Computer Networks and Communications, Computer Engineering, Multidisciplinary, Computer Science Applications
30
Scopus Publications
210
Scholar Citations
9
Scholar h-index
6
Scholar i10-index
Scopus Publications
AI-enhanced routing and slicing strategy for QoS-aware mobile ad hoc networks Venkatesan C., Shaha Al-Otaibi, Balaji Vijayan V., Sathiya T., Mona M. Jamjoom, Surendiran J. Scientific Reports, 2026 Ad hoc networks persistently struggle to guarantee stringent Quality of Service (QoS) when node mobility, interference, and heterogeneous traffic patterns compete for scarce wireless resources. This article proposes an AI-enhanced routing and slicing framework for Mobile Ad Hoc Networks (MANETs) that couples Deep Reinforcement Learning (DRL) with adaptive Network Slicing (NS) to steer packets through latency aware, slice specific paths. The DRL agent observes local topology changes, queue states, and slice budgets, then selects next hops that jointly minimize end to end delay and maximize packet delivery ratio, while a fuzzy logic slicer reallocates bandwidth across slices in real time. We trained the agent in MATLAB using Proximal Policy Optimization and implemented slice control with native Communications System Toolbox functions. Simulations over 100 to 300 nodes moving under the Random Waypoint model showed that, compared with Ad Hoc On Demand Distance Vector (AODV), Dynamic Source Routing (DSR), and a standalone DRL router, the proposed scheme educed average delay by 37%, increased throughput by a factor of 1.8, and lifted packet delivery ratio by 22% at node speeds up to 20 m/s, without sacrificing energy efficiency or incurring excessive control overhead. These results confirm that integrating intelligent routing with agile slicing is a viable pathway to sustain application level QoS in highly dynamic MANETs.
A Scalable Hybrid Edge-Cloud Approach to Minimizing Latency in IoT Applications P. Radhakrishnan, Smitha Kurian, V. Balaji Vijayan, M. Mahabooba, Dileep Pulugu, D. Menaga International Journal of Computational and Experimental Science and Engineering, 2025 The increasing reliance on IoT applications demands efficient, scalable solutions to address latency, a critical factor in time-sensitive operations. Hybrid Edge-Cloud approaches leverage the strengths of both edge and cloud computing to optimize performance and ensure seamless connectivity. However, existing methods often struggle with excessive latency due to resource allocation inefficiencies, limited edge device capabilities, and network congestion. This study proposes a Hybrid model based on Scalable Hybrid Edge-Cloud Approach (SHECA) framework, designed to mitigate these challenges in IoT applications. SHECA integrates edge computing for real-time data processing and cloud computing for storage, advanced analytics, and long-term decision-making. By dynamically distributing computational loads and leveraging intelligent resource allocation, the framework significantly reduces latency and enhances system responsiveness. The findings demonstrate that SHECA reduces average latency by 35% compared to traditional cloud-only methods, ensuring faster response times, scalability, and improved user experience in IoT applications. This hybrid solution offers a robust approach for latency minimization in diverse IoT scenarios.
A Study on Cybersecurity Challenges and Emerging Trends in Contemporary Technologies Balaji Vijayan Venkateswarulu, Mohammed Muffazall, Mohammed Sadiq, Muiz Mujawar Proceedings of 2025 International Conference on Computing for Sustainability and Intelligent Future Comp Sif 2025, 2025 Cybersecurity is an important part of information technology because protecting digital information has become one of the most important challenges in today's world. Cybercrime in particular is on the rise, and when we talk about cybersecurity, we usually think of threats from cybercriminals. To address this issue, governments and organizations around the world are using various strategies and technologies to mitigate these risks. Despite these efforts, cybersecurity continues to be a major concern for many stakeholders.
AgroSmart: Empowering Farmers with a Seamless E-Commerce Platform V. Balaji Vijayan, Ananya GR, Bharath Gowda S, Manoj M C, K M Chethan International Conference on Smart Systems for Applications in Electrical Sciences Icsses 2025, 2025 Agriculture forms the backbone of economies around the world, yet farmers often face challenges such as limited access to markets, dependence on intermediaries, and lack of actionable insights, which hinder their productivity and profitability. This paper presents AgroSmart, a Python-based e-Commerce platform designed to empower farmers by integrating machine learning with a user-friendly web interface. Built using Flask and MySQL, AgroSmart offers a seamless solution for farmers to connect directly with buyers, eliminating intermediaries, and fostering fair trade practices. At the heart of AgroSmart lies a machine learning model “Gradient Boosting algorithm” provides personalized crop recommendations based on environmental conditions, leveraging advanced algorithms to optimize yields. The platform also incorporates real-time market analytics, government scheme recommendations, and secure OTP-based authentication to enhance usability and accessibility. By bridging the digital divide, AgroSmart promotes sustainable agricultural practices and increases farmer's socio-economic well-being.
