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ENADL: Towards Performance Improvement of IoT Networks Using Deep Learning-Based Node Fault Prediction
Shraddha Tripathi;Faheem Nizar;Om Jee Pandey;Tushar Sandhan;Rajesh M. Hegde
IEEE Transactions on Reliability
Year: 2025 | Early Access Article |
The Internet of Things (IoT) has grown explosively with wireless technology integration. Several IoT applications require high data throughput, low data transmission latency, and high data gathering reliability. Since, the IoT network (IoTN) is generally dynamic and utilizes a multi-hop data transmission scheme for such applications, the throughput, latency, and network lifetime tend to degrade as...Show More
MalaNet: A Small World Inspired Neural Network for Automated Malaria Diagnosis
Shubham Dwivedi;Kartikeya Pandey;Kumar Shubham;Om Jee Pandey;Achyut Mani Tripathi;Tushar Sandhan;Rajesh M Hegde
IEEE Transactions on Artificial Intelligence
Year: 2025 | Early Access Article |
In this work, a novel neural network architecture called MalaNet is proposed for the detection and diagnosis of malaria, an infectious disease that poses a major global health challenge. The proposed neural network architecture is inspired by small-world network principles, which generally involve the introduction of new links. A small-world neural network is realized by establishing new connectio...Show More
A Lightweight Causal Sound Separation Model for Real-Time Hearing Aid Applications
Harsh Mishra;Mahendra K. Shukla;Priyanshu;Som Dengre;Yashveer Singh;Om Jee Pandey
Real-time audio processing is crucial for hearing aid IoT applications, where low latency and efficiency are paramount. State-of-the-art models like Demucs achieve high signal-to-distortion ratio (SDR) but are unsuitable for real-time use due to their noncausal nature and high latency. This letter introduces a lightweight causal model tailored for real-time hearing aid applications, designed to mi...Show More
SINR-Delay Constrained Node Localization in RIS-Assisted Time-Varying IoT Networks Using ML Frameworks
Vikash Kumar Bhardwaj;Gagan Mundada;Omm Prakash Sahoo;Mahendra K. Shukla;Om Jee Pandey
IEEE Transactions on Network and Service Management
Year: 2025 | Early Access Article |
Node localization in time-varying Internet of Things (IoT) networks is an essential problem due to increased delay and poor Signal-to-Interference plus Noise Ratio (SINR) at the Base Station (BS). To improve the received signal strength at the BS, Reconfigurable Intelligent Surface (RIS) has recently been used between transmitter and receiver. Additionally, novel phase prediction methods and optim...Show More
Medical Sensor Data Security: A DNN Framework for SOP Prediction in Two-Way Relay NOMA Systems
Astitva Kamble;Harsh Dalwadi;Mahendra K. Shukla;Om Jee Pandey;Vishal Krishna Singh
Securing medical sensor data are imperative due to the susceptibility of wireless transmissions to eavesdropping. In this letter, we focus on improving the security of two-way communication in medical networks by investigating deep neural networks (DNN) for two-way (TWR) relay nonorthogonal multiple access (NOMA) systems. Utilizing a decode-and-forward (DF) relay and considering both maximum ratio...Show More
A Two-way Synchronization Method for Molecular Bio-nanosensor Networks using Truncated Lévy Distribution
Siva Rama Krishna Ayaluru;Chandrakant Shrivastava;Satish K. Tiwari;Nilay Pandey;Gaurav Sharma;Om Jee Pandey
2024 IEEE 8th International Conference on Information and Communication Technology (CICT)
Year: 2024 | Conference Paper |
Bio-nanosensors on their own have limited computational capabilities, but when working collaboratively within nanonetworks, they can perform relatively complex tasks such as sensing, computation, storage, and actuation. Molecular communication is a promising paradigm for enabling such molecular nanonetworks, making it essential to understand certain aspects of molecular communication channels for ...Show More
Node Fault Prediction Assisted Small-World IoT Networks Using ML Frameworks: Towards Performance Improvement
2024 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS)
Year: 2024 | Conference Paper |
The rapid growth of the Internet of Things (IoT) networks has led to the deployment of large-scale networks, enabling seamless connectivity and data exchange among various devices. To manage the complexity and ensure efficient communication in these expansive networks, adopting suitable network architecture becomes crucial. Small-world networks, characterized by a high Average Clustering Coefficie...Show More
A Novel Routing Protocol over Time-Varying IoT Network Using RTS/CTS Framework
Neha Sharma;Prajjwal Pandey;Aryan;Prateek Rathore;Om Jee Pandey
2024 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS)
Year: 2024 | Conference Paper |
