| Autor: |
Said, Ghawar, Ullah, Ata, Ghani, Anwar, Azeem, Muhammad, Yahya, Khalid, Bilal, Muhammad, Shah, Sayed Chhattan |
| Předmět: |
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| Zdroj: |
Intelligent Automation & Soft Computing; 2023, Vol. 38 Issue 1, p83-99, 17p |
| Abstrakt: |
The Internet of Things (IoT) and cloud technologies have encouraged massive data storage at central repositories. Software-defined networks (SDN) support the processing of data and restrict the transmission of duplicate values. It is necessary to use a data de-duplication mechanism to reduce communication costs and storage overhead. Existing State of the art schemes suffer fromcomputational overhead due to deterministic or randomtree-based tags generation which further increases as the file size grows. This paper presents an efficient file-level de-duplication scheme (EFDS) where the cost of creating tags is reduced by employing a hash table with key-value pair for each block of the file. Further, an algorithm for hash table-based duplicate block identification and storage (HDBIS) is presented based on fingerprints that maintain a linked list of similar duplicate blocks on the same index.Hash tables normally have a consistent time complexity for lookup, generating, and deleting stored data regardless of the input size. The experiential results show that the proposed EFDS scheme performs better compared to its counterparts. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
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