Energy efficient data aggregation in wireless sensor network using BEE swarm optimisation K. Prabakaran, R. Raffik, Balaji Vijayan Venkateswaralu, R. Thiyagarajan, S. Arun, R. Krishnamoorthy Aip Conference Proceedings, 2024 In a Wireless Sensor Network (WSN), sensor nodes are randomly distributed over the network and self-configure. By using clustering methods, load balancing and scaling are improved. One component that this algorithm uses to reduce energy use is data transmission. Nevertheless, the most difficult issue is the constant drain of sensor batteries. As a result, numerous efforts are being examined to enhance the network use of sensor energy inside a particular group. To reduce energy consumption in nodes with an adequate reduction in retransmission rates and packet congestion, we developed a bee swarm optimization model in this study and deployed sensor nodes in bigger environments. To reduce latency and packet loss, a cluster-based bee swarm optimization (BSO) clustering is used to elect cluster leaders and elect the WSN as a whole. The lower packet loss ratio guarantees by BSO that packets reaching the destination node more quickly. It has been confirmed through simulation that the entire process is optimised for energy usage and prevents packet retransmission by reducing packet waiting time.
A Systemic Review on Automatic Acoustic Scene Classification J.Surendiran, P.B Edwin Prabhakar, M.Mohammed Ibrahim, G Saritha, Sathish K, V.Balaji Vijayan 4th International Conference on Power Energy Control and Transmission Systems Harnessing Power and Energy for an Affordable Electrification of India Icpects 2024, 2024 Speech research is marked as a most challenging areas among the several challenging research areas. The present literature is analyzed and projected to aid future investigations of the global speech research community. The problems concerned with the acoustic scene corpora, front end algorithms yielding to efficient scene representation, back end engines which outright chore of recognition, are projected in this study. Many works on acoustic scene recognition are analyzed from the perspective of machine learning and deep learning, time length, conviction of development and accessibility. The powerful techniques tending to rich features and robust scene recognition are enlightened in this research review.
Seamless Wi-Fi Integration Enhancing the Experimental Model of Smart Car Parking Systems with IoT and Modulated Sensors S. Arunkumar, M.Vanitha Sheba, S.Usha Naidu, V.Balaji Vijayan, S. Arun, R. Thiagarajan 2nd International Conference on Sustainable Computing and Smart Systems Icscss 2024 Proceedings, 2024 The main reason to improve traffic congestion on highways, multi-storied buildings, and malls caused by the lack of parking places is the smart vehicle parking system that uses the Internet of Things (IoT). If there is an empty spot close to the user's current position, the system will show it to them. We want to maximize the usage of parking spots with our approach. Whenever a parking spot becomes available, we mark it as reserved for the user. An error-free, dependable, secure, and quick management system is possible with a smart parking system, as explained above. The development of the Internet of Things (IoT) has made the concept of a smart-city appear more feasible. Improving the efficiency and dependability of city infrastructure is a constant goal of research and development in the Internet of Things. The Internet of Things is helping to solve issues like traffic jams, a lack of parking, and unsafe roads. The proposed Smart Parking system includes the installation of an Internet of Things (IoT) module at each parking lot to track and communicate the availability of parking spots. Customers may also use the included mobile app to see whether a parking spot is available and reserve it if necessary. The IoT Smart Car Parking System (IoTSCPS) is the name of the proposed system. To test how well it works, it is cross-validated with the traditional Smart Parking Method (SPM). An overview of the system's architecture is also provided in the article. The paper concludes with a discussion of the system's operation, this time in the form of a use case, which demonstrates the validity of the suggested model.
ELNN: A Novel Approach to Identify Periodontal Disease from Panoramic Radiographs in Earlier Stages using Enhanced Logical Neural Networks Bhuvaneshwari Karthikeyan, V.Balaji Vijayan, Kotteeswaran R, M.K. Vidhyalakshmi, R. Krishnamoorthy, R. Thiagarajan 2024 International Conference on Smart Technologies for Sustainable Development Goals Icstsdg 2024, 2024 Periodontal disease is a prevalent condition that can lead to serious dental complications if not detected and treated early. In this paper, we propose an Enhanced Logical Neural Networks (ELNN) model for identifying periodontal disease at early stages from panoramic radiographs. The ELNN model integrates AlexN et, a convolutional neural network (CNN) for feature extraction, with XGBoost for classification, creating a robust hybrid architecture. The dataset used includes 17,654 labeled images collected from hospital records over the last two years. Our preprocessing techniques involve resizing, grayscale conversion, noise reduction, and segmentation to ensure optimal data quality for feature extraction. The ELNN model outperforms traditional machine learning models, such as Logistic Regression, Support Vector Machine (SVM), and standalone deep learning models, achieving an accuracy of 97.77<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">%</sup>. The model demonstrates superior precision (96.45<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">%</sup>) and recall (96.89<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">%</sup>) compared to other approaches, ensuring high reliability in distinguishing early-stage periodontal disease from healthy and advanced cases. The results suggest that the ELNN model has strong potential for clinical applications in dental diagnostics, especially for early detection, which is critical for effective treatment.