In the context of 6G IoT networks, distributed computing has become a critical enabler for seamless communication across diverse sectors, such as smart manufacturing, intelligent transportation, healthcare, and defense. Many of these applications involve mobile IoT devices (IoDs) that change locations dynamically, requiring robust and efficient multi-hop data transmission frameworks. Selecting the...Show More
Heuristic-based Multicasting Utilizing Network Coding over a Multi-Hop Wireless Mesh Network
Neha Sharma;Prateek Rathore;Mahendra K. Shukla;Om Jee Pandey
2024 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS)
Year: 2024 | Conference Paper |
Multicasting over a multi-hop wireless mesh network is a challenging issue that recently received less attention. Various applications, such as distance learning, telemedicine, web radio, and online conferencing, require the same information to be sent to multiple recipients. In these applications, the destination nodes are often far from the source, necessitating the design of a multi-hop multica...Show More
Throughput Maximization in Delay-Critical and Energy-Aware SW-UAV-WNs Using Q-Learning
Sreenivasa Reddy Yeduri;Neha Sharma;Om Jee Pandey;Linga Reddy Cenkeramaddi
Unmanned aerial vehicles (UAVs) are getting significant attention from both researchers and the industry due to their wide range of applications. Remote sensing is one such application, in which UAVs are deployed to sense remote areas and transmit the data to a ground station for processing. However, due to the mobility and limited transmission range of UAVs, data transfer requires multiple hops. ...Show More
TDRA: Transformer-Based Deep Recurrent Architecture for Automatic Modulation Classification Pertinent to Intelligent-Reflecting-Surface-Assisted Internet of Things Networks
Debbarni Sarkar;Yogita;Satyendra Singh Yadav;Linga Reddy Cenkeramaddi;Om Jee Pandey
IEEE Internet of Things Journal
Cited by: Papers (2)
In wireless networks, automatic modulation classification (AMC) is crucial for enabling intelligent signal demodulation, thereby enhancing the system’s adaptability across various applications. Concurrently, the rapid expansion of the Internet of Things (IoT) necessitates scalable network solutions with limited power consumption. Moreover, addressing the Nonline-of-Sight (NLoS) effects in IoT netw...Show More
Energy-Efficient and Latency-Aware Data Routing in Small-World Internet of Drone Networks
Sreenivasa Reddy Yeduri;Sindhusha Jeeru;Om Jee Pandey;Linga Reddy Cenkeramaddi
Recently, drones have attracted considerable attention for sensing hostile areas. Multiple drones are deployed to communicate and coordinate sensing and data transfer in the Internet of Drones (IoD) network. Traditionally, multi-hop routing is employed for communication over long distances to increase the network’s lifetime. However, multi-hop routing over large-scale networks leads to energy imba...Show More
Maximizing Coverage and Energy Conservation in B5G Networks Using Hexagonal Tiling to Deploy FT-S2ES
Vaibhav Tiwari;Chandrasen Pandey;Satyendra Singh Yadav;Diptendu Sinha Roy;Om Jee Pandey;Linga Reddy Cenkeramaddi
Edge Servers (ESs) enhance the efficiency and reliability of modern Beyond Fifth-Generation (B5G) network systems by reducing latency, boosting responsiveness, and optimizing network usage. From an industry standpoint, the optimal positioning of ESs is critical to enhancing coverage reach while reducing potential conflicts with neighboring servers, guaranteeing consistent and reliable user access....Show More
Optimal Routing Protocol in LPWAN Using SWC: A Novel Reinforcement Learning Framework
Naga Srinivasarao Chilamkurthy;Shaik Abdul Hakeem;Satish K. Tiwari;Anirban Ghosh;Linga Reddy Cenkeramaddi;Om Jee Pandey
Low-power wide-area network (LPWAN) has emerged as a dominating communication technology that offers low-power and wide coverage for the Internet of Things (IoT) applications. However, the direct data transmission approach has a limited network lifetime. Even multihop data transmission experiences many difficulties including high data latency, poor bandwidth utilization, and reduced data throughpu...Show More
Space-Air-Ground Integrated Networks: Spherical Stochastic Geometry-Based Uplink Connectivity Analysis
Yalin Liu;Hong-Ning Dai;Qubeijian Wang;Om Jee Pandey;Yaru Fu;Ning Zhang;Dusit Niyato;Chi Chung Lee
By integrating the merits of aerial, terrestrial, and satellite communications, the space-air-ground integrated network (SAGIN) is an emerging solution that can provide massive access, seamless coverage, and reliable transmissions for global-range applications. In SAGINs, the uplink connectivity from ground users (GUs) to the satellite is essential because it ensures global-range data collections ...Show More
A Novel Resource Management Framework for Blockchain-Based Federated Learning in IoT Networks
Aman Mishra;Yash Garg;Om Jee Pandey;Mahendra K. Shukla;Athanasios V. Vasilakos;Rajesh M. Hegde
