V.G. SARANYA

I am V. G. Saranya, a dedicated professor and researcher in the field of Electronics and Communication Engineering, completed a Ph.D. in Wireless Sensor Networks at SRM Institute of Science and Technology (SRM IST) Vadapalani, Chennai. I enrolled in 2022 and have successfully submitted my synopsis and thesis . My research focuses on advanced algorithms to improve the performance of Wireless Sensor Networks, highlight localization, routing, clustering, and security techniques. Throughout my research journey, I have published 3 journal papers indexed in SCI, 5 Scopus-indexed papers, and 2 book chapters. currently working as Assistant professor in computing technologies department, SRM IST Kattankulathur .

EDUCATION

Ph.D in Electronics and Communication Engineering

RESEARCH, TEACHING, or OTHER INTERESTS

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

Scopus Publications

Hybrid compression-based routing strategies for enhanced energy efficiency in wireless sensor networks
Sudhanshu Maurya, Karthik S, Priyadarsini K, P. C. Karthik, V.G. Saranya
Journal of Cloud Computing, 2025
Wireless Sensor Networks (WSNs) are essential in a wide range of applications, from environmental monitoring to industrial automation. However, the limited battery life of sensor nodes is a critical challenge, especially in large-scale deployments where frequent battery replacements are impractical. This study proposes a hybrid compression-based routing strategy to enhance energy efficiency in WSNs. Our approach combines Adaptive Lossless Data Compression (ALDC) with optimized routing protocols, explicitly leveraging Ant Colony Optimization (ACO) and Cuckoo Search (CS) to reduce data size before transmission and optimize the data forwarding paths. The results indicate that the proposed method significantly outperforms traditional routing strategies in terms of both energy consumption and network longevity. Specifically, our hybrid approach achieved a 40% reduction in energy usage, noticeable gains in data delivery ratio 32% and reduced packet loss, affirming its robustness and reliability compared to conventional methods, extending the network lifetime by approximately 25%. Furthermore, the compression ratio reached 78%, demonstrating the effectiveness of ALDC in minimizing data size without compromising data integrity. Network throughput also improved, with a reduction in path length by 84%, thus enhancing the reliability and responsiveness of the WSN. In conclusion, the hybrid compression-based routing strategy offers a promising solution for energy-efficient data transmission in WSNs, supporting prolonged network operations and ensuring reliable data delivery. This approach is particularly suitable for resource-constrained environments, where energy savings are paramount. Future work will refine the compression algorithm for dynamic data patterns and explore real-time adaptability in diverse WSN applications.
TDOA-based WSN localization with hybrid covariance matrix adaptive evolutionary strategy and gradient descent distance techniques
V.G. Saranya, S. Karthik
Alexandria Engineering Journal, 2025
Wireless Sensor Networks (WSNs) play a vital role in modern intelligent systems, with localization techniques critical for determining the precise positions of sensor nodes. Time Difference of Arrival (TDOA) is a widely utilized method for node localization. However, its accuracy suffers in noisy environments. This study introduces an innovative hybrid methodology that integrates Covariance Matrix Adaptive Evolutionary Strategy (CMA-ES) with Gradient Descent Distance (GDD) optimization to enhance the accuracy of TDOA-based localization. The hybrid approach utilizes the robust search capabilities of CMA-ES for initial location estimation, thereafter employing GDD to iteratively decrease the mean squared error (MSE) between estimated and real node locations. Simulations performed on several network settings showed substantial improvements. The TDOA-CMAES with GDD strategy demonstrated a maximum enhancement of 24.8 % in localization accuracy, a 36 % decrease in mean localization error (MLE), and an 18 % reduction in computation time relative to traditional approaches such as JAYA and Particle Swarm Optimization (PSO) and other current techniques. The hybrid method produced an Average Localization Error (ALE) much lower than existing techniques, illustrating its resilience in noisy conditions. Our hybrid TDOA-CMAES-GDD localization system is good for real-time WSN applications that need to quickly and accurately locate nodes because it reduces the time it takes to calculate and improves its accuracy. The method thus offers a strong, effective approach for improving TDOA-based localization in noisy settings.
