Abstract

Recent research has focused on applying blockchain technology to solve security-related problems in Internet of Things (IoT) networks. However, the inherent scalability issues of blockchain technology become apparent in the presence of a vast number of IoT devices and the substantial data generated by these networks. Therefore, in this paper, we use a lightweight consensus algorithm to cater to these problems. We propose a scalable blockchain-based framework for managing IoT data, catering to a large number of devices. This framework utilizes the Delegated Proof of Stake (DPoS) consensus algorithm to ensure enhanced performance and efficiency in resource-constrained IoT networks. DPoS being a lightweight consensus algorithm leverages a selected number of elected delegates to validate and confirm transactions, thus mitigating the performance and efficiency degradation in the blockchain-based IoT networks. In this paper, we implemented an Interplanetary File System (IPFS) for distributed storage, and Docker to evaluate the network performance in terms of throughput, latency, and resource utilization. We divided our analysis into four parts: Latency, throughput, resource utilization, and file upload time and speed in distributed storage evaluation. Our empirical findings demonstrate that our framework exhibits low latency, measuring less than 0.976 ms. The proposed technique outperforms Proof of Stake (PoS), representing a state-of-the-art consensus technique. We also demonstrate that the proposed approach is useful in IoT applications where low latency or resource efficiency is required.

Details

Title
A scalable blockchain based framework for efficient IoT data management using lightweight consensus
Author
Haque, Ehtisham Ul 1 ; Shah, Adil 1 ; Iqbal, Jawaid 2 ; Ullah, Syed Sajid 3 ; Alroobaea, Roobaea 4 ; Hussain, Saddam 5 

 Department of Computer Science, MY University, Islamabad, Pakistan 
 Faculty of Computing, Riphah International University, Islamabad, Pakistan (GRID:grid.414839.3) (ISNI:0000 0001 1703 6673) 
 University of Agder (UiA), Department of Information and Communication Technology, Grimstad, Norway (GRID:grid.23048.3d) (ISNI:0000 0004 0417 6230) 
 Taif University, Department of Computer Science, College of Computers and Information Technology, Taif, Saudi Arabia (GRID:grid.412895.3) (ISNI:0000 0004 0419 5255) 
 Universiti Brunei Darussalam, School of Digital Science, Gadong, Brunei (GRID:grid.440600.6) (ISNI:0000 0001 2170 1621) 
Pages
7841
Publication year
2024
Publication date
2024
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3031478597
Copyright
© The Author(s) 2024. corrected publication 2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.