VENNILA Chockalingam
@saranathan.ac.in
Scopus Publications
- A secure and scalable blockchain-assisted authentication framework for decentralized IoT data management
G. Iswarya, C. Vennila
Scientific Reports, 2026
Over the past few years, IoT devices have witnessed an unprecedented growth rate, disrupting most industries, such as healthcare, home automation, transport, and manufacturing. Despite this, the growth has also opened the IoT networks to high vulnerability to security risks, including data breaches, unauthorized access, and distributed denial-of-service (DDoS) attacks, because of their centralized structure and insufficient computing resources. The main issue is that there is no strong, scalable, and decentralized security structure that could guarantee data integrity, authenticate, and establish trust between the heterogeneous IoT-based devices. This paper will overcome these shortcomings by outlining a blockchain-based secure IoT system named BASIS (Blockchain-Assisted Secure IoT System) in this paper. The model incorporates a lightweight Proof of Authentication (PoA) consensus mechanism, cryptographic data protection, and smart contract-based access control to facilitate decentralized authentication and tamper-resistant data management. In the suggested architecture, PoA is used to validate transactions and cryptographic identities are used to register IoT nodes to minimize computational and energy overheads. Smart contracts are used to implement access control policies and are not based on centralized authorities. A pre-processing attention-based learning modules are also introduced in the system to cater to anomaly finding and adaptive trust-assessment. The experimental outcome shows that BASIS improves the network resilience, minimizes the data validation latency and has a better throughput than the conventional IoT security schemes. In addition, the strategy reduces energy consumption and computational overhead, using optimized consensus protocols, and can be used in resource-constrained IoT settings. To sum up, the offered blockchain framework is a good way to enhance the security of IoT networks with the sources of decentralized trust, data immutability, and scalability, which leads to the future of secure IoT ecosystems. The proposed BASIS approach had better performance: 95 TPS throughput, 200 ms latency, 95 J energy use, 99.5% data integrity, 78% scalability efficiency, and 210 ms validation speed. - Lemur Optimized Efficient Spreading Factor Allocation of LoRa Networks for IoT Deployments
J. SathiaParkavi, C. Vennila
International Journal of Computational Intelligence Systems, 2025
LoRa communication has become a cornerstone for Internet of Things (IoT) applications due to its long-range, low-power capabilities which are ideal for remote and rural deployments such as agricultural monitoring. LoRa faces significant challenges, such as network congestion, high latency, and inefficient resource allocation that hinder its scalability and real-time data transmission capabilities. To overcome these issues, a novel enhanced LORA model using lemuR optimization for AllocatIng of SprEading factor (LORA-RAISE) approach has been proposed to enhance communication speed in LoRa. The Lemur Optimization Algorithm (LOA) is employed to optimize spreading factor allocation which improves communication performance, reduces latency, and conserves energy using parameters, such as frequency band, device power, and bandwidth to ensure robust communication. The data are processed through an Ethernet-based system, providing visual insights that facilitate informed decision-making in agriculture. The efficacy of the LORA-RAISE framework is assessed using metrics, such as delay, packet delivery ratio (PDR), throughput, and Energy Consumption (EC). The LORA-RAISE method improves communication performance and decreases latency using the LOA technique. The LORA-RAISE method achieves a throughput of 8.1%, 10.5%, and 4.6% than existing systems, such as the ADR-OWA, LORA-RSSI, and LR-RL, respectively. - Myocardial Infarction Detection using Variational Mode Decomposition with Fuzzy Weight Particle Swarm Optimization and Depthwise Separable Convolutional Network
P. Saranya, C. Vennila
Computers in Biology and Medicine, 2025 - Comprehensive Analysis of Cluster Head Selection in Heterogeneous Wireless Sensor Networks
Karuppaiah C, Vennila C
Proceedings of 5th International Conference on Ubiquitous Computing and Intelligent Information Systems Icuis 2025, 2025
