N V K Ramesh

Bio: N V K Ramesh is an academic researcher from K L University. The author has contributed to research in topics: Ad hoc On-Demand Distance Vector Routing & Routing protocol. The author has an hindex of 1, co-authored 5 publications receiving 7 citations.

TAD-HOC Routing Protocol for Efficient VANET and Infrastructure-Oriented Communication Network

Abstract: Intelligent Transportation System (ITS) is a critical factor for Vehicular Ad hoc Networks (VANET). Even though VANET belongs to the class of Mobile Ad hoc Network (MANET), none of the MANET routing protocol applies to VANET. VANET network is dynamic, due to increased vehicle speed and mobility. Vehicle mobility of VANET affects conventional routing algorithm performance, which deals with the dynamicity of the network node. The evaluation of the existing research stated that Ad hoc On-Demand Distance Vector (AODV) is an effective MANET protocol to adopt network changes for significant resource utilization and also provides effective adaptation in the network change. Due to the effective performance of the AODV protocol, it is considered as an effective routing protocol for VANET. This paper proposed an ad hoc TROPHY (TAD-HOC) routing protocol for the VANET network for increasing efficiency and effective resource utilization of the network. To improve the overall performance, ad hoc network is combined with Trustworthy VANET ROuting with grouP autHentication keYs (TROPHY) protocol. The proposed TAD-HOC protocol transmits data based on time demand in the VANET network with the desired authentication. Results of the proposed approach show the increased performance of the VANET network with packet delay, transmission range, and end-to-end delay. The comparative analysis of the proposed approach with I-AODV, AODV-R, and AODV-L shows that the proposed TAD-HOC exhibited effective performance.

Performance Analysis of Traffic Types in AODV Routing Protocol for VANETs

Abstract: Vehicular Ad-hoc Networks (VANETs) are the intelligent system that allows vehicles to act like nodes, where there is a starting node, end node and any vehicle between these nodes can act as an intermediate node. Every node has high mobility and fast-changing topology. Each node can sense its coverage area to make available services related to traffic control. To make a connection between nodes routing is done with the help of routing protocol. The reactive routing protocol called Ad-Hoc On-demand Distance Vector (AODV) is the most advanced and commonly used in topology-based routing. Nodes (i.e. Vehicles) are fast moving thus the connection between nodes breaks frequently. This paper, we are going to analyze the Quality of Service (QoS) parameters for UDP and TCP traffic types. This paper is presenting a normal AODV routing protocol to analyze QoS parameters that are Delay and Throughput. We are using Linux based platform software's and doing result analysis using Network Simulator-2 (NS-2).

Identification of Tomato Crop Diseases Using Neural Networks-CNN

Abstract: Agriculture is the backbone of Indian economy as more than 60% of Indian population depend directly or indirectly on agriculture, But the GDP share of agriculture to Economy is comparatively less to the amount of people involved in the sector (20% according to economic survey 2021). One of the major threats to agriculture is the effect of pests, insects, bacteria, fungus. It is important to control the growth of the cultivated crop to ensure minimal losses. Various diseases can affect and attack the leaves of the crop from the time it sprouts until it is ripe and sold. As a result, the primary aim of this study is to solve the problem of tomato leaf disease using simple techniques. The main aim of the proposed work is to find a solution to the problem of detecting tomato leaf disease with a simple method and limited resources while obtaining high results comparable to other techniques. This paper majorly targets on the Tomato crop. The proposed model achieved an accuracy of 94% on average.

Attitude, Position and Velocity determination using Low-cost Inertial Measurement Unit for Global Navigation Satellite System Outages

