To support the explosive growth of Information and Communications Technology(ICT),Mobile Edge Comput-ing(MEC)provides users with low latency and high bandwidth service by offloading computational tasks to the network...To support the explosive growth of Information and Communications Technology(ICT),Mobile Edge Comput-ing(MEC)provides users with low latency and high bandwidth service by offloading computational tasks to the network’s edge.However,resource-constrained mobile devices still suffer from a capacity mismatch when faced with latency-sensitive and compute-intensive emerging applications.To address the difficulty of running computationally intensive applications on resource-constrained clients,a model of the computation offloading problem in a network consisting of multiple mobile users and edge cloud servers is studied in this paper.Then a user benefit function EoU(Experience of Users)is proposed jointly considering energy consumption and time delay.The EoU maximization problem is decomposed into two steps,i.e.,resource allocation and offloading decision.The offloading decision is usually given by heuristic algorithms which are often faced with the challenge of slow convergence and poor stability.Thus,a combined offloading algorithm,i.e.,a Gini coefficient-based adaptive genetic algorithm(GCAGA),is proposed to alleviate the dilemma.The proposed algorithm optimizes the offloading decision by maximizing EoU and accelerates the convergence with the Gini coefficient.The simulation compares the proposed algorithm with the genetic algorithm(GA)and adaptive genetic algorithm(AGA).Experiment results show that the Gini coefficient and the adaptive heuristic operators can accelerate the convergence speed,and the proposed algorithm performs better in terms of convergence while obtaining higher EoU.The simulation code of the proposed algorithm is available:https://github.com/Grox888/Mobile_Edge_Computing/tree/GCAGA.展开更多
Nowadays, robots generally have a variety of capabilities, which often form a coalition replacing human to work in dangerous environment, such as rescue, exploration, etc. In these operating conditions, the energy sup...Nowadays, robots generally have a variety of capabilities, which often form a coalition replacing human to work in dangerous environment, such as rescue, exploration, etc. In these operating conditions, the energy supply of robots usually cannot be guaranteed. If the energy resources of some robots are consumed too fast, the number of the future tasks of the coalition will be affected. This paper will develop a novel task allocation method based on Gini coefficient to make full use of limited energy resources of multi-robot system to maximize the number of tasks. At the same time, considering resources consumption,we incorporate the market-based allocation mechanism into our Gini coefficient-based method and propose a hybrid method,which can flexibly optimize the task completion number and the resource consumption according to the application contexts.Experiments show that the multi-robot system with limited energy resources can accomplish more tasks by the proposed Gini coefficient-based method, and the hybrid method can be dynamically adaptive to changes of the work environment and realize the dual optimization goals.展开更多
Based on the review of various methods of estimating Gini coefficient, the paper applies a quintile rule to estimate Gini coefficient of rural areas, urban areas and the whole country using the grouped income data of ...Based on the review of various methods of estimating Gini coefficient, the paper applies a quintile rule to estimate Gini coefficient of rural areas, urban areas and the whole country using the grouped income data of urban and rural residents. Besides, the paper uses the curve-fitting method to roughly estimate Gini coefficient from eye-catching Hurun Rich List and the latest poverty line. The result shows that the estimation of Gini coefficient using quintile rule is small for both urban and rural area, while the value of the whole country is obviously larger, which is above the warning line of 0.4. It is indicated that the wealth gap mainly comes from the gap between urban and rural areas. On the other hand, the estimation of Gini coefficient using curve-fitting method is as large as more than 0.7, which implies that the wealth gap is?highlighted from the analysis of the lowest and highest part of the wealth distribution. All in all, China’s current gap between the poor and the rich is serious. The reform of the income distribution needs to speed up to ensure social harmony and stability.展开更多
For the load modeling of a large power grid,the large number of substations covered by it must be segregated into several categories and,thereafter,a load model built for each type.To address the problem of skewed clu...For the load modeling of a large power grid,the large number of substations covered by it must be segregated into several categories and,thereafter,a load model built for each type.To address the problem of skewed clustering tree in the classical hierarchical clustering method used for categorizing substations,a fair hierarchical clustering method is proposed in this paper.First,the fairness index is defined based on the Gini coefficient.Thereafter,a hierarchical clustering method is proposed based on the fairness index.Finally,the clustering results are evaluated using the contour coefficient and the t-SNE two-dimensional plane map.The substations clustering example of a real large power grid considered in this paper illustrates that the proposed fair hierarchical clustering method can effectively address the problem of the skewed clustering tree with high accuracy.展开更多