INCS: Design and Development of an Oral Cancer Identification Methodology based on Improved Neural Classification Scheme Bhuvaneshwari Karthikeyan, Reddi Khasim Shaik, V. Balaji Vijayan, A V. Allin Geo, R. Thiagarajan, R. Krishnamoorthy Proceedings 2024 4th International Conference on Soft Computing for Security Applications Icscsa 2024, 2024 The early detection of oral cancer is critical to improving patient outcomes and survival rates. This paper presents the Improved Neural Classification Scheme (INCS) for identifying oral cancer using deep learning techniques. The proposed model integrates MobileNet and EfficientNet, two state-of-the-art convolutional neural networks (CNN), to create an ensemble capable of extracting both fine-grained and high-level semantic features from oral cancer images. The dataset used consists of 500 oral cancer images and 450 non-cancerous images sourced from Kaggle. A comprehensive preprocessing pipeline, including resizing, normalization, and data augmentation, was implemented to optimize the dataset for model training. The INCS model achieved an accuracy of 98.65%, outperforming other models such as MobileNet, EfficientNet, ResNet, and VGG16. The model also achieved high scores in precision (96.89%), recall (97.45%), and F1score (97.17%), demonstrating its robustness in distinguishing between cancerous and non-cancerous lesions. This high accuracy, combined with its low false positive and false negative rates, highlights the potential of INCS for clinical application in oral cancer diagnosis. Future work will focus on expanding the dataset and exploring real-time deployment in clinical settings.
Social Media Sentiment Analysis Using Deep Learning Approach M. Mohamed Iqbal, K. S. Arikumar, Balaji Vijayan Venkateswaralu, S. Aarif Ahamed Lecture Notes of the Institute for Computer Sciences Social Informatics and Telecommunications Engineering Lnicst, 2023
JBits Based Fault Tolerant Framework for Evolvable Hardware Proceedings of the International Conference on Engineering of Reconfigurable Systems and Algorithms, 2003
AI-enhanced routing and slicing strategy for QoS-aware mobile ad hoc networks MMJS Venkatesan C., Shaha Al-Otaibi, Balaji Vijayan V., Sathiya T. Scientific Reports , 2026 2026 Citations: 2
AgroSmart: Empowering Farmers with a Seamless E-Commerce Platform VB Vijayan, GR Ananya, B Gowda, MC Manoj, KM Chethan 2025 3rd International Conference on Smart Systems for applications in … , 2025 2025
A Study on Cybersecurity Challenges and Emerging Trends in Contemporary Technologies BV Venkateswarulu, M Muffazall, M Sadiq, M Mujawar 2025 International Conference on Computing for Sustainability and … , 2025 2025
A Scalable Hybrid Edge-Cloud Approach to Minimizing Latency in IoT Applications P Radhakrishnan, S Kurian, VB Vijayan, M Mahabooba, D Pulugu, ... International Journal of Computational and Experimental Science and … , 2025 2025 Citations: 6
Improved Adaptive Fairness-Indexed Technique for Congestion Control in Underwater Networks KS Manojee, R Nivethitha, T Thamaraimanalan, M Ranjithkumar 2024 International Conference on Communication, Control, and Intelligent … , 2024 2024 Citations: 1
Integrative remote sensing approaches using generative adversarial networks for urban heat island analysis and mitigation G Sundar, P Patchaiammal, BV Venkateshwarulu, TP Kumar, ... Remote Sensing in Earth Systems Sciences 7 (4), 681-698 , 2024 2024 Citations: 9
A Smart and Intelligent Robotic Design to Rescue Human from Disaster Conditions Using Artificial Intelligence Assistance RK Shaik, VB Vijayan, AL Mangrulkar, R Krishnamoorthy, R Thiagarajan 2024 International Conference on Smart Technologies for Sustainable … , 2024 2024 Citations: 6
ELNN: A Novel Approach to Identify Periodontal Disease From Panoramic Radiographs in Earlier Stages Using Enhanced Logical Neural Networks B Karthikeyan, VB Vijayan, MK Vidhyalakshmi, R Krishnamoorthy, ... 2024 International Conference on Smart Technologies for Sustainable … , 2024 2024 Citations: 2
