Abstract
Blockchain technology has revolutionized the ways of processing and storing data in terms of reliability and security. Blockchain plays a pivotal role in transferring the processing hurdle from the client–server to a decentralized and secured platform. Blockchain is deemed to be an efficient technology in a forthcoming era that would beneficiate multifarious industries. An issue that becomes a bottleneck for blockchain-based applications is their restricted ability to process in comparison to distributed database systems. In this paper, we present intelligent traffic control using a hybrid model based on the PSO-based optimization algorithm and fuzzy logic in order to improve blockchain performance. The real-time network feedback model is designed and used as an input to control the transaction traffic across the entire network in a robust way without human intervention. In order to evaluate the effectiveness of the designed model, a clinical trial service framework as a test network is implemented on top of Hyperledger Fabric. The case study is further compared with baseline network, network with fuzzy approach, and network with optimized parameter. The experiments show that the proposed model not only enhanced the network by maximizing the network throughput and minimizing the network latency. A smart contract is implemented to automate the transaction flow as per real-time data of network conditions. An open-source blockchain framework, Hyperledger Fabric, is harnessed for implementation of the experiment environment in order to signify the potential of the proposed model. The outcome of this study indicated a remarkable increase in transaction throughput (i.e., 38.5%) and a decrease in transaction latency of 40.5%. Moreover, the proposed model can easily be integrated with other existing blockchain-based performance-enhancing tools.
Original language | English |
---|---|
Article number | 108327 |
Number of pages | 15 |
Journal | Computers and Industrial Engineering |
Volume | 170 |
Early online date | 1 Jul 2022 |
DOIs | |
Publication status | Published - 1 Aug 2022 |
Externally published | Yes |