This study examines cluster-based routing procedures that enhance energy-efficiency and scalability in Heterogeneous Wireless Sensor Networks (HWSNs), consisting of nodes that differ in energy, range, and processing capabilities. Details are provided to classify methods for Cluster Head (CH) assignment into heuristic, metaheuristic, fuzzy logic, machine learning, bio-inspired approaches, and hybrid between these protocols. Each category is assessed with respect to its energy efficiency, stability, scalable, and support for heterogeneity. The comparative evaluation indicates that hybrid methods, especially those including Genetic Algorithms and fuzzy logic, outperform existing protocols such as LEACH and HEED. The review positions offerings for ongoing areas of research including trust modelling, node movement, and multi-objective optimization. Simulation evaluation is conducted with graphical and tabulated results that validate newly proposed methods of CH selection. This paper provides a transparent framework for evaluation and direction for future research, including, but not limited to deep learning-based clustering, secure the election of CH in IoT based WSN, and energy-harvesting features. - Investigation of Crystalline Electron Conductors
V. Koushick, J. Eindhumathy, C. Divya, C. Vennila
Introduction to Functional Nanomaterials, 2024
Crystalline materials are those that have a crystal structure. A crystal structure is made up of highly organised and symmetrical chemical linkages that influence the material’s overall form and qualities. The unit cell, which is the little section of the structure that holds all of its geometric features, is a fundamental component of a crystal structure. In nature, the mineral halite, for example, will form isometric (cube-shaped) crystal crystalline formations under optimal circumstances. At the microscopic level, the sodium chloride ions form an isometric pattern that repeats at its most basic unit, the unit cell. This pattern is repeated to form a lattice shape, which eventually forms the material. A crystal does not normally carry electricity. However, when the crystal strontium titanate is heated in the appropriate conductions, it changes and becomes conductive to light. The effect, known as ‘persistent photoconductivity,’ occurs at ambient temperature as well. In general, crystals are excellent thermal conductors. In theory, their atomic structure is incredibly organised, allowing atomic vibrations (i.e., heat) to flow through them like a wave. Glasses, on the other hand, are poor heat conductors. In all conditions, the intermolecular forces that hold the debris together are significantly less than ionic or covalent connections. As a result, molecular crystals have much lower melting and boiling points. Because they lack ions or free electrons, molecular crystals are poor electrical conductors. - Retraction Note to: A novel patch selection technique in ANN B-Spline Bayesian hyperprior interpolation VLSI architecture using fuzzy logic for highspeed satellite image processing (Journal of Ambient Intelligence and Humanized Computing, (2021), 12, 6, (6491-6504), 10.1007/s12652-020-02264-9)
K. Chitra, C. Vennila
Journal of Ambient Intelligence and Humanized Computing, 2023 - Diagnosis of COVID-19 from the X-Ray images using BAT Algorithm with Deep Convolutional Neural Network
K. Mohanappriya, C. Vennila, J. SathiaParkavi, E. Shapnarani
2023 3rd International Conference on Advances in Electrical Computing Communication and Sustainable Technologies Icaect 2023, 2023
The COVID-19 widespread has posed a chief contest to the scientific community around the world. For patients with COVID-19 illness, the international community is working to uncover, implement, or invent new approaches for diagnosis and action. A opposite transcription-polymerase chain reaction is currently a reliable tactic for diagnosing infected people. This is a time- and money-consuming procedure. Consequently, the development of new methods is critical. Using X-ray images of the lungs, this research article developed three stages for detecting and diagnosing COVID-19 patients. The median filtering is used to remove the unwanted noised during pre-processing stage. Then, Otsu thresholding technique is used for segmenting the affected regions, where Spider Monkey Optimization (SMO) is used to select the optimal threshold. Finally, the optimized Deep Convolutional Neural Network (DCNN) is used for final classification. The benchmark COVID dataset and balanced COVIDcxr dataset are used to test projected model's performance in this study. Classification of the results shows that the optimized DCNN architecture outperforms the other pre-trained techniques with an accuracy of 95.69% and a specificity of 96.24% and sensitivity of 94.76%. To identify infected lung tissue in images, here SMO-Otsu thresholding technique is used during the segmentation stage and achieved 95.60% of sensitivity and 95.8% of specificity. - An Efficient Route Optimization Using Ticket-ID Based Routing Management System (T-ID BRM)
