TITLE:
Blockchain for Smart Homes: Blockchain Low Latency
AUTHORS:
Reem Jamaan Alzahrani, Fatimah Saad Alzahrani
KEYWORDS:
Internet of Things (IoT), Blockchain Latency, Hyperledger Fabric, Smart Homes, Latency Optimization, Data Security
JOURNAL NAME:
Journal of Computer and Communications,
Vol.12 No.12,
December
3,
2024
ABSTRACT: The inclusion of blockchain in smart homes increases data security and accuracy within home ecosystems but presents latency issues that hinder real-time interactions. This study addresses the important challenge of blockchain latency in smart homes through the development and application of the Blockchain Low Latency (BLL) model using Hyperledger Fabric v2.2. With respect to latency, the BLL model proposes the optimization of the following fundamental blockchain parameters: transmission rate, endorsement policy, batch size, and batch timeout. After conducting hypothesis testing on system parameters, we found that transactions per second (tps) of 30, OutOf (2) endorsement policy, in which any two of five peers endorse a batch size of 10 and batch timeout of 1 s, considerably decrease latency. The BLL model achieved an average latency of 0.39 s, approximately 30 times faster than Ethereum’s average latency of 12 s, thereby enhancing the efficiency of blockchain-based smart home applications. The results of this study demonstrate that despite introducing certain latency issues, proper selection of parameters in blockchain configurations can eliminate these latency problems, making blockchain technology more viable for real-time Internet of Things (IoT) applications such as smart homes. Future work involves applying the proposed model to a larger overlay and deploying it in real-world smart home environments using sensor devices, enhancing the given configuration to accommodate a large number of transactions, and adjusting the overlay in line with the complexity of the network. Therefore, this study provides practical recommendations for solving the latency issue in blockchain systems, relates theoretical advancements to real-life applications in IoT environments, and stresses the significance of parameter optimization for maximum effectiveness.