Faculty Publications
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Publications by NITK Faculty
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Item Multiple aggregator multiple chain routing protocol for heterogeneous wireless sensor networks(2013) Harichandan, P.; Jaiswal, A.; Kumar, S.Wireless sensor nodes are deployed to gather useful information from the field but their constraint on battery power leads us to think about energy efficient routing protocols so that they can operate over longer periods of time. We study the advantages of having multiple chains in a network with each chain's topmost node (called the aggregator) collecting the data from the nodes beneath it and transmitting it to the sink. In the proposed scheme, a chain in each region works as PEGASIS. We also study how considering heterogeneity in the network can improve the lifetime of a network by a significant period. We assume that a fraction of the nodes in the network possess additional energy. We show by simulations that the introduction of heterogeneity into the network results in a greater lifetime, compared to those of the classical data aggregation schemes, with the duration increasing with the amount of additional energy considered. © 2013 IEEE.Item An Energy-Efficient Clustering Algorithm for Edge-Based Wireless Sensor Networks(Elsevier B.V., 2016) Venkateswarlu, K.M.; Kandasamy, A.; Chandrasekaran, K.To employee clustering algorithms in multi-hop data forwarding mechanism, Hot-spot problem will cause unbalanced energy dissipation among the cluster heads in the network. Unequal clustering technique promotes even energy dissipation only in inter-cluster communications not in intra-cluster communication. An Energy-efficient Clustering Algorithm (EECA) is introduced to avoid these problems in edge-based wireless sensor networks. The main aim of the presented algorithm is to avoid hot-spot problem by balancing uniform energy utilization among networked cluster heads. EECA constructs uneven size clusters in different levels to enable uniform energy expenditure among cluster heads. Data delivery is one of the important and unavoidable energy consuming operation in any sensor networks. To balance energy consumption load among data transmission routes, a multi-hop data forwarding protocol is introduced. Here, source node selects a relaying node who has minimum hop count to base station with more energy reserves and relayed less number of packets. Extensive experimental results prove that the presented algorithm overcome the congestion problem in the network by uniform distribution of energy consumption and enhances network's lifetime. © 2016 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license.Item Algorithms for minimizing the receiver interference in a wireless sensor network(Institute of Electrical and Electronics Engineers Inc., 2016) Shetty D, D.P.; Lakshmi, M.P.Limiting Interference between the nodes in a Wireless Sensor Network (WSN) is of considerable importance for energy-efficiency of the network. Minimizing the interference in a WSN minimizes the overall energy consumption of the network by reducing the number of conflicting transmissions. We consider Receiver interference minimization problem. Two types of interference are defined in a WSN, namely Sender interference and Receiver interference. In this paper we consider the Receiver interference problem, where the objective is to minimize the maximum Receiver interference. The problem of minimizing the maximum Receiver interference is proved to be NP-hard. In this paper we propose two algorithms named MinMax-RIP and a modified version of the same to minimize the maximum Receiver interference in a WSN. We evaluate the performance of our algorithms through simulation. We then consider the interference minimization problem in a broadcast network. We propose MinMax-BRIP algorithm for optimal range assignment which gives minimum total Receiver interference for connectivity predicate Broadcast. © 2016 IEEE.Item Range assignment with k-power levels in a Wireless Sensor Network(Institute of Electrical and Electronics Engineers Inc., 2018) Lakshmi, M.P.; Shetty D, S.D.Energy minimization in Wireless Sensor Network (WSN) has gained the attention of several researchers because of its diverse applications in the real world. Optimization in power assignment increases the lifetime of a network. Available sensor nodes operate with a set of discrete power levels in which each sensor node can be assigned with one of the power levels from the given set. Dual power assignment problem was studied by researchers in which only two power levels are available for assignment in a WSN. As the Dual power assignment problem is proved to be NP-hard, several approximation algorithms were proposed. We consider k-power level assignment problem for a given set of sensor nodes with the objective of minimizing the total power assigned to the network provided each sensor node is assigned a power level only from the given set. We propose two heuristic