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Integrating K-Means Clustering with PoA Blockchain and IPFS for Clustered Data Synchronization: The OriBloX CDSF Approach

by Edy Saputro, Mustafid, Jatmiko Endro Suseno
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 186 - Number 71
Year of Publication: 2025
Authors: Edy Saputro, Mustafid, Jatmiko Endro Suseno
10.5120/ijca2025924561

Edy Saputro, Mustafid, Jatmiko Endro Suseno . Integrating K-Means Clustering with PoA Blockchain and IPFS for Clustered Data Synchronization: The OriBloX CDSF Approach. International Journal of Computer Applications. 186, 71 ( Mar 2025), 11-18. DOI=10.5120/ijca2025924561

@article{ 10.5120/ijca2025924561,
author = { Edy Saputro, Mustafid, Jatmiko Endro Suseno },
title = { Integrating K-Means Clustering with PoA Blockchain and IPFS for Clustered Data Synchronization: The OriBloX CDSF Approach },
journal = { International Journal of Computer Applications },
issue_date = { Mar 2025 },
volume = { 186 },
number = { 71 },
month = { Mar },
year = { 2025 },
issn = { 0975-8887 },
pages = { 11-18 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume186/number71/integrating-k-means-clustering-with-poa-blockchain-and-ipfs-for-clustered-data-synchronization-the-oriblox-cdsf-approach/ },
doi = { 10.5120/ijca2025924561 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2025-03-06T21:09:24.893501+05:30
%A Edy Saputro
%A Mustafid
%A Jatmiko Endro Suseno
%T Integrating K-Means Clustering with PoA Blockchain and IPFS for Clustered Data Synchronization: The OriBloX CDSF Approach
%J International Journal of Computer Applications
%@ 0975-8887
%V 186
%N 71
%P 11-18
%D 2025
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Efficient data synchronization in distributed systems presents significant challenges, as centralized solutions often face limitations in scalability, bandwidth efficiency, and resilience to single points of failure. Existing blockchain and decentralized storage technologies struggle to manage frequent data updates effectively. To address these issues, OriBloX CDSF integrates K-Means clustering (optimized with the Elbow method), TF-IDF analysis, Hyperledger Besu (using QBFT PoA consensus), and IPFS to deliver a secure, scalable, and decentralized synchronization framework. Its selective synchronization mechanism optimizes bandwidth usage by retrieving only updated cluster files, reducing unnecessary data transfers by up to 70%. Using the Amazon product catalog dataset, the framework demonstrated robust clustering performance, with the Elbow method consistently identifying optimal clusters and silhouette scores reaching up to 0.114, reflecting well-separated and meaningful groupings. OriBloX’s design ensures efficient metadata synchronization, scalability, and fault tolerance, making it a reliable solution for distributed ecosystems.

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Index Terms

Computer Science
Information Sciences
Security
Algorithms
Data Synchronization
Distributed Systems
Blockchain Technology
Cloud Computing
Fault Tolerance
Decentralization

Keywords

K-Means Clustering TF-IDF Elbow Method Blockchain Proof of Authority QBFT Hyperledger Besu IPFS Data Synchronization Distributed Systems Decentralization Fault Tolerance Smart Contracts.

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