Scaling A Blockchain-Based System Via Optimized Load Balancing Among Shards

Abstract

Blockchain technology, despite its transformative potential, often encounters scalabil-ity challenges that hinder its widespread adoption. This research proposes an innovative approach to improve Blockchain scalability through optimized load balancing by distributing nodes within shards, leveraging different distribution of M/M/k model. To ensure balanced processing, incoming and outgoing queries are handled with distinct distribution methods, reducing idle time and enhancing network traffic management. To validate our approach, we conducted comprehensive performance comparisons with traditional top load balancing techniques, including Round-Robin (RR), Least Connection (LC) and their variants. The results demonstrate that the proposed method significantly outperformed these conventional techniques in terms of load distribution efficiency, response time, and overall system scalability. This study provides a compelling case to adopt our optimized load balancing strategy in Blockchain systems, paving the way for more scalable and robust Blockchain applications.