TIIS (한국인터넷정보학회)
Current Result Document :
| 한글제목(Korean Title) |
Dynamic Prime Chunking Algorithm for Data Deduplication in Cloud Storage |
| 영문제목(English Title) |
Dynamic Prime Chunking Algorithm for Data Deduplication in Cloud Storage |
| 저자(Author) |
Manogar Ellappan
Abirami S
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| 원문수록처(Citation) |
VOL 15 NO. 4 PP. 1342 ~ 1359 (2021. 04) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
The data deduplication technique identifies the duplicates and minimizes the redundant storage data in the backup server. The chunk level deduplication plays a significant role in detecting the appropriate chunk boundaries, which solves the challenges such as minimum throughput and maximum chunk size variance in the data stream. To provide the solution, we propose a new chunking algorithm called Dynamic Prime Chunking (DPC). The main goal of DPC is to dynamically change the window size within the prime value based on the minimum and maximum chunk size. According to the result, DPC provides high throughput and avoid significant chunk variance in the deduplication system. The implementation and experimental evaluation have been performed on the multimedia and operating system datasets. DPC has been compared with existing algorithms such as Rabin, TTTD, MAXP, and AE. Chunk Count, Chunking time, throughput, processing time, Bytes Saved per Second (BSPS) and Deduplication Elimination Ratio (DER) are the performance metrics analyzed in our work. Based on the analysis of the results, it is found that throughput and BSPS have improved. Firstly, DPC quantitatively improves throughput performance by more than 21% than AE. Secondly, BSPS increases a maximum of 11% than the existing AE algorithm. Due to the above reason, our algorithm minimizes the total processing time and achieves higher deduplication efficiency compared with the existing Content Defined Chunking (CDC) algorithms.
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| 키워드(Keyword) |
Content Defined Chunking
Dynamic Prime Chunking
Cloud Storage
Data Deduplication
Performance Evaluation
throughput
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| 파일첨부 |
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