Conference Papers
Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506
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Item Assessment of objective functions under mobility in RPL(Springer Verlag, 2018) Sanshi, S.; Jaidhar, J.Due to the technological advancement in Low-power and Lossy Network (LLN), the sensor node mobility has become a basic requirement. Routing protocol designed for LLN must ensure certain requirements in a mobile environment such as reliability, flexibility, scalability to name a few. To meet the needs of LLN, Internet Engineering Task Force (IETF) released the standard IPv6 Routing Protocol for LLNs (RPL). RPL depends on Objective Function (OF) to select optimized routes from source to destination. However, the standard did not specify which OF to use. In this study, performance analysis of different OFs such as Objective Function zero (OF0), Energy-based Objective Function (OFE), Delay-Efficient Objective Function (OFDE), and Minimum Rank with Hysteresis Objective Function (MRHOF) is carried out under different mobility models, which makes this study unique. The metrics used to measure the performance are latency, packet delivery ratio (PDR), and power consumption. Simulation results demonstrate that under different mobility models, MRHOF achieved better results in terms of PDR and power consumption, while OFDE shows better results in terms of latency compared to other OFs. © Springer Nature Singapore Pte Ltd. 2018.Item Mobility aware routing protocol based on DIO message for low power and lossy networks(Springer Verlag service@springer.de, 2020) Sanshi, S.; Jaidhar, C.D.Mobility support has become a crucial requirement for many of the Low power and Lossy Networks applications, and designing an efficient mobility aware routing protocol towards this end has become an important research topic. In this paper, a Mobility Aware Routing Protocol for Low power and Lossy Networks (MARPL) that updates the Preferred Parent Node information soon after it receives the DIO message has been proposed. In the proposed approach, the Mobile Node is aware of its mobility and updates the PPN information without waiting for the route expiration time. To measure the effectiveness of the proposed MARPL, simulation works were carried out on a Contiki-based Cooja simulator for different mobility models. The obtained simulation results showed that the proposed MARPL performed better compared with the standard RPL for healthcare applications. © Springer Nature Switzerland AG 2020.Item Cardiovascular Diseases Divination using Artificial Neural Network with Ensemble Models(Institute of Electrical and Electronics Engineers Inc., 2023) Pabitha, B.; Sanshi, S.; Karthik, N.Health is wealth, but nowadays, wealth is health, where humans keep running their day-to-day activities without caring about their health for various reasons. Every human being in this world suffers from one or other diseases. Recently, cardiovascular diseases like heart attacks are prevalent in all age groups. Addressing cardiovascular diseases is essential before the disease reaches a crucial stage. Nowadays, artificial intelligence algorithms have been used to detect diseases in their early stages. In this piece of writing, a model of an artificial neural network is utilised to analyze, detect and predict the likelihood of cardiovascular disease in the early stages. In this proposed work, feed forward propagation, forward the input data to learn and map the relationships between inputs and outputs, and backward propagation is used to reduce the errors in the data. Further, an ensemble learning stacked model is used to achieve high accuracy in the prediction of diseases. To verify the correctness of the model, ensemble learning to stack is executed with three different models, namely Model 1, Model 2, and Model 3, with varying sets of feature selections. The experiment results show an accuracy rate of 93% in their predictions. © 2023 IEEE.Item Spatial Dynamics for Identification of Individuals through Gait and Other Locomotion Activities(Institute of Electrical and Electronics Engineers Inc., 2024) Anusha, R.; Sanshi, S.Gait, the pattern of walking, has been extensively studied and various methods have been developed to use it as a biometric for individual recognition. Despite this, the potential to identify individuals through running videos has not been thoroughly explored. The paper introduces a novel method that expands the feature-based approach for identifying individuals based on their running style. This work focuses on extracting the mutual information and location specific metric from the key gait poses of subjects in the testing and training datasets. Later on, the assignment of a testing sample to the training sample is accomplished using the proposed classification method. The experiments are conducted on KTH, OU-ISIR A, and Weizmann database. The efficiency of this method is demonstrated by the obtained experimental results. © 2024 IEEE.Item Performance Evaluation of Wireless Health and Remote Monitoring Network Throughput Under Varying Conditions Using NetSim(Institute of Electrical and Electronics Engineers Inc., 2024) Pabitha, B.; Vani, V.; Sanshi, S.The Wireless Body Area Network (WBAN), organized in/out of the human body region to form Wireless enabled Health and Remote monitoring Network (WHRN), is trending on the medical platform for efficient diagnosis by the physician without the patient's physical visit. This network is framed with different biological sensors in the regional area of the human body to sense unlike biological signals promptly. Wearable WHRN, like smart watches and mobile phones, can notify people about stress, heart rate, and other physiological nods. The technology developed enhances the treatment for the patient, but the security of the information transmitted over different mediums is vulnerable. WHRN is simulated using the NetSim standard tool. Network performance metrics and their plots are analyzed using various encryption standards to provide data transmission and diagnosis security. Security is the primary concern for physiological data sensed and transmitted over different mediums. © 2024 IEEE.Item Multi-factor Authentication and Data Integrity for WBAN Using Hash-Based Techniques(Springer Science and Business Media Deutschland GmbH, 2024) Pabitha, B.; Vani, V.; Sanshi, S.; Karthik, N.In recent days, a wireless body area network (WBAN) has been developed as part of the Internet of Things (IoT) with sensors and actuators in three different modes, building its network, i.e., in-body sensors, wearable sensors, and on-body sensors. The doctor’s access the data recorded and monitored by the sensor embedded in the patient to treat critical situations immediately. Maintaining data integrity and guarding against threats is necessary to secure sensitive patient information. Several people have proposed schemes for authenticating data access through formal and informal verification. In this research work, we carry out multi-factor authentication extensively using zero-knowledge proofs. The anomaly detection of the sensors is detected using machine learning algorithms, which help tune the sensors to their correct working conditions. The work aims to concentrate on sensor working conditions promptly and to handle attacks like masquerade, forgery, and key escrow attacks. To assess whether performance metrics are superior in computing cost, storage overhead, and communication overhead, utilize the BAN logic tool. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.