Optimization algorithm of energy big data storage for cloud computing in Internet of Things
Hash algorithm is currently the mainstream algorithm of data storage for cloud computing， but it has some shortcomings， such as low data processing efficiency and low fault tolerance. To solve these problems， this paper combines HDFS （Hadoop distributed file system） and Hash algorithm to optimize th...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | zho |
| Published: |
zhejiang electric power
2023-08-01
|
| Series: | Zhejiang dianli |
| Subjects: | |
| Online Access: | https://zjdl.cbpt.cnki.net/WKE3/WebPublication/paperDigest.aspx?paperID=3617a33d-925b-47d9-8681-a7e855372d0b |
| _version_ | 1797733129477160960 |
|---|---|
| author | CHEN Zuge MAO Dong RAO Hanyu ZHANG Chen ZHANG Jiuding LIU Zehan |
| author_facet | CHEN Zuge MAO Dong RAO Hanyu ZHANG Chen ZHANG Jiuding LIU Zehan |
| author_sort | CHEN Zuge |
| collection | DOAJ |
| description | Hash algorithm is currently the mainstream algorithm of data storage for cloud computing， but it has some shortcomings， such as low data processing efficiency and low fault tolerance. To solve these problems， this paper combines HDFS （Hadoop distributed file system） and Hash algorithm to optimize the data storage of cloud computing in the Internet of Things. Firstly， HDFS is used to optimize the storage architecture of structured data. Then， the storage design structure of file type data is optimized. Finally， the experiments are carried out to verify the proposed algorithm. The experimental results show that compared with the original algorithm， the data processing efficiency of the proposed optimization algorithm is improved by 24.53% on average， and the fault tolerance rate is improved by 25.56% on average， which fully shows that the proposed data storage optimization algorithm for cloud computing is more superior. |
| first_indexed | 2024-03-12T12:24:39Z |
| format | Article |
| id | doaj.art-698f4bdf9a904eba822eeb496089383a |
| institution | Directory Open Access Journal |
| issn | 1007-1881 |
| language | zho |
| last_indexed | 2024-03-12T12:24:39Z |
| publishDate | 2023-08-01 |
| publisher | zhejiang electric power |
| record_format | Article |
| series | Zhejiang dianli |
| spelling | doaj.art-698f4bdf9a904eba822eeb496089383a2023-08-30T00:46:03Zzhozhejiang electric powerZhejiang dianli1007-18812023-08-01428192610.19585/j.zjdl.2023080031007-1881（2023）08-0019-08Optimization algorithm of energy big data storage for cloud computing in Internet of ThingsCHEN Zuge0MAO Dong1RAO Hanyu2ZHANG Chen3ZHANG Jiuding4LIU Zehan5State Grid Zhejiang Information & Telecommunication Branch, Hangzhou 310000, ChinaState Grid Zhejiang Information & Telecommunication Branch, Hangzhou 310000, ChinaState Grid Zhejiang Information & Telecommunication Branch, Hangzhou 310000, ChinaState Grid Zhejiang Information & Telecommunication Branch, Hangzhou 310000, ChinaState Grid Zhejiang Information & Telecommunication Branch, Hangzhou 310000, ChinaHangzhou Innovation Institute of Beihang University, Hangzhou 310000, ChinaHash algorithm is currently the mainstream algorithm of data storage for cloud computing， but it has some shortcomings， such as low data processing efficiency and low fault tolerance. To solve these problems， this paper combines HDFS （Hadoop distributed file system） and Hash algorithm to optimize the data storage of cloud computing in the Internet of Things. Firstly， HDFS is used to optimize the storage architecture of structured data. Then， the storage design structure of file type data is optimized. Finally， the experiments are carried out to verify the proposed algorithm. The experimental results show that compared with the original algorithm， the data processing efficiency of the proposed optimization algorithm is improved by 24.53% on average， and the fault tolerance rate is improved by 25.56% on average， which fully shows that the proposed data storage optimization algorithm for cloud computing is more superior.https://zjdl.cbpt.cnki.net/WKE3/WebPublication/paperDigest.aspx?paperID=3617a33d-925b-47d9-8681-a7e855372d0benergy big datacloud computingdata storagehash algorithminternet of things |
| spellingShingle | CHEN Zuge MAO Dong RAO Hanyu ZHANG Chen ZHANG Jiuding LIU Zehan Optimization algorithm of energy big data storage for cloud computing in Internet of Things Zhejiang dianli energy big data cloud computing data storage hash algorithm internet of things |
| title | Optimization algorithm of energy big data storage for cloud computing in Internet of Things |
| title_full | Optimization algorithm of energy big data storage for cloud computing in Internet of Things |
| title_fullStr | Optimization algorithm of energy big data storage for cloud computing in Internet of Things |
| title_full_unstemmed | Optimization algorithm of energy big data storage for cloud computing in Internet of Things |
| title_short | Optimization algorithm of energy big data storage for cloud computing in Internet of Things |
| title_sort | optimization algorithm of energy big data storage for cloud computing in internet of things |
| topic | energy big data cloud computing data storage hash algorithm internet of things |
| url | https://zjdl.cbpt.cnki.net/WKE3/WebPublication/paperDigest.aspx?paperID=3617a33d-925b-47d9-8681-a7e855372d0b |
| work_keys_str_mv | AT chenzuge optimizationalgorithmofenergybigdatastorageforcloudcomputingininternetofthings AT maodong optimizationalgorithmofenergybigdatastorageforcloudcomputingininternetofthings AT raohanyu optimizationalgorithmofenergybigdatastorageforcloudcomputingininternetofthings AT zhangchen optimizationalgorithmofenergybigdatastorageforcloudcomputingininternetofthings AT zhangjiuding optimizationalgorithmofenergybigdatastorageforcloudcomputingininternetofthings AT liuzehan optimizationalgorithmofenergybigdatastorageforcloudcomputingininternetofthings |