Smart in-home health monitoring system using IoT: architecture and enhancements
K. Priyadarsini, S. Karthik, J. Jeba Sonia, P.C. Karthik, U.V. Anbhazhagu, V.G. Saranya
AI Numerical Optimization Iot and Blockchain for Healthcare 4 0, 2025
This chapter discusses how Internet of Things (IoT) technologies can be used for the creation of home-based monitoring systems for healthcare. The feasibility of IoT for remote, real-time monitoring of patients' basic health parameters with ease offers overwhelming benefits, especially in pandemic contexts like COVID-19. Healthcare systems are overburdened, and care providers are minimally exposed while adopting this paradigm. A variety of available technologies and platforms are reviewed to emphasize the recent trends, issues, and possible directions in developing cost-effective, scalable, and user-friendly IoT-based health monitoring systems. A case study is also provided to demonstrate a real-world implementation of such a system, with an emphasis on the integration of hardware, server-side infrastructure, and web interfaces for remote patient monitoring.
An IoT-based structure for development management using radio frequency identification system
K. Priyadarsini, S. Karthik, J. Jeba Sonia, U. V. Anbazhagu, V. G. Saranya
Responsible AI for Digital Health and Medical Analytics, 2024
The paper presents a semantic modeling technique for integrating RFID networks into an IoT framework. It proposes solutions for enabling high-level semantic interoperability, increasing RFID middleware for identification, authentication, validation, monitoring of IoT devices and provides a framework for tackling critical issues in IoT-enabled applications. The paper argues that the proposed approach would allow for life cycle management in logistics, planning, strategy education, and implementation of the best practices throughout a system's life cycle. Additionally, the document offers an insightful design of a placing conscious framework, introduces a product life cycle management architecture, and discusses the system's compatibility with the IEC 61499 standard. Overall, this paper offers valuable insights into managing the life cycle of products using RFID technology in an IoT infrastructure.
Health monitoring system in-home using IoT technology: Model and improvement
K. Priyadarsini, S. Karthik, J. Jeba Sonia, U. V. Anbazhagu, P. C. Karthik, V. G. Saranya
Responsible AI for Digital Health and Medical Analytics, 2024
This paper focuses on designing and improving a fitness tracking system using Internet of Things (IoT) strategies for patients, allowing them to stay at home while their doctors can access their critical medical measurements in near real-time. The key benefit of this system is that it enables patients to remain at home, which not only helps reduce the burden on the healthcare system but also protects doctors from exposure to potential pandemic viruses (e.g., Covid-19). In this paper, the author will analyze readily available technologies for health monitoring and internet connectivity to design an IoT-based system for monitoring patients' health. The final design prototype will include a hardware device installed in the patient's room, a backend server to collect and archive data into a database, and a web interface for doctors to monitor the patient's vital signs. Once developed, future work may focus on building a scalable server for more patients and increasing the range of health parameters that the device can measure.
A performance analysis of various compressive sensing techniques in IoT-based WSNs and its applications
Saranya Gunasekar, Karthik Sekhar, Priyadarsini Karthik
Aip Conference Proceedings, 2024
Compressive sensing is a way to deal with signals. The most efficient method for lowering latency and energy usage in IoT-based WSNs is compression sensing (CS). CS is used to lower the quantity and size of transmitted data packets via the IoTnetwork. The compressive sensing (CS) technique lowers the network's energy consumption and end-to-end latency. The practiceof compressive sensing is one of the signal-processing methods that find solutions to underdetermined linear systems by efficientlycollecting and recreating data. To recover a signal, a significant number of samples is required, as stated by the Nyquist-Shannon sampling theorem; however, this number can be lowered through optimization by taking advantage of the signal's intrinsic sparsity. It gives us an easy-to-use framework that lets us gather data and figure out what the signal is from fewer observations. In this paper, we compare CS reconstruction algorithms for overall system performance, data processing complexity values, reconstruction errors, and time for various compression techniques. This paper is useful for future work to compare CS reconstruction techniques to find a new optimized solution method.
