Computer Engineering, Computer Science Applications, Artificial Intelligence, Hardware and Architecture
19
Scopus Publications
179
Scholar Citations
6
Scholar h-index
5
Scholar i10-index
Scopus Publications
QoS-Aware Deployment and Synchronization of Digital Twins Over Federated Cloud Platforms for Smart Infrastructure Monitoring M V Narayana, Naveen Reddy N, Madhu S, Madhu T, Niladri Sekhar Dey, Sanjeev Shrivastava International Journal of Advanced Computer Science and Applications, 2025 This electronic increasingly, Digital Twin (DT) systems are being leveraged in smart infrastructure settings (e.g., structural health monitoring, intelligent traffic controls, and distributed utility networks). Yet, the available solutions all face hurdles that can prevent real-time synchronization of DT instances across federated cloud platforms, primarily due to latency variation, quality of service (QoS) assurance, and stale data, which are all consequences of heterogeneous computer environments. Most solutions depend on static cloud-only models of deployment, with no option for dynamic negotiation of resources. These provide long update times (typically greater than 200ms), low accuracy rates, and low real-time responsiveness. Additionally, traditional DT models were not developed with multi-regional deployment or QoS workloads in mind. In this work, a QoS-Aware Federated Digital Twin Orchestration Framework (Q-FDTO) is designed to allow latency-critical monitoring of infrastructure across different federated cloud regions, through the integration of a hybrid edge-cloud control plane, adaptive synchronization, jitter consideration for observed intervals, and dynamic resource allocation via reinforcement learning for defined QoS Service Level Objectives (SLOs). This system was evaluated on a smart city testbed of 1200 sensor nodes. The testbed monitored sensor readings for structural strain, vibration, and traffic density across twelve locations. The digital twin pipeline is comprehensive [i.e., (i) ingestion via Wi-Fi MQTT, (ii) stream fusion of all the sensor readings via Kalman filtering, and (iii) twin modeling of prediction, through a temporal graph convolutional network (T-GCN)]. To assess performance, sync policies were evaluated on metrics for average update latency (ms), sync drift (ms), and data consistency rate (%). The results demonstrate that Q-FDTO had an average update latency of 87.3 ms, reduced from 194.6 ms, and a 96.2% consistency rate across federated nodes with less than 2.5% sync drift over 10-minute intervals, showing Q-FDTO architecture ability for network boundaries and also compatible with AWS Outposts and Azure Arc hybrid cloud environments. It establishes a scalable and practical approach to latency-sensitive DT deployments in the realm of smart infrastructure systems.
A NOVEL INTEGRATED FRAMEWORK FOR SECURE IOT-BASED SMART VEHICLE MANAGEMENT USING MACHINE LEARNING AND BLOCKCHAIN FOR PATH PLANNING AND COLLISION AVOIDANCE Journal of Theoretical and Applied Information Technology, 2025
A particle swarm optimization inspired global and local stability driven predictive load balancing strategy Niladri Sekhar Dey, Hrushi Kesava Raju Sangaraju Indonesian Journal of Electrical Engineering and Computer Science, 2024 In distributed systems and parallel computing, optimal load balancing is difficult. These abstract addresses load balancing in distributed situations, highlighting current solutions' flaws and emphasizing the need for new ones. Load balancing research includes centralized and distributed algorithms, heuristics, and predictive models. Despite various successful methods, workload adaptability, overhead reduction, and scaling to large systems remain unresolved. This study proposes a particle swarm optimization (PSO) load balancing method that considers global and local stability considerations. The proposed method uses PSO principles to balance exploration and exploitation and allocate resources among distributed nodes. Predictive components improve preventative load management by predicting workload changes. Global and local load balancing stability criteria distinguish this study. The recommended method considers global system-wide performance indicators, local node-level characteristics, and micro-level stability to maximize system efficiency. A dual-focus technique distinguishes the proposed load balancing strategy from others, solving dynamic distributed system challenges. The study examines load balancing system advances and suggests improvements and further research. More accurate prediction modeling, stability measures, and application-specific enhancements may be studied in the future. Experimental validation and real-world implementation of the recommended approach are necessary to determine its practicality and ability to handle modern distributed computing systems.
Energy-Efficiency Optimization in IoT Networks: Algorithms, Techniques, and Case Studies 15th International Conference on Advances in Computing Control and Telecommunication Technologies Act 2024, 2024
Comprehensive Analysis of Text Summarization Techniques for Legal Documents 15th International Conference on Advances in Computing Control and Telecommunication Technologies Act 2024, 2024
Hybrid Load Balancing Strategy for Cloud Data Centers with Novel Performance Evaluation Strategy International Journal of Intelligent Systems and Applications in Engineering, 2023
ACO-Inspired Load Balancing Strategy for Cloud-Based Data Centre with Predictive Machine Learning Approach Niladri Dey, T. Gunasekhar, K. Purnachand Computers Materials and Continua, 2023 Virtual Machines are the core of cloud computing and are utilized to get the benefits of cloud computing. Other essential features include portability, recovery after failure, and, most importantly, creating the core mechanism for load balancing. Several study results have been reported in enhancing load-balancing systems employing stochastic or biogenetic optimization methods. It examines the underlying issues with load balancing and the limitations of present load balance genetic optimization approaches. They are criticized for using higher-order probability distributions, more complicated solution search spaces, and adding factors to improve decision-making skills. Thus, this paper explores the possibility of summarizing load characteristics. Second, this study offers an improved prediction technique for pheromone level prediction over other typical genetic optimization methods during load balancing. It also uses web-based third-party cloud service providers to test and validate the principles provided in this study. It also reduces VM migrations, time complexity, and service level agreements compared to other parallel standard approaches.
