Enhancing IoT blockchain scalability through the eepos consensus algorithm
Downloads
Published
DOI:
https://doi.org/10.58414/SCIENTIFICTEMPER.2025.16.2.02Keywords:
Blockchain, Consensus Algorithm, EePoS, Energy Efficiency, IoT, Proof of Stake.Dimensions Badge
Issue
Section
License
Copyright (c) 2025 The Scientific Temper

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
The integration of blockchain technology with the Internet of Things (IoT) introduces significant scalability, energy efficiency, and security challenges, particularly when using traditional consensus mechanisms like Proof of Work (PoW). IoT networks generate vast amounts of data while operating under resource constraints, necessitating the development of consensus algorithms that balance energy efficiency, transaction throughput, and security. Addressing these challenges is critical for the sustainable adoption of blockchain in IoT ecosystems. This research aims to enhance blockchain scalability and performance in IoT environments through the development of the Enhanced Efficient Proof of Stake (EePoS) consensus algorithm. The objective is to provide a framework that optimizes validator selection, minimizes energy consumption, and ensures robust security against common blockchain threats. The proposed method employs a multi-layered architecture, selective validation, and a behavior-aware penalty-reward system to ensure efficient consensus. Key security metrics, including Probability of Successful Attack (PSA) and Forking Rate (FR), were evaluated to demonstrate the algorithm’s resilience. EePoS reduces PSA by dynamically adjusting validator selection based on stake, behavior, and transaction load while decreasing FR through cluster-based voting and hierarchical aggregation. Experimental results demonstrated 20% lower PSA, 30% reduced FR, and 8% faster consensus time compared to ePoS. Throughput improved to 296 TPS while reducing CPU and memory utilization, ensuring robust performance for resource-constrained IoT networks. The novelty of this work lies in the tailored enhancements to the PoS framework, specifically designed for IoT constraints, making EePoS a scalable, energy-efficient, and secure solution for IoT blockchain integration.Abstract
How to Cite
Downloads
Similar Articles
- A. Jabeen, A. R. M. Shanavas, Hazard regressive multipoint elitist spiral search optimization for resource efficient task scheduling in cloud computing , The Scientific Temper: Vol. 15 No. 02 (2024): The Scientific Temper
- Susithra N, Rajalakshmi K, Ashwath P, Performance analysis of compressive sensing and reconstruction by LASSO and OMP for audio signal processing applications , The Scientific Temper: Vol. 14 No. 01 (2023): The Scientific Temper
- R. Sakthiraman, L. Arockiam, RFSVMDD: Ensemble of multi-dimension random forest and custom-made support vector machine for detecting RPL DDoS attacks in an IoT-based WSN environment , The Scientific Temper: Vol. 16 No. 03 (2025): The Scientific Temper
- K. Gokulkannan, M. Parthiban, Jayanthi S, Manoj Kumar T, Cost effective cloud-based data storage scheme with enhanced privacy preserving principles , The Scientific Temper: Vol. 15 No. 02 (2024): The Scientific Temper
- V. Parimala, D. Ganeshkumar, Solar energy-driven water distillation with nanoparticle integration for enhanced efficiency, sustainability, and potable water production in arid regions , The Scientific Temper: Vol. 15 No. 01 (2024): The Scientific Temper
- Manikannan Palanivel, Alaudeen A, Pandiyan K. S, Sivaprakasam P, Hybrid fuzzy and fire fly algorithm-based MPPT controller for PV system using super lift boost converter , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
- Chandrasekaran M, Rajesh P K, Optimization of cost to customer of power train in commercial vehicle using knapsack dynamic programming influenced by vehicle IoT data , The Scientific Temper: Vol. 14 No. 02 (2023): The Scientific Temper
- K. Akila, Location-specific trusted third-party authentication model for environment monitoring using internet of things and an enhancement of quality of service , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
- K Sreenivasulu, Sameer Yadav, G Pushpalatha, R Sethumadhavan, Anup Ingle, Romala Vijaya, Investigating environmental sustainability applications using advanced monitoring systems , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
- M. Menaha, J. Lavanya, Crop yield prediction in diverse environmental conditions using ensemble learning , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
<< < 1 2 3 4 5 6 7 8 9 10 > >>
You may also start an advanced similarity search for this article.

