modern solution was proposed for IoT-based application development and deployment, which provides new time constraint services like a tactile internet, autonomous vehicles, etc. Moreover, to maintain quality service delivery services, two different algorithms have been developed to pick load points in the search mechanism for congestion of users and find the fog migration node. Finally, simulation results proved that the proposed framework could reduce the execution time of the microservice function by up to 70% by deploying the rational allocation of resources reasonably.

Method for Forecasting Urban National Sports and Fitness Demand Based on Ant Colony Algorithm

With the continuous development of social economy, when people are pursuing economic income, they are also gradually paying attention to their own physical health. They achieve their own physical exercise through sports such as running, fitness, and mountaineering, but these sports often require a certain venue and equipment. Therefore, in view of these sports fitness demands, the ant colony algorithm is introduced to sort out the fitness activities in the context of urban residents’ supply and demand relationships, analyze the demand from both subjective and objective aspects, and explore the lack of supply of sports facilities in this paper. Analysis is conducted from cognitive and national fitness, social needs, habits, and other perspectives. It tries to guide the rational allocation and creation of resources, obtain residents’ fitness awareness and support, and provide corresponding suggestions and support for residents’ fitness activities. The simulation experimental results show that the ant colony algorithm is effective and can support the predictive analysis of the urban national fitness demand.

Research on the Industrial Upgrade of Vegetable Growers in Shaanxi: A Cross-Regional Comparative Analysis of Experience Reference

The prime goals of this article are to classify farmers’ production structures in different regions through comparative analysis and propose a structural framework that can quantify the transformation and upgrade of the vegetable industry in Shaanxi. The study utilized New Structural Economics (NSE) theory to construct the theoretical model, and the empirical data set has been crafted from 1992 vegetable growers in the Shaanxi, Hebei, and Shandong provinces. We qualitatively evaluated the potentiality of the Shaanxi vegetable industry, facilitating an industrial upgrade by drawing on the development experience of other regions. More specifically, we utilized the tomato growers to construct a five-step analysis method to transform and upgrade the vegetable industries. This article found that the chosen three provinces have structural differences and similarities in their production sides, and, compared with Hebei and Shandong, the vegetable industry in Shaanxi is still in the catching-up stage. Hebei has similar planting characteristics to Shaanxi, but the production characteristics of growers in Shaanxi are quite different from those in Shandong. Therefore, tomato growers in Hebei are the desired learning object for growers in Shaanxi. By learning planting experience from Hebei growers, tomato growers in the Shaanxi Province can improve their yield and product quality. We found that Shaanxi farmers have 15.57 percent improvement potential in improving crop management and rational allocation of production materials. Proper information-sharing platforms should be implemented to grasp consumption trends on the demand side and guide industrial upgrading.

Research on risk management of medical and health care integration projects based on fuzzy WINGS-G1

PurposeThis study establishes a risk management system for medical and health care integration projects to address the problem of high-risk potential and a strong correlation between risk factors.Design/methodology/approachA new fuzzy WINGS-G1 model for identifying key risk factors in medical and health care integration projects is proposed by introducing the fuzzy theory and the concept of risk incidence into the Weighted Influence Non-linear Gauge System (WINGS) method.FindingsThe authors analyze the fluidity of project risk factors through complex networks to control direct risks and cut off risk transmission paths to provide a reference for risk control and prevention of medical and health care integration projects.Originality/value(1) The integration of fuzzy theory into the WINGS method solves the problem of strong subjectivity of expert scoring in the traditional WINGS method; (2) By the different probabilities of risk factors, the concept of risk incidence is introduced in the WINGS model, which is more conducive to the identification of the critical risk factors and the rational allocation and utilization of organizational resources; (3) The use of the complex network for risk interactivity analysis fully reflects the dynamic nature of risk factors in medical and health care integration projects.

Entrepreneurship and Decentralised Investment in a Planned Economy

Since the 1980s, authors of the Austrian School have argued that the problem of rational allocation in a planned economy is not computational or technical in nature (static optimisation, with given information) but a question of dynamic efficiency (innovation and the creation of new information), and that this would be impossible without market processes and free entrepreneurship. In this article, we argue to the contrary that a planned economy can effectively drive dynamic efficiency. We first reveal that the Austrian thesis on the impossibility of dynamic efficiency in socialist planning is based on tautological arguments, or on problems already solved by technological development. Secondly, we present an institutional formula for promoting innovative activities and entrepreneurship within a framework of social ownership of the means of production and social control of investment.