Bio-Inspired Intelligent Routing in WSN: Integrating Mayfly Optimization and Enhanced Ant Colony Optimization for Energy-Efficient Cluster Formation and Maintenance
V. G. Saranya, S. Karthik
CMES Computer Modeling in Engineering and Sciences, 2024
Wireless Sensor Networks (WSNs) are a collection of sensor nodes distributed in space and connected through wireless communication. The sensor nodes gather and store data about the real world around them. However, the nodes that are dependent on batteries will ultimately suffer an energy loss with time, which affects the lifetime of the network. This research proposes to achieve its primary goal by reducing energy consumption and increasing the network’s lifetime and stability. The present technique employs the hybrid Mayfly Optimization Algorithm-Enhanced Ant Colony Optimization (MFOA-EACO), where the Mayfly Optimization Algorithm (MFOA) is used to select the best cluster head (CH) from a set of nodes, and the Enhanced Ant Colony Optimization (EACO) technique is used to determine an optimal route between the cluster head and base station. The performance evaluation of our suggested hybrid approach is based on many parameters, including the number of active and dead nodes, node degree, distance, and energy usage. Our objective is to integrate MFOA-EACO to enhance energy efficiency and extend the network life of the WSN in the future. The proposed method outcomes proved to be better than traditional approaches such as Hybrid Squirrel-Flying Fox Optimization Algorithm (HSFL-BOA), Hybrid Social Reindeer Optimization and Differential Evolution-Firefly Algorithm (HSRODE-FFA), Social Spider Distance Sensitive-Iterative Antlion Butterfly Cockroach Algorithm (SADSS-IABCA), and Energy Efficient Clustering Hierarchy Strategy-Improved Social Spider Algorithm Differential Evolution (EECHS-ISSADE).
A Comprehensive Study on Security Attacks and its Defense Techniques in Wireless Sensor Networks
Saranya V G, S. Karthik
Proceedings of the 4th International Conference on Smart Electronics and Communication Icosec 2023, 2023
In a variety of crucial applications, wireless sensor networks (WSNs) are being deployed regularly as the new speed-accelerating technology. Network efficiency and safety may be directly and physically impacted by any harm or vulnerability to data security. Key management, identification, and trust management in wireless sensing networks is one of the active study fields (WSN). It can be challenging to decide which key management strategies in a particular WSN application are optimal because researchers have offered a variety of protection schemes. This research study has thoroughly analysed the characteristics of various trust management, identity, and key management techniques as well as their potential applications to specific applications. Based on this review, the previously recommended methodology and advantages of the key management, verification, and trust systems in WSN are described. This study is finally concluded by describing potential future directions for IoT security, including the lack of organised adaptable algorithms for encryption, the use of algorithms based on machine learning to enhance security and related challenges, and the use of blockchain technology to deal with threats in IoT.
A Brief Survey on Cluster based Energy Efficient Routing Protocols in IoT based Wireless Sensor Networks
Priyadarsini K, Saranya V G, Karthik S
International Journal on Recent and Innovation Trends in Computing and Communication, 2022
The wireless sensor network (WSN) consists of a large number of randomly distributed nodes capable of detecting environmental data, converting it into a suitable format, and transmitting it to the base station. The most essential issue in WSNs is energy consumption, which is mostly dependent on the energy-efficient clustering and data transfer phases. We compared a variety of algorithms for clustering that balance the number of clusters. The cluster head selection protocol is arbitrary and incorporates energy-conscious considerations. In this survey, we compared different types of energy-efficient clustering-based protocols to determine which one is effective for lowering energy consumption, latency and extending the lifetime of wireless sensor networks (WSN) under various scenarios.

