摘要
文章针对大数据时代的存储与访问挑战,提出一种面向大数据的分布式存储与访问优化框架。提出总体框架设计,明确了分布式存储与访问系统的整体架构和功能模块。针对数据存储问题,研究了数据压缩和存储技术的优化方法,以提高存储效率和数据可靠性。针对分布式访问问题,研究了基于负载均衡的数据访问优化方法,以提高系统的整体性能和吞吐量。通过分析和讨论,探讨了方法的特点和改进空间,为分布式存储与访问技术的进一步研究提供了参考。
This article proposes a distributed storage and access optimization framework for big data,addressing the challenges of storage and access in the era of big data.The overall framework design is proposed,clarifying the overall architecture and functional modules of the distributed storage and access system.In response to the issue of data storage,optimization methods for data compression and storage technology were studied to improve storage efficiency and data reliability.A data access optimization method based on load balancing was studied to address the issue of distributed access,in order to improve the overall performance and throughput of the system.Through analysis and discussion,the characteristics and improvement space of the method were explored,providing a reference for further research on distributed storage and access technology.
作者
马洒
尹孟洋
MA Sa;YIN Mengyang(Nanyang Vocational College of Science and Technology,Nanyang 474150,China)
出处
《通信电源技术》
2024年第7期225-227,共3页
Telecom Power Technology
关键词
大数据
分布式存储
小波变换
负载均衡
big data
distributed storage
wavelet transform
load balancing
