تصميم خوارزمية إلغاء بيانات مكررة فعالة للملفات الصوتية في التخزين السحابي

عمار زقزوق; حسن حسن

doi:10.5281/zenodo.19347954

Authors

Prof. Dr. Ammar Zakzouk Al Wataniya Private University
Hasan Hasan Homs University

DOI:

https://doi.org/10.5281/zenodo.19347954

Keywords:

Deduplication, Hash Table, MD6, Audio Files, Cloud Storage

Abstract

Duplicate data is a major problem in big data storage systems because it consumes additional space and affects data organization, management, and processing, while ideal systems are expected to use storage capacity efficiently. To address this, hash algorithms are used to generate hash keys for files, so that identical files share the same key. However, different files may sometimes receive the same key, which is known as a collision, and the likelihood of this depends on the key length: the longer the key, the lower the probability of collision. When a file is uploaded to cloud storage, its hash key is compared with the keys already stored, but as the volume of data grows, the search time increases. This paper proposes a file-level deduplication technique for audio data in cloud storage. The technique relies on building a hash table with multiple indexes according to the audio file format (uncompressed, lossy compressed, lossless compressed), where a separate index is assigned to each format. The MD6 algorithm, which generates a 512-bit key, is used to reduce the probability of collision.

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