algorithms; one is based on Euclidean Minimum Spanning Tree (MST) and the other is an Incremental Heuristic which runs in polynomial time. We present the simulation results to compare and analyze the proposed algorithms. We also conduct the experiments for various number of nodes by varying the number of power levels. © 2018 IEEE.Item Improved Algorithm for Minimum Power 2-Connected Subgraph Problem in Wireless Sensor Networks(Institute of Electrical and Electronics Engineers Inc., 2018) Lakshmi, M.; Shetty D, D.A Wireless Sensor Network (WSN) consists of small sensor nodes which communicate with each other using wireless radio channel and are used to monitor certain environmental parameters. Since the nodes are powered by a small battery of limited capacity, it is important to minimize the energy consumption in a WSN. By using an appropriate topology the energy utilization of the network can be minimized which results in an increased lifetime of a WSN. In practice, the transmission power of a sensor node can be tuned to obtain a required topology that satisfies certain connectivity constraints and this problem is known as Range Assignment Problem. For a given network, a reduced topology is constructed satisfying some connectivity constraints like k-connectivity, bounded diameter etc. Fault tolerance addresses the issue of node or link failure which aims at k-connectivity so that, the network has at least k vertex disjoint paths between any two nodes of the network. With the motivation of achieving fault tolerant network with minimum transmission energy, we consider Minimum power 2-connected subgraph (MP2CS) problem which is proved to be NP-hard. A polynomial time heuristic is proposed in this paper for the MP2CS problem and simulation is performed to compare with the existing algorithm. © 2018 IEEE.Item Mesh WSN data aggregation and face identification in fog computing framework(IEEE Computer Society help@computer.org, 2019) Sahith, S.R.; Rudraraju, S.R.; Negi, A.; Suryadevara, N.K.This work aims to aggregate data from various sensors in a mesh topology based Wireless Sensor Network (WSN). It analyzes this data using fog computing framework to trigger alerts. The WSN consists of nodes with several sensors like temperature sensor, potentiometer and light emitting diode connected with radio communication module XBee. The sensor nodes are connected in mesh topology for better reliability and using ZigBee protocol mechanism. The Fog gateway node collects the sensor data from several sensor nodes. The WSN also includes Pi Camera and passive infrared sensor augmented with Philips Hue Lights. Hue Light gives a visual indication of motion detection, using ON/OFF states. Pi camera captures image whenever any motion is detected. The captured images are used for face recognition by applying Eigenfaces method. The AI algorithm is applied on the aggregated temperature sensor data, at the Fog node level, to determine the adaptive threshold. If the temperature data from any sensor node is above the threshold value an alert message is triggered. The proposed system is run continuously for data collection and the functionality of the system is tested with various inputs and the results are encouraging. © 2019 IEEE.Item An Efficient Optimized Neural Network System for Intrusion Detection in Wireless Sensor Networks(Modern Education and Computer Science Press, 2024) Sanshi, S.; Vatambeti, R.; Revathi, V.; Rahman, S.Z.In the realm of wireless network security, the role of intrusion detection cannot be overstated in identifying and thwarting malicious activities within communication channels. Despite the existence of various intrusion detection system (IDS) approaches, challenges persist in terms of accurate classification and specification. Consequently, this article introduces a novel and innovative approach, the African Vulture-based Modular Neural System (AVbMNS), to address these issues. This research aims to detect and categorize malicious events in wireless networks effectively. The methodology begins with preprocessing the dataset and extracting relevant features. These extracted features are then subjected to a novel training technique to enhance the detection and classification of network attacks. The integration of African Vulture optimization significantly enhances the detection rate, leading to more precise attack identification. The research's effectiveness is demonstrated through validation using the NSL-KDD dataset, with impressive results. The performance analysis reveals that the developed model achieves a remarkable 99.87% detection rate and 99.92% accuracy when applied to the NSL-KDD dataset. Furthermore, the outcomes of this novel model are compared with existing approaches to gauge the extent of improvement. The comparative assessment affirms that the developed model outperforms its counterparts, underscoring its effectiveness in addressing the challenges of intrusion detection in wireless networks. © 2024, Modern Education and Computer Science Press. All rights reserved.