Enhancing Agricultural Efficiency through IoT-Based Water Valve Actuators VB Vijayan, V Madhusudhana, BN Sachin, AM Pruthvi Journal of Big Data Analytics and Business Intelligence, 10-19 , 2024 2024
A Systemic Review on Automatic Acoustic Scene Classification J Surendiran, PBE Prabhakar, MM Ibrahim, G Saritha, VB Vijayan 2024 International Conference on Power, Energy, Control and Transmission … , 2024 2024 Citations: 1
INCS: Design and Development of an Oral Cancer Identification Methodology based on Improved Neural Classification Scheme B Karthikeyan, RK Shaik, VB Vijayan, AVA Geo, R Thiagarajan, ... 2024 4th International Conference on Soft Computing for Security … , 2024 2024 Citations: 30
Seamless Wi-Fi Integration Enhancing the Experimental Model of Smart Car Parking Systems with IoT and Modulated Sensors S Arunkumar, MV Sheba, SU Naidu, VB Vijayan, S Arun, R Thiagarajan 2024 2nd International Conference on Sustainable Computing and Smart Systems … , 2024 2024 Citations: 5
Wireless Networking: Smart Agriculture VB Vijayan, A Haleem, A Irbaz, AA Rehman, F Pasha Journal of Cyber Security, Privacy Issues and Challenges 3 (1), 32-37 , 2024 2024 Citations: 2
Wireless Networking: Smart Agriculture FP V Balaji Vijayan, Abdul Haleem, Abdullah Irbaz, Ali Abdul Rehman Journal of Cyber Security, Privacy Issues and Challenges 3 (1), 32-37 , 2024 2024
Experimental evaluation of smart forest fire detection methodology using internet of things and logical sensors VB Vijayan, T Dhanalakshmi, P Parthasarathi, S Nivedha, ... 2024 10th International Conference on Communication and Signal Processing … , 2024 2024 Citations: 19
Energy efficient data aggregation in wireless sensor network using BEE swarm optimisation K Prabakaran, R Raffik, BV Venkateswaralu, R Thiyagarajan, S Arun, ... AIP Conference Proceedings 2816 (1), 050004 , 2024 2024 Citations: 20
Social Media Sentiment Analysis Using Deep Learning Approach MM Iqbal, KS Arikumar, BV Venkateswaralu, SA Ahamed International Conference on Intelligent Systems and Machine Learning, 431-438 , 2022 2022 Citations: 1
A robust, scalable, and energy-efficient routing strategy for UWSN using a Novel Vector-based Forwarding routing protocol D Santhi Jeslet, V Balaji Vijayan, R Thiagarajan, I Mohan, R Kalpana Journal of Circuits, Systems and Computers 31 (15), 2250265 , 2022 2022 Citations: 9
Epidemiology and ventilation characteristics of confirmed cases of severe COVID-19 pneumonia admitted in intensive care unit (EPIC19): A multicentre observational study AA Havaldar, MV Kumar, B Vijayan, J Prakash, M Kartik, A Sangale Indian Journal of Anaesthesia 66 (10), 724-733 , 2022 2022 Citations: 6
Electro search optimization based long short‐term memory network for mobile malware detection P Shanmugam, B Venkateswarulu, R Dharmadurai, T Ranganathan, ... Concurrency and Computation: Practice and Experience 34 (19), e7044 , 2022 2022 Citations: 10
MOST CITED SCHOLAR PUBLICATIONS
INCS: Design and Development of an Oral Cancer Identification Methodology based on Improved Neural Classification Scheme B Karthikeyan, RK Shaik, VB Vijayan, AVA Geo, R Thiagarajan, ... 2024 4th International Conference on Soft Computing for Security … , 2024 2024 Citations: 30
An efficient routing protocol based on polar tracing function for underwater wireless sensor networks for mobility health monitoring system application BV Venkateswarulu, N Subbu, S Ramamurthy Journal of medical systems 43 (7), 218 , 2019 2019 Citations: 24
Cyber attack detection on IOT using network traffic mechanism by neural network predictive approach R Krishnamoorthy, V Balajivijayan, DRT Sowmiya, DS Arun European Journal of Molecular & Clinical Medicine 7 (10), 3690-3697 , 2020 2020 Citations: 21
Energy efficient data aggregation in wireless sensor network using BEE swarm optimisation K Prabakaran, R Raffik, BV Venkateswaralu, R Thiyagarajan, S Arun, ... AIP Conference Proceedings 2816 (1), 050004 , 2024 2024 Citations: 20