At present, the centralized learning models, used for IoT applications generating large amount of data, face several challenges such as bandwidth scarcity, more energy consumption, increased uses of computing resources, poor connectivity, high computational complexity, reduced privacy, and large latency towards data transfer. In order to address the aforementioned challenges, Blockchain-Enabled Fe...Show More
OptRISQL: Toward Performance Improvement of Time-Varying IoT Networks Using Q-Learning
Neha Sharma;Venkata Saai Praneeth Thota;Yuvaraj Tankala;Shraddha Tripathi;Om Jee Pandey
In order to support the recent explosive growth in the applications of Internet of Things (IoT), networking technologies are evolving, resulting in high data throughput, low-latency data transfer, and improved lifetime of Internet of Things Devices (IoDs). These technologies work fairly for static conditions as the devices have fixed locations. However, in several practical IoT networks, including...Show More
STCNN: Combining SMOTE-TOMEK With CNN for Imbalanced Classification of Alzheimer's Disease
The most frequent cause of dementia worldwide is Alzheimer's disease (AD). Progressing from mild to severe, it gradually deteriorates, making independent tasks more challenging. Due to the aging population and the timing of diagnoses, its prevalence has exceeded expectations. Existing models for categorizing cases include magnetic resonance imaging (MRI), cognitive testing, and medical history. Ho...Show More
Energy-Efficient and Latency-Aware Blockchain-Enabled Federated Learning for Edge Networks
Deepali Kushwaha;Manan Kalavadia;Vinayaka Hegde;Om Jee Pandey
The introduction of blockchain in federated learning can initiate a federation of trustworthy devices by validating the local model. However, challenges arise due to the blockchain framework’s increased latency and energy consumption. This brief proposes a blockchain-enabled federated learning framework that jointly optimizes latency and energy consumption. The proposed method is evaluated over th...Show More
A Computationally Efficient and QoS-Aware Data Offloading Framework for Biased Fog Networks
Fog computing alleviates the cloud-centric limitations of Internet of Things (IoT). However, in the dynamic landscape of fog computing, the uneven distribution of workload among fog nodes emerges as a substantial obstacle to both, data latency and network profit. To mitigate workload imbalances, data packet offloading offers a twofold benefit. The offloading fog node leverages latency satisfaction...Show More
Socially Aware Network Clustering for Throughput Maximization in Mobile Wireless Sensor Networks
Mobile sensors, such as smart wearables, autonomous cars, cognitive healthcare devices, and intelligent drones, draw great attention due to their ability to provide a wide-range of services. Hence, a consistent connection of each sensor node to the access point is a crucial requirement to obtain high data throughput in such mobile wireless sensor networks (MWSN). Data interference among such dense...Show More
An Unified Data Compression Framework in an IoT Network: Towards Performance Improvement
2023 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS)
Year: 2023 | Conference Paper |
The Internet of Things (IoT) has fundamentally changed the way we interact worldwide, however, the sheer volume of data it generates is enormous. Effectively handling this extensive data is a critical task in IoT networks, as transmitting it over the network consumes significant energy. Therefore, the need for data compression at the sensor layer and gateways directly improves the data transmissio...Show More
Parkinson's disease (PD) is a neurodegenerative condition characterized by intricate behavior and neuronal function changes. The intricacy of these changes makes it difficult to identify PD in its early stages. Experts frequently use manual evaluations of patients' movements, including drawing, writing, walking, tremors, facial expressions, and speech, although this process is laborious and prone ...Show More
Small-World Inspired Neural Network (SW-NN) for an Effective and Accurate Diagnosis of Diabetes
2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT)
Year: 2023 | Conference Paper |
As the use of artificial intelligence in medical diagnosis is growing, the need for enhanced efficacy is becoming paramount. By merging the robustness of neural networks with the distinctive attributes of small-world networks (SWN), the possibility arises for even greater levels of accuracy with maintaining good generalizability. This work presents a novel approach for diagnosing diabetes using a ...Show More
Human activity recognition (HAR) is the process of identifying a person’s activities accurately. It is possible by placing sensors on the subject’s body and obtaining data from a variety of high-dimensional physiological signals. Recently, sensors such as an accelerometer and gyroscopes have been incorporated directly into wearable devices, making activity identification fairly straightforward. Hi...Show More
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