Abstract: Over the few years civilian and military applications are maneuvering with multi-sensor Unmanned Aerial Vehicles (UAV). The aim of this paper is to improve autonomous UAV positioning by using Inertial measurement unit (IMU) and Global Navigation Satellite System (GNSS) is considered. The positional accuracy of UAV is limited to GNSS signal blockage. The advancements in micro electro mechanical systems (MEMS) helps to design low-cost IMU with meter-level accuracy in positioning. The estimation of attitude, position and velocity measurements are determined from a nine degree of freedom Arduino embedded IMU sensor. The Low-cost IMU sensor has been tested under static condition and then a dynamic movement of sensor is observed under moving base-line conditions on February 2nd 2020 at Koneru Lakshmaiah Education Foundation (KLEF). In this paper, covariance filters are implemented to eliminate the gyro bias and accelerometer bias for improving attitude determination of IMU navigation system. The positioning from IMU sensor is derived using standard strap-down inertial navigation system (SINS) formulation. The position error from SINS indicates that IMU sensor is able to perform well with maximum position error of 5 meters and 2.5 meters for static and dynamic environments respectively. The outcome of this work would be useful for integration of navigation sensors using kalman filter based advanced techniques for UAV applications.

Prevention of Fire Accidents in Running Trains Using GSM Technology

Abstract: Any crisis circumstance can be better dealt with by quickly announcing its event. Crisis times requests quick arrangements. Time is the parameter that makes all the difference. To have a moment and compelling arrangement we should have a successful framework close by. Our sole target in doing this task is to construct such powerful fire ready framework where the framework quickly perceives the littlest of disparities in the typical progression of things and cautions the concerned individuals of the separate association. It is considered that anything which emits smoke beyond a threshold temperature as a Fire accident. What makes this project an ever-exploring idea is the novelty in the scheme of explosions that are happening all-around. Characteristics of a system whose purpose is to alert the officials when the ammonium nitrate is emitted from the containers can be different from the system whose purpose is to detect a short out. It is an utmost necessity to build a system that finds its relevance in maximum of the situations. The proposed framework contains a circuit which will efficiently control the fire shock which are happening in running trains time and again.

Hybrid Genetic Firefly Algorithm-Based Routing Protocol for VANETs

Abstract: Vehicular Adhoc Networks (VANETs) are used for efficient communication among the vehicles to vehicle (V2V) infrastructure. Currently, VANETs are facing node management, security, and routing problems in V2V communication. Intelligent transportation systems have raised the research opportunity in routing, security, and mobility management in VANETs. One of the major challenges in VANETs is the optimization of routing for desired traffic scenarios. Traditional protocols such as Adhoc On-demand Distance Vector (AODV), Optimized Link State Routing (OLSR), and Destination Sequence Distance Vector (DSDV) are perfect for generic mobile nodes but do not fit for VANET due to the high and dynamic nature of vehicle movement. Similarly, swarm intelligence routing algorithms such as Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) routing techniques are partially successful for addressing optimized routing for sparse, dense, and realistic traffic network scenarios in VANET. Also, the majority of metaheuristics techniques suffer from premature convergence, being stuck in local optima, and poor convergence speed problems. Therefore, a Hybrid Genetic Firefly Algorithm-based Routing Protocol (HGFA) is proposed for faster communication in VANET. Features of the Genetic Algorithm (GA) are integrated with the Firefly algorithm and applied in VANET routing for both sparse and dense network scenarios. Extensive comparative analysis reveals that the proposed HGFA algorithm outperforms Firefly and PSO techniques with 0.77% and 0.55% of significance in dense network scenarios and 0.74% and 0.42% in sparse network scenarios, respectively.

Hybrid Genetic Firefly Algorithm-Based Routing Protocol for VANETs

Abstract: Vehicular Adhoc Networks (VANETs) are used for efficient communication among the vehicles to vehicle (V2V) infrastructure. Currently, VANETs are facing node management, security, and routing problems in V2V communication. Intelligent transportation systems have raised the research opportunity in routing, security, and mobility management in VANETs. One of the major challenges in VANETs is the optimization of routing for desired traffic scenarios. Traditional protocols such as Adhoc On-demand Distance Vector (AODV), Optimized Link State Routing (OLSR), and Destination Sequence Distance Vector (DSDV) are perfect for generic mobile nodes but do not fit for VANET due to the high and dynamic nature of vehicle movement. Similarly, swarm intelligence routing algorithms such as Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) routing techniques are partially successful for addressing optimized routing for sparse, dense, and realistic traffic network scenarios in VANET. Also, the majority of metaheuristics techniques suffer from premature convergence, being stuck in local optima, and poor convergence speed problems. Therefore, a Hybrid Genetic Firefly Algorithm-based Routing Protocol (HGFA) is proposed for faster communication in VANET. Features of the Genetic Algorithm (GA) are integrated with the Firefly algorithm and applied in VANET routing for both sparse and dense network scenarios. Extensive comparative analysis reveals that the proposed HGFA algorithm outperforms Firefly and PSO techniques with 0.77% and 0.55% of significance in dense network scenarios and 0.74% and 0.42% in sparse network scenarios, respectively.