Experimental evaluation of smart forest fire detection methodology using internet of things and logical sensors VB Vijayan, T Dhanalakshmi, P Parthasarathi, S Nivedha, ... 2024 10th International Conference on Communication and Signal Processing … , 2024 2024 Citations: 19
Electro search optimization based long short‐term memory network for mobile malware detection P Shanmugam, B Venkateswarulu, R Dharmadurai, T Ranganathan, ... Concurrency and Computation: Practice and Experience 34 (19), e7044 , 2022 2022 Citations: 10
Integrative remote sensing approaches using generative adversarial networks for urban heat island analysis and mitigation G Sundar, P Patchaiammal, BV Venkateshwarulu, TP Kumar, ... Remote Sensing in Earth Systems Sciences 7 (4), 681-698 , 2024 2024 Citations: 9
A robust, scalable, and energy-efficient routing strategy for UWSN using a Novel Vector-based Forwarding routing protocol D Santhi Jeslet, V Balaji Vijayan, R Thiagarajan, I Mohan, R Kalpana Journal of Circuits, Systems and Computers 31 (15), 2250265 , 2022 2022 Citations: 9
Management of encrypted data and de-duplication of big data in cloud computing S Srivastava, R Thiagarajan, R Krishnamoorthy, S Arun, S Padmapriya 2021 3rd international conference on advances in computing, communication … , 2021 2021 Citations: 9
Automatic GA Based Evolution of Fault Tolerant Digital Circuits AP Shanthi, B Vijayan, M Rajendran, S Veluswami 4th Asia–Pacific Conference on Simulated Evolution and Learning (SEAL 02 … , 2002 2002 Citations: 7
A Scalable Hybrid Edge-Cloud Approach to Minimizing Latency in IoT Applications P Radhakrishnan, S Kurian, VB Vijayan, M Mahabooba, D Pulugu, ... International Journal of Computational and Experimental Science and … , 2025 2025 Citations: 6
A Smart and Intelligent Robotic Design to Rescue Human from Disaster Conditions Using Artificial Intelligence Assistance RK Shaik, VB Vijayan, AL Mangrulkar, R Krishnamoorthy, R Thiagarajan 2024 International Conference on Smart Technologies for Sustainable … , 2024 2024 Citations: 6
Epidemiology and ventilation characteristics of confirmed cases of severe COVID-19 pneumonia admitted in intensive care unit (EPIC19): A multicentre observational study AA Havaldar, MV Kumar, B Vijayan, J Prakash, M Kartik, A Sangale Indian Journal of Anaesthesia 66 (10), 724-733 , 2022 2022 Citations: 6
Seamless Wi-Fi Integration Enhancing the Experimental Model of Smart Car Parking Systems with IoT and Modulated Sensors S Arunkumar, MV Sheba, SU Naidu, VB Vijayan, S Arun, R Thiagarajan 2024 2nd International Conference on Sustainable Computing and Smart Systems … , 2024 2024 Citations: 5
GA based on-line testing and recovery for critical digital systems AP Shanthi, B Vijayan, M Rajendran, S Veluswami Proceedings of the HiPC Workshop on Soft Computing, 81-89 , 2002 2002 Citations: 5
Hybrid genetic algorithm-based unit commitment SR Paranjothi, V Balaji Electric Power Components and Systems 30 (10), 1047-1054 , 2002 2002 Citations: 3
AI-enhanced routing and slicing strategy for QoS-aware mobile ad hoc networks MMJS Venkatesan C., Shaha Al-Otaibi, Balaji Vijayan V., Sathiya T. Scientific Reports , 2026 2026 Citations: 2
ELNN: A Novel Approach to Identify Periodontal Disease From Panoramic Radiographs in Earlier Stages Using Enhanced Logical Neural Networks B Karthikeyan, VB Vijayan, MK Vidhyalakshmi, R Krishnamoorthy, ... 2024 International Conference on Smart Technologies for Sustainable … , 2024 2024 Citations: 2
Wireless Networking: Smart Agriculture VB Vijayan, A Haleem, A Irbaz, AA Rehman, F Pasha Journal of Cyber Security, Privacy Issues and Challenges 3 (1), 32-37 , 2024 2024 Citations: 2
Technique for Automation Billing in Smart Shopping” R Thiagarajan, V BalajiVijayan, DS Arun, I MohanNovel International Journal of Scientific & Technology Research 9 (4), 5363-5369 , 2020 2020 Citations: 2
