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Kingsy Grace R.,Sri Ramakrishna Engineering College
Journal of Parallel and Distributed Computing

Data replication techniques are used in data grid to reduce makespan, storage consumption, access latency and network bandwidth. Data replication enhances data availability and thereby increases the system reliability. There are two steps involved in data replication, namely, replica placement and replica selection. Replica placement involves identifying the best possible node to duplicate data based on network latency and user request. Replica selection involves selecting the best replica location to access the data for job execution in the data grid. Various replica placement and selection algorithms are available in the literature. These algorithms measure and analyze different parameters such as bandwidth consumption, access cost, scalability, execution time, storage consumption and makespan. In this paper, various replica placement and selection strategies along with their merits and demerits are discussed. This paper also analyses the performance of various strategies with respect to the parameters mentioned above. In particular, this paper focuses on the dynamic replica placement and selection strategies in the data grid environment. © 2013 Elsevier Inc. All rights reserved. Source

Balasangameshwara J.,Atria Institute of Technology | Raju N.,Sri Ramakrishna Engineering College
Journal of Network and Computer Applications

Due to the emergence of grid computing over the Internet, there is a need for a hybrid load balancing algorithm which takes into account the various characteristics of the grid computing environment. Hence, this research proposes a fault tolerant hybrid load balancing strategy namely AlgHybrid-LB, which takes into account grid architecture, computer heterogeneity, communication delay, network bandwidth, resource availability, resource unpredictability and job characteristics. AlgHybrid-LB juxtaposes the strong points of neighbor-based and cluster based load balancing algorithms. Our main objective is to arrive at job assignments that could achieve minimum response time and optimal computing node utilization. Major achievements include low complexity of proposed approach and drastic reduction of number of additional communications induced due to load balancing. A simulation of the proposed approach using Grid Simulation Toolkit (GridSim) is conducted. Experimental results show that the proposed algorithm performs very well in a large grid environment. © 2011 Elsevier Ltd. All rights reserved. Source

Ramamurthy B.,Sri Ramakrishna Engineering College | Chandran K.R.,PSG College of Technology
Journal of Computer Science

Problem statement: Recently, there has been a huge progress in collection of varied image databases in the form of digital. Most of the users found it difficult to search and retrieve required images in large collections. In order to provide an effective and efficient search engine tool, the system has been implemented. In image retrieval system, there is no methodologies have been considered directly to retrieve the images from databases. Instead of that, various visual features that have been considered indirect to retrieve the images from databases. In this system, one of the visual features such as texture that has been considered indirectly into images to extract the feature of the image. That featured images only have been considered for the retrieval process in order to retrieve exact desired images from the databases. Approach: The aim of this study is to construct an efficient image retrieval tool namely, "Content Based Medical Image Retrieval with Texture Content using Gray Level Co-occurrence Matrix (GLCM) and k-Means Clustering algorithms". This image retrieval tool is capable of retrieving images based on the texture feature of the image and it takes into account the Preprocessing, feature extraction, Classification and retrieval steps in order to construct an efficient retrieval tool. The main feature of this tool is used of GLCM of the extracting texture pattern of the image and k-means clustering algorithm for image classification in order to improve retrieval efficiency. The proposed image retrieval system consists of three stages i.e., segmentation, texture feature extraction and clustering process. In the segmentation process, preprocessing step to segment the image into blocks is carried out. A reduction in an image region to be processed is carried out in the texture feature extraction process and finally, the extracted image is clustered using the k-means algorithm. The proposed system is employed for domain specific based search engine for medical Images such as CT-Scan, MRI-Scan and X-Ray. Results: For retrieval efficiency calculation, conventional measures namely precision and recall were calculated using 1000 real time medical images (100 in each category) from the MATLAB Workspace database. For selected query images from the MATLAB-Image Processing tool Box-Workspace Database, the proposed tool was tested and the precision and recall results were presented. The result indicates that the tool gives better performance in terms of percentage for all the 1000 real time medical images from which the scalable performance of the system has been proved. Conclusion: This study proposed a model for the Content Based Medical Image Retrieval System by using texture feature in calculating the Gray Level Co Occurrence matrix (GLCM) from which various statistical measures were computed in order to increasing similarities between query image and database images for improving the retrieval performance along with the large scalability of the databases. © 2012 Science Publications. Source

Christy Mano Raj J.S.,Salem College | Ebenezer Jeyakumar A.,Sri Ramakrishna Engineering College
Solar Energy

A new method of tracking the maximum power point (MPP) of a photovoltaic (PV) module exploiting the effects of the inherent characteristic resistances of the photovoltaic cells is proposed in this paper. An analysis of the mathematical model of the IV characteristic of the PV module revealed a possibility of estimating the MPP from its characteristic parameters such as the open circuit voltage (Voc), short circuit current (Isc), series resistance (Rse) and the shunt resistance (Rsh). The first stage of estimation process, for obtaining the voltage at the MPP, was facilitated by the effects of the series and shunt resistance on the IV characteristic of the PV module and the second stage of estimation process was facilitated by the combined process of the first stage of estimation and the condition for extracting the maximum power from the mathematical model of the pv characteristic of the PV module. The estimated voltage at the MPP in the second stage of estimation was found very close to the true MPP. The effectiveness of tracking the MPP with the proposed method has closely matched with the true MPP. This was validated by the results obtained through simulations and experiments. An analysis of the effects of degradation on the performance of the proposed technique showed that the performance was excellent during the first few years and with the update of characteristic resistances in the proposed algorithm the performance was found to be almost invariant. The successful experimental results obtained with a 100Wp PV module indicate that the technique can be favourably implemented for standalone PV power systems. © 2014 Elsevier Ltd. Source

Shanmugasundram R.,Sri Ramakrishna Engineering College | Yadaiah N.,JNTUH College of Engineering
IEEE/ASME Transactions on Mechatronics

This paper presents design and digital implementation of a fuzzy controller for achieving improved performance of Brushless dc (BLDC) servomotor drive. The performance of fuzzy and PID controller-based BLDC servomotor drives is investigated under different operating conditions such as change in reference speed, parameter variations, load disturbance, etc. BLDC servomotors are used in aerospace, instrumentation systems, space vehicles, electric vehicles, robotics, and industrial control applications. In such applications, conventional controllers like P, PI, and PID are being used with the BLDC servomotor drive control systems to achieve satisfactory transient and steady-state responses. However, the major problem associated with the conventional PID controller is that the tuned gain parameters obtained for such BLDC servomotor drive control systems do not yield better transient and steady-state responses under different operating conditions such as parameter variations, load disturbances, etc. In this paper, design and implementation of fuzzy controller is presented and its performance is compared with PID controller to show its capability to track the error and usefulness of fuzzy controller in control applications.©1996-2012 IEEE. Source

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