Robust Hybrid Data Deduplication Algorithm through Fog Computing
M. A. SayedElahl, Abdelrahman M. Ahmed · International Journal of Computing Science and Mathematics · 2024
Cloud computing often encounters issues with uptime and connectivity, especially in regions with poor infrastructure. This work presents a solution through the robust hybrid data deduplication algorithm (RHDA) integrated with fog computing. RHDA enhances data management by eliminating redundancy and ensuring integrity via Rabine fingerprinting. Compression and encryption further reduce data volume and protect sensitive information during transmission over potentially insecure WANs. Fog computing plays a crucial role by enabling initial data processing near the source, thereby minimising latency and server load in unstable WAN environments. The method improves data transfer efficiency by converting data into lightweight metadata, which is then decompressed and reconstructed upon arrival. This approach not only reduces the data volume transferred over unreliable WANs but also significantly boosts data transfer speeds and stability. Consequently, RHDA combined with fog computing provides a robust and scalable solution for improving cloud service performance, particularly in next-generation smart applications.