A NOVEL INTEGRATED FRAMEWORK FOR SECURE IOT-BASED SMART VEHICLE MANAGEMENT USING MACHINE LEARNING AND BLOCKCHAIN FOR PATH PLANNING AND COLLISION AVOIDANCE MV NARAYANA, P PARTHASARADHY, PJ KUMAR, S KIRAN, ... Journal of Theoretical and Applied Information Technology 103 (21) , 2025 2025
YOLO-BASED FEATURE LEARNING WITH RF–XGB ENSEMBLES FOR ROBUST CITRUS LEAF DISEASE DETECTION KV AJAY, MSKB PADMAJA PULICHERLA, DVD P THIRUMOORTHY, ... Journal of Theoretical and Applied Information Technology 103 (21) , 2025 2025
QoS-Aware Deployment and Synchronization of Digital Twins Over Federated Cloud Platforms for Smart Infrastructure Monitoring. MV Narayana, NS Dey, S Shrivastava International Journal of Advanced Computer Science & Applications 16 (8) , 2025 2025
A particle swarm optimization inspired global and local stability driven predictive load balancing strategy NS Dey, HKR Sangaraju Indonesian Journal of Electrical Engineering and Computer Science 35 (3), 10 … , 2024 2024 Citations: 23
Quantum-Inspired Machine Learning Models for Cyber Threat Intelligence SPK Reddy, NS Dey, A SrujanGoud, U Rakshitha International Conference on Intelligent Computing and Big Data Analytics … , 2024 2024 Citations: 1
Lung cancer detection and classification using transfer learning with pre-trained VGG19 convolutional neural networks S Das, G Lavanya, SJ Prakash, NS Dey, J Panuganti, R Poojitha 2023 3rd International Conference on Emerging Frontiers in Electrical and … , 2023 2023 Citations: 7
Automated brain tumor segmentation in mri: An enhanced mask generation approach S Das, NS Dey, M Mounika 2023 7th International conference on I-SMAC (IoT in social, mobile … , 2023 2023 Citations: 3
Serverless computing: architectural paradigms, challenges, and future directions in cloud technology NS Dey, SPK Reddy 2023 7th International Conference on I-SMAC (IoT in Social, Mobile … , 2023 2023 Citations: 13
Hybrid load balancing strategy for cloud data centers with novel performance evaluation strategy NS Dey, HKR Sangaraju International Journal of Intelligent Systems and Applications in Engineering … , 2023 2023 Citations: 29
Energy-Efficiency Optimization in IoT Networks: Algorithms, Techniques, and Case Studies MU Nagavelli, NS Dey, SPK Reddy AIDE-2023 and PCES-2023, 414 , 2023 2023
Comprehensive Analysis of Text Summarization Techniques for Legal Documents R Deepika, S Das, NS Dey, J Panuganti, MR Hussain AIDE-2023 and PCES-2023, 426 , 2023 2023
ACO-Inspired Load Balancing Strategy for Cloud-Based Data Centre with Predictive Machine Learning Approach N Dey, T Gunasekhar, K Purnachand Computers, Materials, & Continua 75 (1), 513 , 2023 2023 Citations: 1
Sentiment extraction and analysis using machine learning tools-survey A Shaik, N Sekhar Dey, K Purnachand, CM Babu IOP Conference Series: Materials Science and Engineering 594 (1), 012022 , 2019 2019 Citations: 5
A comprehensive survey of load balancing strategies using hadoop queue scheduling and virtual machine migration NS Dey, T Gunasekhar IEEE Access 7, 92259-92284 , 2019 2019 Citations: 47
A structured approach for learner centric digital elearning: Vishnu massive online open courses: A cloud based elearning portal NS Dey, KD Ramaiah 2014 IEEE International Conference on MOOC, Innovation and Technology in … , 2014 2014 Citations: 1
Performance analysis of cloud databases handling social networking data N Dey, S Bhattacharya 2013 IEEE International Conference on Cloud Computing in Emerging Markets … , 2013 2013 Citations: 2
Speech and speaker recognition system using artificial neural networks and hidden Markov model NS Dey, R Mohanty, KL Chugh 2012 international conference on communication systems and network … , 2012 2012 Citations: 45
On Road Navigation System Using Spatial and MotionImage Processing for Automatic Navigation System NS Dey, R Mohanty, KL Chugh International Journal of Innovation, Management and Technology 3 (1), 80 , 2012 2012 Citations: 2
Speech and Speaker Recognition System using Artificial Neural Networks and Hidden Markov Model for Automatic Machine Learning NS Dey, P Rao, KL Chugh Journal of Innovation in Computer Science and Engineering 2 (1), 24-28 , 2012 2012
Cloud Based Ranking System on Clustered Databases N Dey, S Bhattacharya 2010
