Papers by Sangappa Biradar
Ad hoc networks are a new wireless networking paradigm for mobile nodes. It enabling devices to c... more Ad hoc networks are a new wireless networking paradigm for mobile nodes. It enabling devices to create and join networks on-the-fly anywhere, anytime. The military, emergency rescue, disaster relief operations are the main applications of ad hoc networks. Unlike traditional wireless networks, ad hoc networks do not rely on any fixed infrastructure. Instead, hosts rely on each other to keep the network connected. In this paper we compared single path and multipath routing protocols over mobile ad hoc wireless networks using ns-2 simulator. Simulation results are presented by varying number of source, pause time and node mobility.
Lecture Notes in Networks and Systems, 2020
The multihop wireless network, especially mobile adhoc network, has gained popularity in various ... more The multihop wireless network, especially mobile adhoc network, has gained popularity in various contexts that may include independent rescue system, connecting network at the edge in Internet and sub-network in upcoming global Internet of the cyber-physical system. The future-generation network systems will be a kind of software-defined network, where the system will have a possibility of choosing and adopting various routing protocol depending upon the context. This paper discusses the advantages of multihop wireless communication and investigates the performance behaviors of AODV and DSR with different Quality of Services parameters by proposing an enhanced energy model in the base node configuration.
Indian Journal of Computer Science and Engineering, 2021
Wireless networks in general can consume a lot of energy and incur losses if they do not have the... more Wireless networks in general can consume a lot of energy and incur losses if they do not have the right protocols to properly add packets to the destination. Similarly, if the connectivity of the network nodes is different, its resource losses will be higher. Thus, the network will quickly disconnect and cause very high losses. As well as wireless nodes, this sends various data, so energy losses are high. This proposed method-CDLN-cluster distance-based data forwarding and optimal leader election using fuzzy inference in wireless network-is designed to take care of all these and formulate routing accordingly. In this method, the cluster set is formed and the main leader and assistant leaders are selected. Thus, when the main leader is disconnected, the assistant cluster acts to prevent network loss. Because the transmission ranges in this network are different sizes, the cluster set will have different members. These cluster sets are formed in a fuzzy inference mode and set up with precise leaders and routing, thus reducing energy costs, network life time and the number of dead nodes. It can also be seen in the output that the network lasts longer.
Procedia Computer Science, 2016
The advancement into smart mobile devices has accelerated the adoption of various pervasive compu... more The advancement into smart mobile devices has accelerated the adoption of various pervasive computing based ubiquitous applications, where Mobile Adhoc Network (MANET) has extended its usability from hard core military applications to civil society applications. The success for routing requires a robust computational mechanism of routing based on the collaborative framework of energy (i.e. battery power), signal strength and zonal routings. The paper presents a framework of novel routing technique in order to jointly address the problem pertaining to routing overhead and energy drainage among the mobile nodes. Different from conventional simulation mechanism, the paper presents a communication district with inclusion of auxiliary nodes for minimizing the overhead during the routing process. The outcome of the proposed study shows significant reduction in routing overhead along with energy efficiency as compared to existing AODV and DSDV protocols.
International Journal of Computer Applications, 2014
Routing is one of the crucial phenomenons in any networking principles. However, formulation and ... more Routing is one of the crucial phenomenons in any networking principles. However, formulation and operation of the routing protocols are not so easy in dynamic topologies like mobile adhoc network. Since past decade there has been an evolution of various routing protocols in mobile adhoc network community that are claimed to be efficient by various researchers, it became important to understand their effectiveness. Hence, the proposed study chooses to understand and scale the effectiveness of the existing routing protocols in mobile adhoc network from routing overhead minimization and adoption of signal strength in enhancing route behavior. The study has discussed some of the significant contributions and interesting outcomes with support of discussion on precise research gaps of the existing literatures.
