Blockchain is a decentralized digital database that records transactions across a large number of computers. Block chain could be used in a variety of industries, including finance, medicine, real estate, transport, agriculture, and supply chain management. Because blockchain enables dispersed peer-to-peer connections, it ensures safety and confidentiality. Big data offers new prospects, increased value, and operational efficiencies in traditional supply chain strategies, according to this research. Hence, this paper presents a novel framework for blockchain-based Supply system with an aim to improve the scalability with secured data storage. Initially, the data set is preprocessed using normalization method and feature extraction is done by Principal Component Analysis. To improve the storage’s security and node’s scheduling, the proposed Precedence Partition Scheduling Algorithm is employed. We also introduce Enhanced Particle Swarm Optimization Algorithm to improve the scalability of the network. To check the nodes, we employ Delegated Proof of Stake consensus protocol. In blockchain, to change the input entity to an output entity with defined length, the message digest-5 hash approach is employed. The proposed method is analyzed in terms of performance metrics like execution time, energy consumption, CPU usage, response time, security, throughput and efficiency, and is related with the current methodologies. The presented approach was established to be scalable for supply system when compared to the conventional approaches.

Blockchain technology, supply system ,scalability, Principal Component Analysis, Precedence Partition Scheduling Algorithm, Enhanced Particle Swarm Optimization Algorithm, Message Digest-5 Hash, Delegated Proof of Stake consensus protocol