Using retroactive adjustment approach of history data published by the National Bureau of Statistics （NBS）, this study has adjusted micro-level survey data of China Household Income Project Survey （CHIPS, 2007） an...Using retroactive adjustment approach of history data published by the National Bureau of Statistics （NBS）, this study has adjusted micro-level survey data of China Household Income Project Survey （CHIPS, 2007） and conducted point estimation on household income Gini coefficient using the NBS method. On this basis, the standard error of the point estimation of China＇s Gini coefficient is estimated using bootstrap method, creating a confidence interval of Gini coefficient. Results indicate that among five continuous declines of Gini coefficient between 2008 and 2013, only three declines are statistically significant. It is thus too early to jump at the conclusion that the Gini coefficient of China＇s household income distribution has already entered into a downward channel and at least the argument that China＇s Gini coefficient has been on the decline for five consecutive years is questionable.展开更多
This paper calculates the urban, rural and general Gini coefficients （hereinafter referred to as GC） of household income in 27provinces, municipalities and autonomous regions of China between 1995 and 2010 using GC ...This paper calculates the urban, rural and general Gini coefficients （hereinafter referred to as GC） of household income in 27provinces, municipalities and autonomous regions of China between 1995 and 2010 using GC calculation formulas. After calculating the GCs, this paper analyzes their trends using density function estimation in nonparametric econometrics. The results show that the GCs of household income in provincial regions tend to rise from coastal regions to inland regions. In other words, the GCs of household income in the regions tend to rise from the east to the west and they appear to be concentrated and region-specific. A discriminate analysis of economic growth and income distribution in the provincial regions by income level and GC also shows a regional characteristic, consistent with the division of eastern, central and western China and that as one analyzes household income from the east to the west, income distribution becomes more unequal and income level becomes lower.展开更多
Editorial note Income gap has been considered one of the most potent threats to China’s society and economy in the future.This paper finds that China’s residential income gap has exceeded the reasonable bound but st...Editorial note Income gap has been considered one of the most potent threats to China’s society and economy in the future.This paper finds that China’s residential income gap has exceeded the reasonable bound but still falls within the tolerable range.Following an analysis of the causes of widening income gap,the authors also attempt to lay out an institutional arrangement framework aimed at achieving fair and equitable distribution from the three respects of starting point,process and result.展开更多
文摘To support the explosive growth of Information and Communications Technology(ICT),Mobile Edge Comput-ing(MEC)provides users with low latency and high bandwidth service by offloading computational tasks to the network’s edge.However,resource-constrained mobile devices still suffer from a capacity mismatch when faced with latency-sensitive and compute-intensive emerging applications.To address the difficulty of running computationally intensive applications on resource-constrained clients,a model of the computation offloading problem in a network consisting of multiple mobile users and edge cloud servers is studied in this paper.Then a user benefit function EoU(Experience of Users)is proposed jointly considering energy consumption and time delay.The EoU maximization problem is decomposed into two steps,i.e.,resource allocation and offloading decision.The offloading decision is usually given by heuristic algorithms which are often faced with the challenge of slow convergence and poor stability.Thus,a combined offloading algorithm,i.e.,a Gini coefficient-based adaptive genetic algorithm(GCAGA),is proposed to alleviate the dilemma.The proposed algorithm optimizes the offloading decision by maximizing EoU and accelerates the convergence with the Gini coefficient.The simulation compares the proposed algorithm with the genetic algorithm(GA)and adaptive genetic algorithm(AGA).Experiment results show that the Gini coefficient and the adaptive heuristic operators can accelerate the convergence speed,and the proposed algorithm performs better in terms of convergence while obtaining higher EoU.The simulation code of the proposed algorithm is available:https://github.com/Grox888/Mobile_Edge_Computing/tree/GCAGA.
