An Intelligent and Scalable Edge-Based Sea Food Supply Chain Management Harnessing Block Chain Technology

Abstract

Recent technologies report promising potential improvements across the Supply Chain Management(SCM) industry. These advancements have acquired growing attention among communities like logistics, manufacturing, packaging and transportation. Traditional systems are equipped with centralized server for managing all the functionalities which includes raw material exchange, order placing, buyer-seller interactions, order updates and changes. Hence, the supply chain network may be vulnerable to risky factors where every action has to be routed to the centralized server hosted on the website. The use of block chain offers the decentralized transaction processing without relying on the central controller unit. In this context, block chain technologyform the key enabler of the supply chain ecosystem and brings several advancements in present systems. Furthermore, several challenges like scalability, data integrity, security and availability still need addressing. The efficient use of edge computing and priority data access enhances the performance of the resource constrained supply chain network. The main objective of the proposed system is manifold. First, to achieve scalability, we perform an efficient priority setting using Intelligent K-Means(IKM) clustering across the edge nodes to classify each data’s priority level. This classifier is used as the method to check whether the edge node has received prioritized data or low-prioritized data. If the low prioritized data received, it stores in the log files for future data analysis. Second, the prioritized data is processed in the public block chain by performing  HighPriority Access based Smart Contract (HPASC)  to enable secured data transfer excluding the third parties. Based on the proposed model, a prototype is developed and that was further evaluated with two existing block chain systems. The results shows that the model outperforms the existing systems in terms of scalability, response time, throughput and accuracy.