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The efficient replica layout is an important guarantee for distributed storage systems reliability. Data replica can increase system data availability, as well as improve the system load balance ability, but it also produces energy consumption problems simultaneously. Aiming at the conflicts between efficiency improvement and energy consumption replicas bring, replica layout algorithm based on a multi-objective decomposition strategy (MDSRL) is proposed. It regards the mean file unavailability, load balance and energy consumption as optimization objectives, decomposes multi-objective problems into multiple scalar problems and optimizes them simultaneously. The optimization of each scalar problem is based on the information of several adjacent scalar problems. After multiple iterations of optimization, this paper tries to find a set of tradeoff solutions that can perform well on all three objectives. Experiments demonstrate that the solutions obtained by the MDSRL algorithm are 3.11 and 2.3 percentage points less than the multi-objective evolutionary (MOE) algorithm in mean file unavailability and energy consumption, and are 68.1 and 0.2 percentage points less than the multi-objective replica management (MORM) algorithm in the mean file unavailability and load variance, and the solutions distribution and convergence are better.

With the rapid development of computer and network technology, to deal with explosively growing mass data correctly, distributed file systems have come into being, and they have been applied in many enterprises. However, in the packet storage process, the traditional TCP/IP transmission protocol has to pass through the operating system and application software layer. It takes up many server resources and memory bus bandwidth, which places a heavy burden on the server's CPU and memory. In this paper, we analyze the research status of the distributed file system based on analyzing and comparing the advantages of RDMA over traditional TCP Ethernet communication architecture. We propose an optimization scheme for the network transmission performance of the original FastDFS to replace the original TCP module with an RDMA network communication module, and we design a lightweight distributed file system with higher performance than the original FastDFS, which is suitable for small file storage. Using the zero-copy technology and kernel bypass technology of soft RDMA, the network communication mechanism in FastDFS is optimized to free the server's CPU from heavy data processing work. In this paper, the RDMA-based FastDFS is compared with the original FastDFS. The test results show that the network transmission performance of the optimized FastDFS is improved compared with the original FastDFS, which achieves the expected effect and can better meet the requirements of mass small file storage for today's Internet applications. [ABSTRACT FROM AUTHOR]

Urban agglomeration is a primary source of global energy consumption and CO2 emissions. It is employed as a major means of modern economic and social activities. Analysis of the temporal and spatial characteristics of CO2 emissions in urban agglomerations and prediction of the future trends of CO2 emissions in urban agglomerations will help in the implementation of CO2 reduction policies within region-wide areas. So, based on that, this study contains four aspects. Firstly, it calculates the energy CO2 emissions of China's Chengdu-Chongqing urban agglomeration. Secondly, it analyzes the time and space changes in the area by using ArcGIS. Then, the STIRPAT model is used to investigate the factors influencing CO2 emissions, and the elasticity coefficient of the influencing factors is estimated using the ridge regression method, and the important influencing factors are screened on the basis of the estimated results, which are then used as input features for prediction. Finally, a combined prediction model based on the improved GM (1, N) and SVR models is constructed, and then the optimal solution is found through the particle swarm optimization algorithm. It sets up different CO2 emission scenarios to predict the energy CO2 emission of the region and its cities. The results show that, first, the CO2 emissions of the Chengdu-Chongqing urban agglomeration have accumulated year by year, but by 2030, as predicted, it will not reach its peak. The spatial layout of CO2 emissions in this region is not expected to undergo major changes by 2030. Second, population, GDP, gas and electricity consumption, and industrial structure have served as important factors affecting energy CO2 emissions in the region. Third, on the basis of the prediction results for different scenarios, the CO2 emissions in the baseline scenario are low in the short term, but the CO2 emissions in the low-carbon scenario are low in the long run. This study also puts forward some policy recommendations on how to reduce CO2 emissions. [ABSTRACT FROM AUTHOR]