2. Conference Papers
Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/1/7
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Item Modified MapReduce framework for enhancing performance of graph based algorithms by fast convergence in distributed environment(2014) Singhal, H.; Ram Mohana Reddy, GuddetiThe amount of data which is produced is huge in current world and more importantly it is increasing exponentially. Traditional data storage and processing techniques are ineffective in handling such huge data [10]. Many real life applications require iterative computations in general and in particular used in most of machine learning and data mining algorithms over large datasets, such as web link structures and social network graphs. MapReduce is a software framework for easily writing applications which process large amount of data (multi-terabyte) in parallel on large clusters (thousands of nodes) of commodity hardware. However, because of batch oriented processing of MapReduce we are unable to utilize the benefits of MapReduce in iterative computations. Our proposed work is mainly focused on optimizing three factors resulting in performance improvement of iterative algorithms in MapReduce environment. In this paper, we address the key issues based on execution of tasks, the unnecessary creation of new task in each iteration and excessive shuffling of data in each iteration. Our preliminary experiments have shown promising results over the basic MapReduce framework. The comparative study with existing solutions based on MapReduce framework like HaLoop, has also shown better performance w.r.t algorithm run time and amount of data traffic over Hadoop Cluster. � 2014 IEEE.Item Resource Provisioning Framework for IoT Applications in Fog Computing Environment(2018) Rakshith, G.; Rahul, M.V.; Sanjay, G.S.; Natesha, B.V.; Ram Mohana Reddy, GuddetiThe increasing utility of ubiquitous computing and dramatic shifts in the domain of Internet of Things (IoT) have generated the need to devise methods to enable the efficient storage and retrieval of data. Fog computing is the de facto paradigm most suitable to make efficient use of the edge devices and thus shifting the impetus from a centralized cloud environment to a decentralized computing paradigm. By utilizing fog resources near to the edge of the network, we can reduce the latency and the overheads involved in the processing of the data by deploying the required services on them. In this paper, we present resource provisioning framework which provisions the resources and also manages the registered services in a dynamic topology of the fog architecture. The results demonstrate that using fog computing for deploying services reduces the total service time. � 2018 IEEE.Item Recent trends in content-based video copy detection(2010) Roopalakshmi, R.; Ram Mohana Reddy, GuddetiVideo copy detection is an interesting & challenging problem, as it is becoming increasingly important with the growing rate of illegal digital media and huge piracy issues. Therefore, in the present era of Internet &Multimedia technologies,the existence of ubiquitous digital videos, has led to the requirement of robust video copy detection techniques, for content management and copyright protection. In this paper, an overview of content based video copy detection (CBVCD) is presented along with the different state-of-the-art techniques used for video feature/ signature description. This article also explores the future key directions and highlights the research challenges that need to be addressed in the CBVCD paradigm. � 2010 IEEE.Item Recent advances and future potential of computer aided diagnosis of liver cancer on computed tomography images(2011) Megha, P.A.; Ram Mohana Reddy, GuddetiLiver cancer has been known as one of the deadliest diseases. It has become a major health issue in the world over the past 30 years and its occurrence has increased in the recent years. Early detection is necessary to diagnose and cure liver cancer. Advances in medical imaging and image processing techniques have greatly enhanced interpretation of medical images. Computer aided diagnosis (CAD) systems based on these techniques play a vital role in the early detection of liver cancer and hence reduce death rate. The concept of computer aided diagnosis is to provide a computer output as a second opinion in analysis of liver cancer. It assists radiologist's image interpretation by improving accuracy and consistency of radiological diagnosis and also by reducing image analysis time. The main objective of this paper is to provide an overview of recent advances in the development of CAD systems for analysis of liver cancer. Medical imaging system based on computer tomography will be focused as it is particularly suitable for detecting liver tumors. The paper begins with introduction to liver tumors and medical imaging techniques. Then the key CAD techniques developed recently for liver tumor detection, classification, case-based reasoning based on image retrieval and 3D reconstruction are presented. This article also explores the future key directions and highlights the research challenges that need to be addressed in the development of CAD system which can help the radiologist in improving the diagnostic accuracy. � Springer-Verlag 2011.Item Projection and interaction with ad-hoc interfaces on non-planar surfaces(2013) Dere, K.S.; Ram Mohana Reddy, GuddetiProjector-based display systems have been used in area of computer interaction as Ad-hoc interface in recent time. The mobile hand-held projectors are becoming more popular. Many human centric user interfaces with the human wearable computer are being developed. Most of such system uses daily objects for projection and the interaction. But most of ignores the fact that these object surfaces are not planar. Hence such interfaces suffers from the distortion due to non-planar projection surface. Besides this projection quality also suffers from the radiometric distortion as well. Further more the interaction proposed with such interfaces bound to the planar surface only. Hence this paper is targeted to address the geometric distortion free projection of and interaction with such interfaces on non planar surfaces. Kinect is used as depth sensor for 3D scenario acquisition. We use imageper warping to mesh from Kinect. We use colored fingertip gloves for interaction. Here our system aims any day to day object surface for distortion free