An Efficient Lightweight Blockchain for Decentralized IoT
- URL: http://arxiv.org/abs/2508.19219v1
- Date: Tue, 26 Aug 2025 17:36:45 GMT
- Title: An Efficient Lightweight Blockchain for Decentralized IoT
- Authors: Faezeh Dehghan Tarzjani, Mostafa Salehi,
- Abstract summary: The Internet of Things (IoT) is applied in various fields, and the number of physical devices connected to the IoT is increasingly growing.<n>There are significant challenges to the IoT's growth and development, mainly due to the centralized nature and large-scale IoT networks.<n>A promising decentralized platform for IoT is blockchain.
- Score: 0.19336815376402716
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: The Internet of Things (IoT) is applied in various fields, and the number of physical devices connected to the IoT is increasingly growing. There are significant challenges to the IoT's growth and development, mainly due to the centralized nature and large-scale IoT networks. The emphasis on the decentralization of IoT's architecture can overcome challenges to IoT's capabilities. A promising decentralized platform for IoT is blockchain. Owing to IoT devices' limited resources, traditional consensus algorithms such as PoW and PoS in the blockchain are computationally expensive. Therefore, the PoA consensus algorithm is proposed in the blockchain consensus network for IoT. The PoA selects the validator as Turn-based selection (TBS) that needs optimization and faces system reliability, energy consumption, latency, and low scalability. We propose an efficient, lightweight blockchain for decentralizing IoT architecture by using virtualization and clustering to increase productivity and scalability to address these issues. We also introduce a novel PoA based on the Weight-Based-Selection (WBS) method for validators to validate transactions and add them to the blockchain. By simulation, we evaluated the performance of our proposed WBS method as opposed to TBS. The results show reduced energy consumption, and response time, and increased throughput.
Related papers
- Efficient Byzantine Consensus MechanismBased on Reputation in IoT Blockchain [22.73971353086496]
This paper proposes the Efficient Byzantine Reputation-based Consensus (EBRC) mechanism to resolve the issues raised above.<n>Our experiments show that the EBRC algorithm has lower consensus delay, higher throughput, improved security, and lower verification costs.
arXiv Detail & Related papers (2025-08-03T17:13:29Z) - A Distributed Blockchain-based Access Control for the Internet of Things [0.0]
Internet of Things (IoT) environment has become increasingly fertile for malicious users to break the security and privacy of IoT users.<n>To address the distributed IoT environment, blockchain is viewed as a promising data management technology.<n>We propose a decentralised access control and attribute-based access control model for IoT entitled (DBC-ABAC)<n>A proof-of-concept implementation is presented using Hyperledger Fabric.
arXiv Detail & Related papers (2025-03-22T22:36:02Z) - A Fair and Lightweight Consensus Algorithm for IoT [0.0]
This work introduces a fair and lightweight hybrid consensus algorithm tailored for IoT.<n>The proposed approach minimizes resource demands on the nodes while ensuring a secure and fair agreement process.<n>In addition, a reputation-based block voting mechanism is incorporated to enhance trust and establish finality.
arXiv Detail & Related papers (2025-03-11T16:45:51Z) - Digital Twin-Assisted Federated Learning with Blockchain in Multi-tier Computing Systems [67.14406100332671]
In Industry 4.0 systems, resource-constrained edge devices engage in frequent data interactions.
This paper proposes a digital twin (DT) and federated digital twin (FL) scheme.
The efficacy of our proposed cooperative interference-based FL process has been verified through numerical analysis.
arXiv Detail & Related papers (2024-11-04T17:48:02Z) - Blockchains for Internet of Things: Fundamentals, Applications, and Challenges [38.29453164670072]
Not every blockchain system is suitable for specific IoT applications.
Public blockchains are not suitable for storing sensitive data.
We explore the blockchain's application in three pivotal IoT areas: edge AI, communications, and healthcare.
arXiv Detail & Related papers (2024-05-08T04:25:57Z) - Enhancing Trust and Privacy in Distributed Networks: A Comprehensive Survey on Blockchain-based Federated Learning [51.13534069758711]
Decentralized approaches like blockchain offer a compelling solution by implementing a consensus mechanism among multiple entities.
Federated Learning (FL) enables participants to collaboratively train models while safeguarding data privacy.
This paper investigates the synergy between blockchain's security features and FL's privacy-preserving model training capabilities.
arXiv Detail & Related papers (2024-03-28T07:08:26Z) - Graph Attention Network-based Block Propagation with Optimal AoI and Reputation in Web 3.0 [59.94605620983965]
We design a Graph Attention Network (GAT)-based reliable block propagation optimization framework for blockchain-enabled Web 3.0.
To achieve the reliability of block propagation, we introduce a reputation mechanism based on the subjective logic model.
Considering that the GAT possesses the excellent ability to process graph-structured data, we utilize the GAT with reinforcement learning to obtain the optimal block propagation trajectory.
arXiv Detail & Related papers (2024-03-20T01:58:38Z) - Generative AI-enabled Blockchain Networks: Fundamentals, Applications,
and Case Study [73.87110604150315]
Generative Artificial Intelligence (GAI) has emerged as a promising solution to address challenges of blockchain technology.
In this paper, we first introduce GAI techniques, outline their applications, and discuss existing solutions for integrating GAI into blockchains.
arXiv Detail & Related papers (2024-01-28T10:46:17Z) - A Blockchain Solution for Collaborative Machine Learning over IoT [2.4739484546803334]
Federated learning (FL) and blockchain technologies have emerged as promising approaches to address these challenges.<n>We present a novel IoT solution that combines the incremental learning vector quantization algorithm (XuILVQ) with blockchain technology.<n>Our proposed architecture addresses the shortcomings of existing blockchain-based FL solutions by reducing computational and communication overheads while maintaining data privacy and security.
arXiv Detail & Related papers (2023-11-23T18:06:05Z) - Optimizing Resource-Efficiency for Federated Edge Intelligence in IoT
Networks [96.24723959137218]
We study an edge intelligence-based IoT network in which a set of edge servers learn a shared model using federated learning (FL)
We propose a novel framework, called federated edge intelligence (FEI), that allows edge servers to evaluate the required number of data samples according to the energy cost of the IoT network.
We prove that our proposed algorithm does not cause any data leakage nor disclose any topological information of the IoT network.
arXiv Detail & Related papers (2020-11-25T12:51:59Z) - Resource Management for Blockchain-enabled Federated Learning: A Deep
Reinforcement Learning Approach [54.29213445674221]
Federated Learning (BFL) enables mobile devices to collaboratively train neural network models required by a Machine Learning Model Owner (MLMO)
The issue of BFL is that the mobile devices have energy and CPU constraints that may reduce the system lifetime and training efficiency.
We propose to use the Deep Reinforcement Learning (DRL) to derive the optimal decisions for theO.
arXiv Detail & Related papers (2020-04-08T16:29:19Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.