An Efficient IoT-Blockchain Sharding Technique using Frequently Transacting Sender and Receiver Information

Distributed systems have become an integral part of many modern applications, processing large amounts of data and serving large numbers of users simultaneously. However, as these systems grow in size and complexity, it becomes increasingly difficult to ensure optimal performance and scalability. This scenario is more common for Internet of Things (IoT) applications. In this research, the problem of limited scalability of IoT frameworks is addressed by proposing a blockchain-integrated new sharding algorithm. The algorithm is based on analyzing transaction records of frequently traded sender-receiver pairs. Our goal is to improve the overall performance of the system and improve its ability to handle higher volumes of transactions. By analyzing a real dataset, we observed a significant reduction in overall execution time by about 10%, demonstrating the effectiveness of our proposed sharding algorithm. Additionally, we found that the algorithm continued to improve the transaction per second rate (TPS) as the number of tasks processed increased. These results highlight the potential of our proposed method for optimizing the efficiency and scalability of distributed systems. Further investigation and analysis across different datasets and system configurations are recommended to validate the generalizability and effectiveness of our approach.