MOST CITED SCHOLAR PUBLICATIONS
A comprehensive survey of load balancing strategies using hadoop queue scheduling and virtual machine migration NS Dey, T Gunasekhar IEEE Access 7, 92259-92284 , 2019 2019 Citations: 47
Speech and speaker recognition system using artificial neural networks and hidden Markov model NS Dey, R Mohanty, KL Chugh 2012 international conference on communication systems and network … , 2012 2012 Citations: 45
Hybrid load balancing strategy for cloud data centers with novel performance evaluation strategy NS Dey, HKR Sangaraju International Journal of Intelligent Systems and Applications in Engineering … , 2023 2023 Citations: 29
A particle swarm optimization inspired global and local stability driven predictive load balancing strategy NS Dey, HKR Sangaraju Indonesian Journal of Electrical Engineering and Computer Science 35 (3), 10 … , 2024 2024 Citations: 23
Serverless computing: architectural paradigms, challenges, and future directions in cloud technology NS Dey, SPK Reddy 2023 7th International Conference on I-SMAC (IoT in Social, Mobile … , 2023 2023 Citations: 13
Lung cancer detection and classification using transfer learning with pre-trained VGG19 convolutional neural networks S Das, G Lavanya, SJ Prakash, NS Dey, J Panuganti, R Poojitha 2023 3rd International Conference on Emerging Frontiers in Electrical and … , 2023 2023 Citations: 7
Sentiment extraction and analysis using machine learning tools-survey A Shaik, N Sekhar Dey, K Purnachand, CM Babu IOP Conference Series: Materials Science and Engineering 594 (1), 012022 , 2019 2019 Citations: 5
Automated brain tumor segmentation in mri: An enhanced mask generation approach S Das, NS Dey, M Mounika 2023 7th International conference on I-SMAC (IoT in social, mobile … , 2023 2023 Citations: 3
Performance analysis of cloud databases handling social networking data N Dey, S Bhattacharya 2013 IEEE International Conference on Cloud Computing in Emerging Markets … , 2013 2013 Citations: 2
On Road Navigation System Using Spatial and MotionImage Processing for Automatic Navigation System NS Dey, R Mohanty, KL Chugh International Journal of Innovation, Management and Technology 3 (1), 80 , 2012 2012 Citations: 2
Quantum-Inspired Machine Learning Models for Cyber Threat Intelligence SPK Reddy, NS Dey, A SrujanGoud, U Rakshitha International Conference on Intelligent Computing and Big Data Analytics … , 2024 2024 Citations: 1
ACO-Inspired Load Balancing Strategy for Cloud-Based Data Centre with Predictive Machine Learning Approach N Dey, T Gunasekhar, K Purnachand Computers, Materials, & Continua 75 (1), 513 , 2023 2023 Citations: 1
A structured approach for learner centric digital elearning: Vishnu massive online open courses: A cloud based elearning portal NS Dey, KD Ramaiah 2014 IEEE International Conference on MOOC, Innovation and Technology in … , 2014 2014 Citations: 1
A NOVEL INTEGRATED FRAMEWORK FOR SECURE IOT-BASED SMART VEHICLE MANAGEMENT USING MACHINE LEARNING AND BLOCKCHAIN FOR PATH PLANNING AND COLLISION AVOIDANCE MV NARAYANA, P PARTHASARADHY, PJ KUMAR, S KIRAN, ... Journal of Theoretical and Applied Information Technology 103 (21) , 2025 2025
YOLO-BASED FEATURE LEARNING WITH RF–XGB ENSEMBLES FOR ROBUST CITRUS LEAF DISEASE DETECTION KV AJAY, MSKB PADMAJA PULICHERLA, DVD P THIRUMOORTHY, ... Journal of Theoretical and Applied Information Technology 103 (21) , 2025 2025
QoS-Aware Deployment and Synchronization of Digital Twins Over Federated Cloud Platforms for Smart Infrastructure Monitoring. MV Narayana, NS Dey, S Shrivastava International Journal of Advanced Computer Science & Applications 16 (8) , 2025 2025
Energy-Efficiency Optimization in IoT Networks: Algorithms, Techniques, and Case Studies MU Nagavelli, NS Dey, SPK Reddy AIDE-2023 and PCES-2023, 414 , 2023 2023
Comprehensive Analysis of Text Summarization Techniques for Legal Documents R Deepika, S Das, NS Dey, J Panuganti, MR Hussain AIDE-2023 and PCES-2023, 426 , 2023 2023
Speech and Speaker Recognition System using Artificial Neural Networks and Hidden Markov Model for Automatic Machine Learning NS Dey, P Rao, KL Chugh Journal of Innovation in Computer Science and Engineering 2 (1), 24-28 , 2012 2012
Cloud Based Ranking System on Clustered Databases N Dey, S Bhattacharya 2010