S. Venkatasubramanian, A. Suhasini, C. Vennila
Wireless Personal Communications, 2022 - Cluster Head Selection and Optimal Multipath detection using Coral Reef Optimization in MANET Environment
S. Venkatasubramanian, , A. Suhasini, C. Vennila
International Journal of Computer Network and Information Security, 2022
Mobile Ad-hoc Network (MANET) data transfer between nodes in a multi-hop way offers a wide variety of applications. The dynamic feature of ad hoc network mobile nodes is primarily influenced by safety issues, which limit data forwarding rate in multipath routing. As a supplementary method to improve safe data delivery in a MANET, this paper propose and analyse the cluster head (CH) selection and optimum multipath scheme. The CHs are chosen based on the possibility values of each node in MANET, which are considered from the residual energy of each node. During the present phase, the total remaining node energy is used to calculate the mean energy of the entire network. The most likely nodes are picked as the CH, which gathers packets from the cluster members through multi-hop communication. The fundamental idea is to partition a top-secret communication into several shares and then forward the shares via numerous routes to the destination. The Coral Reef Optimization method is used in this work to perform optimum multipath routing. The thorough simulation findings validate the feasibility and efficacy of the suggested strategy in comparison to Butterfly optimization algorithm (BA), Whale Optimization algorithm (WOA) and BAT algorithm techniques. - Performance Improvement of SIMD Processor for High-Speed end Devices in IoT Operation Based on Reversible Logic with Hybrid Adder Configuration
Vinoth Kumar Kalimuthu, Karthikeyan Somasundaram, Bhavani Sridharan
Tehnicki Vjesnik, 2022
: The reversible logic function is gaining significant consideration as a style for the logic design by implementing modern Nano and quantum computing with minimal impact on physical entropy. Recent advances in reversible logic allow for computer design applications using advanced quantum computer algorithms. In the literature, significant contributions have been made towards reversible logic gate structures and arithmetic units. However, there are many attempts to dictate the design of Single Instruction-Multiple Data (SIMD) processors. In this research work, a novel programmable reversible logic gate design is verified and a reversible processor design suggests its implementation of SIMD processor. Then, implementing the ripple-carry, carry-select and Kogge-Stone carry look-ahead adders using reversible logic and the performance is compared. The proposed reversible logic-based architecture has a minimum fan out with binary tree structure and minimum logic depth. The simulation result of the proposed design is obtained from Xilinx 14.5 software. From the simulated result, the computational path net delay for 16 × 16 reversible logic with Kogge Stone Adder is 17.247 ns. Compared with 16-bit Kogge Stone Adder, the reversible logic-based 16-bit Kogge Stone Adder gives low power and low time delay. By looking at the speed, energy and area parameters, including fast applications in which two smaller delay and low power adders are required, the effectiveness, including the proper area use of the hybrid adder recommended by it is evaluated. - Errorless Underwater Channel Selection Scheme Using Forward Error Rectification and Modulation
A. Herald, C. Vennila
Intelligent Automation and Soft Computing, 2022 - RETRACTION:Energy consumption in cluster communication using mcsbch approach in WSN
Vijay Ravindran, C. Vennila
Journal of Intelligent and Fuzzy Systems, 2022 - UTILISATION OF THE DLBM APPROACH FOR EFFECTIVE ROUTING OPTIMISATION IN AN OPTICAL BURST SWITCHING NETWORK ON ECOLOGICAL ENVIRONMENT
Journal of Environmental Protection and Ecology, 2022 - QoS Provisioning in MANET Using Fuzzy-Based Multifactor Multipath Routing Metric
S. Venkatasubramanian, A. Suhasini, C. Vennila