Optimization Algorithm and Simulation of Public Resource Emergency Scheduling Based on Wireless Sensor Technology

Public resource scheduling refers to the rational allocation and effective use of resources, while public emergency scheduling refers to the rational allocation and effective use of resources in the context of emergencies. Its main purpose is to reduce casualties and property losses caused by emergencies. This paper mainly studies the emergency scheduling of public resources based on line sensing technology and solves the scheduling problem of public resources through algorithm optimization. Firstly, combined with the positioning algorithm of wireless sensor, this paper optimizes the positioning and detection technology of wireless sensor technology. Then, we design an improved multiagent genetic algorithm (MAGA-MTERS) using natural number coding and design a penalty function to solve the model. Then, the algorithm is compared with the traditional genetic algorithm. The results show that the accurate positioning of wireless sensor technology can improve the efficiency of public resource scheduling and save the scheduling cost. The multiagent genetic algorithm optimizes the positioning function of wireless sensor. Compared with the traditional genetic algorithm, MAGA-MTERS algorithm can obtain a better solution.

Labor Industry Allocation, Industrial Structure Optimization, and Economic Growth

Industrial structure optimization is an important explanatory variable of economic growth. The allocation of production factors among industries affects the evolution of industrial structure and then acts on economic growth. Labor force is one of the most important factors of production. In recent years, there has been a significant wage difference between different industries in China’s labor market, and the employees have shifted from low-wage industries to high-wage industries. Using the sample data of 282 prefecture-level cities from 2008 to 2018, this paper tests whether this wage-guided labor industry allocation will affect economic growth and whether there is an intermediary effect of industrial structure optimization. The empirical results show that the allocation of labor force to high-wage industries not only directly hinders economic growth but also indirectly hinders economic growth through the intermediary effect of industrial structure optimization. Furthermore, this paper makes a comparative study in different regions. The research conclusion shows that promoting the optimization of industrial structure and economic growth depends on correcting the price distortion of labor market and guiding the cross-industry rational allocation of labor force.

Technologies of financial flows sustainable management of the Russian banking sector

Subject. This article deals with the issues of rational allocation and management of macro-financial flows of the banking sector. Objectives. The article aims to interpret technologies of sustainable management of financial flows of the banking sector. Methods. For the study, I used post evaluation, systems, functional and structural, evolutionary, and dynamic analyses, and the techniques of observation, classification, grouping, sampling, comparison, and generalization. Conclusions and Relevance. To manage the macro-financial flows of the banking sector, financial technologies should be used both within the banking sector and cooperation between the sector and the Bank of Russia, and different sectors of the economy. The introduction of financial technologies will help the banking sector manage macro-financial flows in a sustainable manner, reduce regulatory burden and improve the efficiency of compliance with the Bank of Russia's regulatory requirements, and risk management.

Characterizing the complex influence of the urban built environment on the dynamic population distribution of Shenzhen, China, using geographically and temporally weighted regression

Big data can provide new insights for smart city planning. This study exploits mobile-phone locating-request (MPLR) data as a proxy for real-time intra-urban population distribution. It models the relationship between the dynamic population distribution and the urban built environment using geographically and temporally weighted regression (GTWR), which can account for spatial and temporal non-stationarity simultaneously. A case study is undertaken based on MPLR records in Shenzhen, China and points of interest-based urban environment data aggregated to grid zones. Compared with previous models, GTWR yields a better result. Furthermore, the spatiotemporal coefficients are analyzed and compared. The results suggest that the patterns of urban population distribution are more complex during weekends than during weekdays. The coefficients of the company density variable are significantly higher during weekdays than weekends, while the coefficients associated with residential buildings are lower during weekday afternoons. Hence, the urban built environment plays an important role in the dynamic distribution of the population at different times. The findings show that the GTWR model in combination with MPLR and points of interest-based urban environment data can assist urban planners in gaining a better understanding of the spatiotemporal dynamics of the population distribution, thereby providing potential inputs to the rational allocation of public resources over space and time.

Rational allocation of the resource designated for comprehensive safety assurance at an enterprise: the problem statement

Introduction. Corporate resources translate into a strong in-house capacity that ensures sustainable production processes. We present a novel integrated area of activity, whose purpose is to solve problems by identifying the factors of influence, coming from employees of versatile departments (structural units) and focused on industryspecific (sectoral) functions that are part of the comprehensive safety system of an enterprise.Methods of research. The author employed the established methods of comprehensive safety assurance to analyze a number of approaches. He also explored the features of their application. The author also substantiated the choice of the Lagrange multiplier method, used to formulate the problem of rational allocation of the resource designated for the sustainable performance of functions that assure the comprehensive safety of an enterprise.Problem statement. The author addresses the problem of rational allocation of the resource (the labor potential), considered as a factor of influence produced on the sustainable performance of industry-specific (sectoral) functions that comprise the system of comprehensive safety of an enterprise. An exemplary solution. The author offers an example that represents a description of the process of consecutive identification of critical points that are relevant to the impact (a coefficient) produced by the personnel on the sustainable performance of industry-specific (sectoral) functions that contribute to the comprehensive safety of an enterprise.Conclusions. Solutions for specific tasks, forming part of a methodologically described problem, will make it possible to develop a methodology for the synthesis of the comprehensive safety which is adaptable to different conditions of operation of an enterprise (day-to-day operations, as well as threats and emergencies of natural and man-induced origin), and each is of great economic importance for Russia.