Home > Research > Publications & Outputs > Hash Table Assisted Efficient File Level De-dup...

Research

Links

Text available via DOI:

Keywords

View graph of relations

Hash Table Assisted Efficient File Level De-duplication Scheme in SD-IoV Assisted Sensing Devices

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Published

Standard

Hash Table Assisted Efficient File Level De-duplication Scheme in SD-IoV Assisted Sensing Devices. / Said, Ghawar; Ullah, Ata; Ghani, Anwar et al.
In: Intelligent Automation Soft Computing, Vol. 38, No. 1, 26.01.2024, p. 83-99.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Said, G, Ullah, A, Ghani, A, Azeem, M, Yahya, K, Bilal, M & Shah, SC 2024, 'Hash Table Assisted Efficient File Level De-duplication Scheme in SD-IoV Assisted Sensing Devices', Intelligent Automation Soft Computing, vol. 38, no. 1, pp. 83-99. https://doi.org/10.32604/iasc.2023.036079

APA

Said, G., Ullah, A., Ghani, A., Azeem, M., Yahya, K., Bilal, M., & Shah, S. C. (2024). Hash Table Assisted Efficient File Level De-duplication Scheme in SD-IoV Assisted Sensing Devices. Intelligent Automation Soft Computing, 38(1), 83-99. https://doi.org/10.32604/iasc.2023.036079

Vancouver

Said G, Ullah A, Ghani A, Azeem M, Yahya K, Bilal M et al. Hash Table Assisted Efficient File Level De-duplication Scheme in SD-IoV Assisted Sensing Devices. Intelligent Automation Soft Computing. 2024 Jan 26;38(1):83-99. Epub 2023 Jun 27. doi: 10.32604/iasc.2023.036079

Author

Said, Ghawar ; Ullah, Ata ; Ghani, Anwar et al. / Hash Table Assisted Efficient File Level De-duplication Scheme in SD-IoV Assisted Sensing Devices. In: Intelligent Automation Soft Computing. 2024 ; Vol. 38, No. 1. pp. 83-99.

Bibtex

@article{e0fec99c226741f1be34ffa6d86e91dd,
title = "Hash Table Assisted Efficient File Level De-duplication Scheme in SD-IoV Assisted Sensing Devices",
abstract = "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 from computational overhead due to deterministic or random treebased 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 keyvalue pair for each block of the file. Further, an algorithm for hash tablebased 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.",
keywords = "Hash table, de-duplication, linked list, IoT, sensing devices",
author = "Ghawar Said and Ata Ullah and Anwar Ghani and Muhammad Azeem and Khalid Yahya and Muhammad Bilal and Shah, {Sayed Chhattan}",
year = "2024",
month = jan,
day = "26",
doi = "10.32604/iasc.2023.036079",
language = "English",
volume = "38",
pages = "83--99",
journal = "Intelligent Automation Soft Computing",
publisher = "Tech Science Press",
number = "1",

}

RIS

TY - JOUR

T1 - Hash Table Assisted Efficient File Level De-duplication Scheme in SD-IoV Assisted Sensing Devices

AU - Said, Ghawar

AU - Ullah, Ata

AU - Ghani, Anwar

AU - Azeem, Muhammad

AU - Yahya, Khalid

AU - Bilal, Muhammad

AU - Shah, Sayed Chhattan

PY - 2024/1/26

Y1 - 2024/1/26

N2 - 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 from computational overhead due to deterministic or random treebased 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 keyvalue pair for each block of the file. Further, an algorithm for hash tablebased 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.

AB - 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 from computational overhead due to deterministic or random treebased 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 keyvalue pair for each block of the file. Further, an algorithm for hash tablebased 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.

KW - Hash table

KW - de-duplication

KW - linked list

KW - IoT

KW - sensing devices

U2 - 10.32604/iasc.2023.036079

DO - 10.32604/iasc.2023.036079

M3 - Journal article

VL - 38

SP - 83

EP - 99

JO - Intelligent Automation Soft Computing

JF - Intelligent Automation Soft Computing

IS - 1

ER -