RECENT SCHOLAR PUBLICATIONS

Hybrid compression-based routing strategies for enhanced energy efficiency in wireless sensor networks
S Maurya, K S, P K, PC Karthik, VG Saranya
Journal of Cloud Computing 14 (1), 71 , 2025
2025.0
Citations: 1
Visual Analytics in Healthcare Resource Optimization: A Tableau-Based Case Study in India
S Karthik, K Priyadarsini, VG Saranya
The 2025 International Conference on Advanced Research in Electronics and … , 2025
2025.0
Citations: 1
An IoT-based structure for development management using radio frequency identification system
K Priyadarsini, S Karthik, JJ Sonia, UV Anbazhagu, VG Saranya
Responsible AI for Digital Health and Medical Analytics, 327-350 , 2025
2025.0
Citations: 2
Health Monitoring System In-Home Using IoT Technology: Model and Improvement
K Priyadarsini, S Karthik, JJ Sonia, UV Anbazhagu, PC Karthik, ...
Responsible AI for Digital Health and Medical Analytics, 351-376 , 2025
2025.0
TDOA-based WSN localization with hybrid covariance matrix adaptive evolutionary strategy and gradient descent distance techniques
VG Saranya, S Karthik
Alexandria Engineering Journal 112, 723-738 , 2025
2025.0
Citations: 10
Bio-inspired intelligent routing in WSN: integrating mayfly optimization and enhanced ant colony optimization for energy-efficient cluster formation and maintenance
V Saranya, S Karthik
Computer Modeling in Engineering & Sciences 141 (1), 127 , 2024
2024.0
Citations: 15
Context based ranking strategies for renowned instructional methodologies
V Saranya, A Abdullah, P Ramadass, S Srinivasan, BD Shivahare, ...
Intelligence-Based Medicine 10, 100186 , 2024
2024.0
A Comprehensive Study on Security Attacks and its Defense Techniques in Wireless Sensor Networks
VG Saranya, S Karthik
2023 4th International Conference on Smart Electronics and Communication … , 2023
2023.0
Citations: 3
A Brief Survey on Cluster based Energy Efficient Routing Protocols in IoT based Wireless Sensor Networks
Priyadarsini K, Saranya V G, Karthik S
International Journal on Recent and Innovation Trends in Computing and … , 2022
2022.0
Citations: 2
Smart in-home health monitoring system using IoT: architecture and enhancements
K Priyadarsini, S Karthik, J Jeba Sonia, PC Karthik, UV Anbhazhagu, ...

MOST CITED SCHOLAR PUBLICATIONS

Bio-inspired intelligent routing in WSN: integrating mayfly optimization and enhanced ant colony optimization for energy-efficient cluster formation and maintenance
V Saranya, S Karthik
Computer Modeling in Engineering & Sciences 141 (1), 127 , 2024
2024.0
Citations: 15
TDOA-based WSN localization with hybrid covariance matrix adaptive evolutionary strategy and gradient descent distance techniques
VG Saranya, S Karthik
Alexandria Engineering Journal 112, 723-738 , 2025
2025.0
Citations: 10
A Comprehensive Study on Security Attacks and its Defense Techniques in Wireless Sensor Networks
VG Saranya, S Karthik
2023 4th International Conference on Smart Electronics and Communication … , 2023
2023.0
Citations: 3
An IoT-based structure for development management using radio frequency identification system
K Priyadarsini, S Karthik, JJ Sonia, UV Anbazhagu, VG Saranya
Responsible AI for Digital Health and Medical Analytics, 327-350 , 2025
2025.0
Citations: 2
A Brief Survey on Cluster based Energy Efficient Routing Protocols in IoT based Wireless Sensor Networks
Priyadarsini K, Saranya V G, Karthik S
International Journal on Recent and Innovation Trends in Computing and … , 2022
2022.0
Citations: 2
Hybrid compression-based routing strategies for enhanced energy efficiency in wireless sensor networks
S Maurya, K S, P K, PC Karthik, VG Saranya
Journal of Cloud Computing 14 (1), 71 , 2025
2025.0
Citations: 1
Visual Analytics in Healthcare Resource Optimization: A Tableau-Based Case Study in India
S Karthik, K Priyadarsini, VG Saranya
The 2025 International Conference on Advanced Research in Electronics and … , 2025
2025.0
Citations: 1
Health Monitoring System In-Home Using IoT Technology: Model and Improvement
K Priyadarsini, S Karthik, JJ Sonia, UV Anbazhagu, PC Karthik, ...
Responsible AI for Digital Health and Medical Analytics, 351-376 , 2025
2025.0
Context based ranking strategies for renowned instructional methodologies
V Saranya, A Abdullah, P Ramadass, S Srinivasan, BD Shivahare, ...
Intelligence-Based Medicine 10, 100186 , 2024
2024.0
Smart in-home health monitoring system using IoT: architecture and enhancements
K Priyadarsini, S Karthik, J Jeba Sonia, PC Karthik, UV Anbhazhagu, ...