Lecture Notes on Data Engineering and Communications Technologies, 2022 - Design and Simulation of UWB Antenna with Multiple Notched Bands on the Feed Line
V. Ramkumar, R. Vijay Ravindran, R. Bhavani, C. Vennila, M. Gunavathi
Iet Conference Proceedings, 2022 - Efficient multipath zone-based routing in MANET Using (TID-ZMGR) ticked-ID based zone manager
S. Venkatasubramanian, A. Suhasini, C. Vennila
International Journal of Computer Networks and Applications, 2021 - A novel patch selection technique in ANN B-Spline Bayesian hyperprior interpolation VLSI architecture using fuzzy logic for highspeed satellite image processing
K. Chitra, C. Vennila
Journal of Ambient Intelligence and Humanized Computing, 2021 - AN ENERGY-EFFICIENT CLUSTERING PROTOCOL FOR IOT WIRELESS SENSOR NETWORKS BASED ON CLUSTER SUPERVISOR MANAGEMENT
Vijay Ravindran, Chockalingam Vannila
Comptes Rendus De L Academie Bulgare Des Sciences, 2021 - NOVEL ROUTING STRUCTURE WITH NEW LOCAL MONITORING, ROUTE SCHEDULING, AND PLANNING MANAGER IN ECOLOGICAL WIRELESS SENSOR NETWORK
Journal of Environmental Protection and Ecology, 2021 - Performance improvement in satellite image classification using adaptive supervised multi-resolution approach
S. Jayanthi, C. Vennila
Computer Communications, 2020 - Systolic array multiplier for augmenting data center networks communication link
S. Subathradevi, C. Vennila
Cluster Computing, 2019 - A review on machine learning techniques for QoS in WSN
International Journal of Advanced Science and Technology, 2019 - Advanced Satellite Image Classification of Various Resolution Image Using a Novel Approach of Deep Neural Network Classifier
S. Jayanthi, C. Vennila
Wireless Personal Communications, 2019 - Performance simulation of higher frequency band models for D2D application of 5G technology
B. Suganthi, C. Vennila
Applied Mathematics and Information Sciences, 2017 - Delay optimized novel architecture of FIR filter using clustered-retimed MAC unit Cell for DSP applications
S. Subathradevi, C. Vennila
Applied Mathematics and Information Sciences, 2017 - Comparison of modulation techniques for underwater optical wireless communication at Mallipattinam, Tamil Nadu
A Herald, C Vennila
1st International Conference on Emerging Trends in Engineering Technology and Science Icetets 2016 Proceedings, 2016 - Novelty in architecture of ROBDD for the minimization of interconnect delay
S. Subathradevi, C. Vennila
2015 International Conference on Control Instrumentation Communication and Computational Technologies Iccicct 2015, 2016 - Survey over on-chip buses for VLSI architecture with optimized delay for multiprocessor system design
S. Subathradevi, C. Vennila
2015 International Conference on Control Instrumentation Communication and Computational Technologies Iccicct 2015, 2016 - Design and testing of low power reliable NoCs for wireless applications
R. Ganesan, G. Seetharaman, Tughrul Arslan, C. Vennila, T. N. Prabakar
Advances in Intelligent Systems and Computing, 2016 - Modified architecture for distributed arithmetic with optimized delay using parallel processing
S. Subathradevi, C. Vennila
Indian Journal of Science and Technology, 2015 - Dynamic partial reconfigurable adaptive transceiver for OFDM based cognitive radio
C. Vennila, K. Suresh, Rohit Rather, G. Lakshminarayanan, Seok-Bum-Ko
Canadian Conference on Electrical and Computer Engineering, 2013 - Dynamic partial reconfigurable Viterbi decoder for wireless standards
C. Vennila, Alok Kumar Patel, G. Lakshminarayanan, Seok-Bum Ko
Computers and Electrical Engineering, 2013 - Dynamic partial reconfigurable FFT/IFFT pruning for OFDM based Cognitive radio
C. Vennila, Kumar Palaniappan CT, Kodati Vamsi Krishna, G. Lakshminarayanan, Seok-Bum Ko
Iscas 2012 2012 IEEE International Symposium on Circuits and Systems, 2012 - Dynamic partial reconfigurable FFT for OFDM based communication systems
C. Vennila, G. Lakshminarayanan, Seok-Bum Ko
Circuits Systems and Signal Processing, 2012 - Design of self reconfigurable task scheduler to implement multi-rate MB-OFDM UWB wireless system
C. Vennila, Anand Krishnan, Arpit Raj, G. Mithun Reddy, T.P. Santosh, Vijay K. Kumar, G. Lakshminarayanan
2010 International Conference on Electronic Devices Systems and Applications Icedsa 2010 Proceedings, 2010 - Design of reconfigurable UWB transmitter to implement multi-rate MB-OFDM UWB wireless system
C. Vennila, G. Lakshminarayanan, Sowjanya Tungala
Act 2009 International Conference on Advances in Computing Control and Telecommunication Technologies, 2009