projection such as human body, curved wall, room corners, curtain's and many more objects. � 2013 IEEE.Item Primary education for the specially-abled(2013) Chandra, S.; Sagar, M.; Rout, P.; Khattri, P.; Domanal, S.; Ram Mohana Reddy, GuddetiTechnology can support the children who require special needs, who if given the proper training and opportunity, can compete on a basis of equality with their peers. This should be the basic philosophy of a programmer who designs programs, standards for programs, or evaluation of programs. Proper education for these children will lead to enhancing their capability to lead a dignified life and also help them to earn a square meal. Technology is needed to teach them and hence the necessity can clearly be seen for further research and development in this field. In addition to software being used as teaching tools at schools and at-home, the learning process should be more interesting so that child should feel engaged. A daily routine, not only a syllabus/homework, using technologies such as text to speech conversion and image morphology is needed to both help them understand concepts of classroom syllabus and motivate them to learn more at home as specially-abled children need to be given enough motivation, as well as time, to succeed. The system developed proves to be useful to specially-abled children to memorize rhymes, recognize common sounds (like that of animals) as well as develop haptic abilities using a game like interface. � 2013 IEEE.Item Predicting an optimal sparse matrix format for SpMV computation on GPU(2014) Neelima, B.; Ram Mohana Reddy, Guddeti; Raghavendra, P.S.Many-threaded architecture based Graphics Processing Units (GPUs) are good for general purpose computations for achieving high performance. The processor has latency hiding mechanism through which it hides the memory access time in such a way that when one warp (group of 32 threads) is computing, the other warps perform memory bound access. But for memory access bound irregular applications such as Sparse Matrix Vector Multiplication (SpMV), memory access times are high and hence improving the performance of such applications on GPU is a challenging research issue. Further, optimizing SpMV time on GPU is an important task for iterative applications like jacobi and conjugate gradient. However, there is a need to consider the overheads caused while computing SpMV on GPU. Transforming the input matrix to a desired format and communicating the data from CPU to GPU are non-trivial overheads associated with SpMV computation on GPU. If the chosen format is not suitable for the given input sparse matrix then desired performance improvements cannot be achieved. Motivated by this observation, this paper proposes a method to chose an optimal sparse matrix format, focusing on the applications where CPU to GPU communication time and pre-processing time are nontrivial. The experimental results show that the predicted format by the model matches with that of the actual high performing format when total SpMV time in terms of pre-processing time, CPU to GPU communication time and SpMV computation time on GPU, is taken into account. The model predicts an optimal format for any given input sparse matrix with a very small overhead of prediction within an application. Compared to the format to achieve high performance only on GPU, our approach is more comprehensive and valuable. This paper also proposes to use a communication and pre-processing overhead optimizing sparse matrix format to be used when these overheads are non trivial. � 2014 IEEE.Item Performance analysis of Ensemble methods on Twitter sentiment analysis using NLP techniques(2015) Kanakaraj, M.; Ram Mohana Reddy, GuddetiMining opinions and analyzing sentiments from social network data help in various fields such as even prediction, analyzing overall mood of public on a particular social issue and so on. This paper involves analyzing the mood of the society on a particular news from Twitter posts. The key idea of the paper is to increase the accuracy of classification by including Natural Language Processing Techniques (NLP) especially semantics and Word Sense Disambiguation. The mined text information is subjected to Ensemble classification to analyze the sentiment. Ensemble classification involves combining the effect of various independent classifiers on a particular classification problem. Experiments conducted demonstrate that ensemble classifier outperforms traditional machine learning classifiers by 3-5%. � 2015 IEEE.Item Parallelized K-Means clustering algorithm for self aware mobile Ad-hoc networks(2011) Thomas, L.; Manjappa, K.; Annappa, B.; Ram Mohana Reddy, GuddetiProviding Quality of Service (QoS) in Mobile Ad-hoc Network (MANET) in terms of bandwidth, delay, jitter, throughput etc., is critical and challenging issue because of node mobility and the shared medium. The work in this paper predicts the best effective cluster while taking QoS parameters into account. The proposed work uses K-Means clustering algorithm for automatically discovering clusters from large data repositories. Further, iterative K-Means clustering algorithm is parallelized using Map-Reduce technique in order to improve the computational efficiency and thereby predicting the best effective cluster. Hence, parallel K-Means algorithm is explored for finding the best effective cluster containing the hops which lies in the best cluster with the best throughput in self aware MANET. Copyright � 2011 ACM.Item Parallel implementation of 3D modelling of indoor environment using Microsoft Kinect sensor(2013) Manojkumar, P.; Ram Mohana Reddy, Guddeti3D visual modelling of indoor space will not only provide the detailed knowledge about the environment but also rich contextual information of the existing objects. In this paper, we propose a parallel implementation of 3D modelling of indoor environment using Microsoft Kinect depth camera. 3D maps are generated by Simultaneous Localization And Mapping [SLAM] technique. These 3-D maps will be more useful in Context aware and in Robotics applications. Iterative Closest Point [ICP] with initial guess by RANSAC is used for pair alignment. Many tasks of pair registration are parallelised using OpenMP and the performance evaluation of both sequential and parallel implementations are compared. Simulation results demonstrate that OpenMP based parallel implementation has achieved a speedup factor of 3.7. � 2013 IEEE.