Dr.M.INBAVALLI

EDUCATION

M.Sc,M.C.A,Ph.D

RESEARCH, TEACHING, or OTHER INTERESTS

Computer Science, Artificial Intelligence, Computer Networks and Communications, Computer Science Applications

Scopus Publications

Optimizing technological transactions using a dual-layer blockchain for enhanced scalability
Th. Kanimozhi, M. Inbavalli
Scientific and Technical Journal of Information Technologies Mechanics and Optics, 2026
In the era of rapidly evolving digital infrastructures, ensuring the scalability and efficiency of technological transactions has become a critical challenge. Traditional blockchain models often suffer from limitations, such as high latency, restricted throughput, and network congestion, particularly under high transaction volumes. This paper proposes a novel dual-layer blockchain architecture designed to address these limitations by segregating transaction processing and consensus mechanisms into two distinct but interoperable layers. The first layer, a lightweight transactional layer, handles real-time data exchange and verification with minimal computational overhead, while the second layer focuses on robust consensus, security, and long-term data immutability. By decoupling these functions, the proposed model significantly improves scalability, reduces latency, and enhances system responsiveness. Experimental simulations demonstrate that the dual-layer approach outperforms conventional single-chain systems in terms of transaction throughput, confirmation time, and scalability under varying loads. This architecture holds promising potential for deployment in sectors requiring high-performance, secure, and decentralized transaction systems, such as finance, supply chain, and smart industry ecosystems.
Power of blockchain technology for enhancing efficiency transparency and data provenance in supply chain management
Kanimozhi Thirunavaukkarasu, Inbavalli Mani
Iaes International Journal of Artificial Intelligence, 2025
Global supply chains face increasing challenges in improving efficiency, transparency, and compliance with regulatory requirements. Traditional supply chain systems often suffer from inefficiencies due to fragmented data and manual processes, which result in delays and higher costs. Blockchain technology has emerged as a potential solution by offering decentralization, data immutability, and automation through smart contracts. However, existing blockchain implementations struggle with issues like scalability and transaction speed, which limits their effectiveness in supply chain management. This study introduces a new framework based on distributed ledger technology (DLT) with enhanced smart contract functions and data provenance tracking. The framework aims to improve transaction throughput, reduce latency, and provide better data integrity, enabling more efficient and transparent supply chain operations. By incorporating mechanisms to track the origin and movement of goods, the framework ensures that stakeholders have real-time access to accurate information, improving decision-making and trust across the supply chain. We evaluate the performance of this framework using the AnyLogic simulation platform, comparing it to traditional blockchain systems. Metrics such as transaction throughput, latency, and efficiency are analyzed to demonstrate the improvements achieved by the proposed system. The results show significant enhancements in transaction speed and operational efficiency, offering a practical solution for optimizing supply chains in various industries.
Enhancing scalability and efficiency in technological transaction utilizing dual-layer blockchain approach
T. Kanimozhi, M. Inbavalli
International Journal of Reconfigurable and Embedded Systems, 2025
The leather industry encounters significant challenges in integrating blockchain technology and smart contracts into its complex supply networks. Despite technological advancements, existing supply chain management systems suffer from inefficiencies, opacity, and vulnerabilities to fraud. Blockchain offers promising solutions such as immutable ledgers, decentralized governance, and smart contract automation. However, scalability limitations hinder the efficient handling of high transaction volumes, impacting procurement, production, inventory management, and distribution processes, leading to delays and increased costs. This research aims to address these challenges by exploring innovative approaches, including dual-layer blockchain architectures incorporating sharding and state channels, tailored to the unique needs of the leather industry. By overcoming scalability barriers, the research seeks to unlock the transformative potential of blockchain technology and smart contracts, enhancing transparency, traceability, and efficiency in leather supply chains while ensuring global interoperability and regulatory compliance. Through empirical validation and comparative analysis, this study provides understandings into the practical implementation of blockchain solutions within the leather industry, offering strategic guidance for sustainable supply chain management practices.
Fuzzy inference model for computation and prediction of disease pattern
Inbavalli M.
Journal of Advanced Research in Dynamical and Control Systems, 2020
An intelligent agent based mining techniques for distributed data mining
Inbavalli M.
Journal of Advanced Research in Dynamical and Control Systems, 2020
Multi Agent Probabilistic Inference Model for Distributed Decisive Support System Based on Fuzzy Rule Sets Using Data Mining
International Journal of Applied Engineering Research, 2014