Reliable Group of Vehicles (RGoV) in VANET

Abstract: Nowadays vehicles on the roads can communicate using a special type of wireless network called Vehicular Ad-hoc Networks (VANETs). It has been demonstrated by the researchers that because of the unique features such as high density of vehicles and frequent change of network topology, VANETs are not supported by the traditional routing protocols. The routing consistency of such highly dynamic networks must be taken into account in VANETs as communication links are disintegrated in VANETs more often than Mobile ad-hoc Networks (MANETs). The nature of VANET communication can bring extreme routing overhead to the network, therefore to increase network performance, the overhead issue must be tackled. The proposed protocol is focused on reducing the overhead to get the improved PDR performance of the network. The improvement is achieved by permitting communication amongst only those nodes which are considered reliable in terms of availability and geographical position. The reliability factor simply reduces unnecessary nodes from the communication process and selects a set of reliable nodes that are discovered with the help of clustering technique throughout the routing process. Simulation experiments using the network simulator are presented to demonstrate the efficacy of the proposed protocol. The results show that the proposed protocol has enhanced network performance effectively compared to prior approaches.

Improving AODV Routing Protocol for Image Transmission Over Mobile Video Sensor Networks

Abstract: Wireless Sensor Networks (WSNs) have become extremely popular for sensing, collecting, and transmitting data across different environments. In particular, the AODV protocol is widely used to improve the behavior of WSNs in various applications. A bottleneck in the protocol's performance is the amount of data that need to be moved between different nodes. This bottleneck becomes evident in applications based on multimedia contents, such as images or videos, in which huge chunks of data need to be delivered over long distances. In this article, we propose a new method to enhance the performance of the AODV protocol. Simulation results show that the proposed method improves the performance of the AODV protocol for image-based applications. The technique increases the quality of the delivered images, extends the network's lifetime, and reduces the delay and the network overhead associated with providing such images.

Performance Assessment and Modeling of Routing Protocol in Vehicular Ad Hoc Networks Using Statistical Design of Experiments Methodology: A Comprehensive Study

Abstract: The performance assessment of routing protocols in vehicular ad hoc networks (VANETs) plays a critical role in testing the efficiency of the routing algorithms before deployment in real conditions. This research introduces the statistical design of experiments (DOE) methodology as an innovative alternative to the one factor at a time (OFAT) approach for the assessment and the modeling of VANET routing protocol performance. In this paper, three design of experiments methods are applied, namely the two-level full factorial method, the Plackett–Burman method and the Taguchi method, and their outcomes are comprehensively compared. The present work considers a case study involving four factors namely: node density, number of connections, black hole and worm hole attacks. Their effects on four measured outputs called responses are simultaneously evaluated: throughput, packet loss ratio, average end-to-end delay and routing overhead of the AODV routing protocol. Further, regression models using the least squares method are generated. First, we compare the main effects of factors resulted from the three DOE methods. Second, we perform analysis of variance (ANOVA) to explore the statistical significance and compare the percentage contributions of each factor. Third, the goodness of fit of regression models is assessed using the adjusted R-squared measure and the fitting plots of measured versus predicted responses. VANET simulations are implemented using the network simulator (NS-3) and the simulator of urban mobility (SUMO). The findings reveal that the design of experiments methodology offers powerful mathematical, graphical and statistical techniques for analyzing and modeling the performance of VANET routing protocols with high accuracy and low costs. The three methods give equivalent results in terms of the main effect and ANOVA analysis. Nonetheless, the Taguchi models show higher predictive accuracy.