Background China launched a new round of healthcare-system reform in 2009 and proposed the goal of equal and guaranteed essential medical and health services for all by 2020. We aimed to investigate the changes in China’s health resources over the past ten years after the healthcare reform. Methods Data were collected from the China Statistical Yearbook and China Health Statistics Yearbook from 2009 to 2018. Four categories and ten indicators of health resources were analyzed. A descriptive analysis was used to present the overall condition. The Health Resource Density Index was applied to showcase health-resource distribution in demographic and geographic dimensions. The global and local Moran’s I were used to assess the spatial autocorrelation of health resources. Concentration Index (CI) was used to quantify the equity of health-resource distribution. A Geo-Detector model and Geographic Weighted Regression (GWR) were applied to assess the association between gross domestic product (GDP) per capita and health resources. Results Health resources have increased over the past ten years. The global and local Moran’s I suggested spatial aggregation in the distribution of health resources. Hospital beds were concentrated in wealthier areas, but this inequity decreased yearly (from CI=0.0587 in 2009 to CI=0.0021 in 2018). Primary medical and health institutions (PMHI) and their beds were concentrated in poorer areas (CI remained negative). Healthcare employees were concentrated in wealthier areas (CI remained positive). In 2017, the q-statistics indicated that the explanatory power of GDP per capita to beds, health personnel, and health expenditure was 40.7%, 50.3%, and 42.5%, respectively. The coefficients of GWR remained positive with statistical significance, indicating the positive association between GDP per capita and health resources. Conclusions From 2009 to 2018, the total amount of health resources in China has increased substantially. Spatial aggregation existed in the health-resources distribution. Health resources tended to be concentrated in wealthier areas. When allocating health resources, the governments should take economic factors into account.

Because of the bottleneck of disk I/O, the distributed file system based on disk is limited in the performance on data throughput and latency. It is a big challenge for such a system to meet the high performance requirement of the massive small-file storage.Cache has been widely used in storage system to improve the data access performance. In order to support the storage of massive small files, we have integrated memcached into our distributed file system to optimize the storage of massive small files. However eviction problem arose from LRU replacement algorithm in memcached. It means that the non-stale objects might be replaced due to large short-lived objects. Therefore, we proposed Prioritized Cache (PC) and Prioritized Cache Management (PCM) to solve the problem. The cache of memcached is reorganized and classified into permanent cache and temporary cache. Furthermore, in order to alleviate side effects on hit rate in sequential access, temporary cache is partitioned into different parts with different priorities and managed according to the priorities. We have implemented and evaluated the integrated prototype system. The experimental results show that the improved distributed file system with distributed object cache can deliver high performance on smallfile storage. Compared with the original system, the read of small files increased by a factor of 2.65 8.05, without write performance degradation.

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Replica management method has been widely used in distributed file system to improve parallelism and reliability. Traditional replica management method is synchronous replication management (SRM) which updates replicas synchronously. Because of synchronous updating, it is difficult to provide high throughput and low access latency. If the system achieves SRM in the memory hierarchy, it will take a lot of memory space.In order to improve write performance, we design a Two-Layered Replica Management Method (TLRMM) based on memory and disk. It can be used for disk-based or memory-based data storage system. TLRMM maintains 3 replicas for every chunk and store one in memory. Using asynchronous update, it can improve the system's I/O performance significantly. We integrated TLRMM in Carrier which is a distributed file system designed by Tsinghua University, and use version number to ensure replica consistency. Furthermore, in order to ensure the reliability of Carrier, we design a replica recovery strategy to solve the failure of single point. We have implemented and evaluated the integrated prototype system. The experimental results show that TLRMM can deliver high performance on distributed file system. Compared with SRM, write throughput of TLRMM increased by a factor of 1.62 2.05, without read performance degradation.

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