International Journal of Computer Networks and Applications, 2021
Mobile Ad-hoc Networks (MANETs) are a type of wireless network that allows people gaining more ub... more Mobile Ad-hoc Networks (MANETs) are a type of wireless network that allows people gaining more ubiquitous, as seen by their exponential rise over the last decade. They are made up of mobile nodes that connect remotely. The network's efficiency is highly dependent on the routing protocol used. This provided an opportunity for academics to design routing methods capable of increasing network efficiency. The literature focuses on building algorithms for route selection based on either the energy level or the distance between source and destination. However, there are other elements that affect the network's data transmission efficiency. Thus, this study work offers a unique Golden Eagle Optimizer-based Trusted Ad-hoc On-Demand Distance Vector (GEO-TAODV) routing protocol that optimizes route selection on the basis of criteria such as priority queue, trust degree, delay, hop count, and energy level. The trustworthiness of potential routes is determined using a consensus network model. By satisfying the reward expectations of the given multi-objective function, the suggested GEO method assists in determining the most efficient and trusted route for data transfer. Thus, the GEO-TAODV routing protocol assures that data is transmitted efficiently via a trusted path. The proposed GEO-TAODV protocol is simulated and compared to existing AODV and AODV-version 2 routing methods.
MECS, Apr 17, 2014
Image restoration deals with recovery of a sharp image from a blurred version. This appr... more Image restoration deals with recovery of a sharp image from a blurred version. This approach can be defined as blind or non-blind based on the availability of blur parameters for deconvolution. In case of blind restoration of image, blur classification is extremely desirable before application of any blur parameters identification scheme. A novel approach for blur classification is presented in the paper. This work utilizes
the appearance of blur patterns in frequency domain. These features are extracted in wavelet domain and a feed forward neural network is designed with these features. The simulation results illustrate the high efficiency of our algorithm.
International Journal of Tomography and Simulation, May 2014
The aim of image restoration techniques is to recover the original image from a degraded observat... more The aim of image restoration techniques is to recover the original image from a degraded observation. One of the most common degradation phenomena in images is defocus blur. In case of blind image restoration accurate estimation of defocus blur parameters is required for deblurring of defocused images. This paper proposes a novel technique for estimating the parameter of defocus blur. It uses Curvelet transform to find the features of the blurred images and a radial biases neural network to estimate the blur parameter. This work is tested on different barcode images with varying degrees of defocus blur. The simulation results of proposed method are found more accurate than the existing methods.
International Journal of Computer Engineering Science , Oct 16, 2014
Classification of multiclass images is very enviable for different recognition. This is affected ... more Classification of multiclass images is very enviable for different recognition. This is affected by many factors such as noise, blur, low illumination, complex background, occlusion etc. Noise is one of the major factors causing degradation of the classification performance. This paper proposes an efficient method for classification of multiclass object images which are corrupted by Gaussian noise. A wavelet transform based denoising scheme by thresholding the wavelet coefficients namely NeighShrink has been utilized to eliminate too many wavelet coefficients that might contain noise information and selecting useful coefficients. This work shows robustness of proposed method of multiclass object classification over the spatial domain denoising and feature extraction method for classification.
ETPub, Dec 31, 2013
The goal of image restoration is to improve a given image in some predefined sense. Resto... more The goal of image restoration is to improve a given image in some predefined sense. Restoration attempts to recover an image by modelling the degradation function and applying the inverse process. Motion blur is a common type of degradation which is caused by the relative motion between an object and camera. Motion blur can be modeled by a point spread function consists of two parameters angle and length. Accurate estimation of these parameters is required in case of blind restoration of motion blurred images. This paper compares different approaches to estimate the parameters of a motion blur namely direction and length directly from the observed image with and without the influence of Gaussian noise. These estimated motion blur parameters can then be used in a standard non-blind deconvolution algorithm. Simulation results compare the performance of most common motion blur estimation methods.
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Papers by Sangappa Biradar
the appearance of blur patterns in frequency domain. These features are extracted in wavelet domain and a feed forward neural network is designed with these features. The simulation results illustrate the high efficiency of our algorithm.
the appearance of blur patterns in frequency domain. These features are extracted in wavelet domain and a feed forward neural network is designed with these features. The simulation results illustrate the high efficiency of our algorithm.