A Comprehensive Survey of Dynamic Hashing Techniques in Network Data Processing

Abstract

Dynamic hashing techniques have become pivotal in managing and processing large-scale network data, where scalability, efficiency, and adaptability are paramount. This survey provides an extensive overview of dynamic hashing methodologies, emphasizing their applications within various network architectures and protocols. We explore the evolution of hashing algorithms, analyze their performance in real-time data processing scenarios, and examine their integration with modern network technologies such as software-defined networking (SDN) and distributed systems. Additionally, we discuss the challenges and future directions in optimizing dynamic hashing for enhanced data throughput, security, and fault tolerance in network environments. This study serves as a valuable resource for researchers and practitioners aiming to leverage dynamic hashing for efficient network data management.