TY  - EJOU
AU  - Said, Ghawar 
AU  - Ullah, Ata 
AU  - Ghani, Anwar 
AU  - Azeem, Muhammad 
AU  - Yahya, Khalid 
AU  - Bilal, Muhammad 
AU  - Shah, Sayed Chhattan 

TI  - Hash Table Assisted Efficient File Level De-Duplication Scheme in SD-IoV Assisted Sensing Devices
T2  - Intelligent Automation \& Soft Computing

PY  - 2023
VL  - 38
IS  - 1
SN  - 2326-005X

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 tree-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.
KW  - Hash table; de-duplication; linked list; IoT; sensing devices

DO  - 10.32604/iasc.2023.036079