基金supported by the National High Technology Research and Development Program of China(863 Program)(2015AA015403)the National Natural Science Foundation of China(61404069,61401185)the Project of Education Department of Liaoning Province(LJYL052)
文摘Nowadays, robots generally have a variety of capabilities, which often form a coalition replacing human to work in dangerous environment, such as rescue, exploration, etc. In these operating conditions, the energy supply of robots usually cannot be guaranteed. If the energy resources of some robots are consumed too fast, the number of the future tasks of the coalition will be affected. This paper will develop a novel task allocation method based on Gini coefficient to make full use of limited energy resources of multi-robot system to maximize the number of tasks. At the same time, considering resources consumption,we incorporate the market-based allocation mechanism into our Gini coefficient-based method and propose a hybrid method,which can flexibly optimize the task completion number and the resource consumption according to the application contexts.Experiments show that the multi-robot system with limited energy resources can accomplish more tasks by the proposed Gini coefficient-based method, and the hybrid method can be dynamically adaptive to changes of the work environment and realize the dual optimization goals.
文摘Based on the review of various methods of estimating Gini coefficient, the paper applies a quintile rule to estimate Gini coefficient of rural areas, urban areas and the whole country using the grouped income data of urban and rural residents. Besides, the paper uses the curve-fitting method to roughly estimate Gini coefficient from eye-catching Hurun Rich List and the latest poverty line. The result shows that the estimation of Gini coefficient using quintile rule is small for both urban and rural area, while the value of the whole country is obviously larger, which is above the warning line of 0.4. It is indicated that the wealth gap mainly comes from the gap between urban and rural areas. On the other hand, the estimation of Gini coefficient using curve-fitting method is as large as more than 0.7, which implies that the wealth gap is?highlighted from the analysis of the lowest and highest part of the wealth distribution. All in all, China’s current gap between the poor and the rich is serious. The reform of the income distribution needs to speed up to ensure social harmony and stability.
基金supported by the Major Science and Technology Project of Yunnan Province entitled“Research and Application of Key Technologies of Power Grid Operation Analysis and Protection Control for Improving Green Power Consumption”(202002AF080001)the China South Power Grid Science and Technology Project entitled“Research on Load Model and Modeling Method of Yunnan Power Grid”(YNKJXM20180017).
文摘For the load modeling of a large power grid,the large number of substations covered by it must be segregated into several categories and,thereafter,a load model built for each type.To address the problem of skewed clustering tree in the classical hierarchical clustering method used for categorizing substations,a fair hierarchical clustering method is proposed in this paper.First,the fairness index is defined based on the Gini coefficient.Thereafter,a hierarchical clustering method is proposed based on the fairness index.Finally,the clustering results are evaluated using the contour coefficient and the t-SNE two-dimensional plane map.The substations clustering example of a real large power grid considered in this paper illustrates that the proposed fair hierarchical clustering method can effectively address the problem of the skewed clustering tree with high accuracy.
文摘Using retroactive adjustment approach of history data published by the National Bureau of Statistics （NBS）, this study has adjusted micro-level survey data of China Household Income Project Survey （CHIPS, 2007） and conducted point estimation on household income Gini coefficient using the NBS method. On this basis, the standard error of the point estimation of China＇s Gini coefficient is estimated using bootstrap method, creating a confidence interval of Gini coefficient. Results indicate that among five continuous declines of Gini coefficient between 2008 and 2013, only three declines are statistically significant. It is thus too early to jump at the conclusion that the Gini coefficient of China＇s household income distribution has already entered into a downward channel and at least the argument that China＇s Gini coefficient has been on the decline for five consecutive years is questionable.
文摘This paper calculates the urban, rural and general Gini coefficients （hereinafter referred to as GC） of household income in 27provinces, municipalities and autonomous regions of China between 1995 and 2010 using GC calculation formulas. After calculating the GCs, this paper analyzes their trends using density function estimation in nonparametric econometrics. The results show that the GCs of household income in provincial regions tend to rise from coastal regions to inland regions. In other words, the GCs of household income in the regions tend to rise from the east to the west and they appear to be concentrated and region-specific. A discriminate analysis of economic growth and income distribution in the provincial regions by income level and GC also shows a regional characteristic, consistent with the division of eastern, central and western China and that as one analyzes household income from the east to the west, income distribution becomes more unequal and income level becomes lower.
文摘Editorial note Income gap has been considered one of the most potent threats to China’s society and economy in the future.This paper finds that China’s residential income gap has exceeded the reasonable bound but still falls within the tolerable range.Following an analysis of the causes of widening income gap,the authors also attempt to lay out an institutional arrangement framework aimed at achieving fair and equitable distribution from the three respects of starting point,process and result.
