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Chennai, India

Sheela Shantha Kumari P.K.,HIGH-TECH | Duraipandian,Vellammal Engg College | Cyril,Drmgr University
International Journal of Applied Engineering Research

Using cloud storage, users can remotely store their data and enjoy the ondemand high-quality applications and services from a shared pool of configurable resources available over the cloud, without the need for the client to maintain local data storage. However in cloud computing, since the data is stored anywhere across the globe, the client organization has less control over the stored data. The proposed application or software will provide data integrity verification by using Merkle Hash algorithm and provide encryption/decryption using AES algorithm. With the character of low maintenance, cloud computing provides an efficient solution for sharing resources available in the cloud. But sharing data in a multi-owner group has to provide security to the data stored in order to prevent unauthorized access by data users. In this paper, we propose secure data storage with enhanced third party auditing scheme for dynamic multi owner groups in the cloud. Finally Load balancing scheme is used to retrieve the data from cloud in order to minimize overhead of cloud server. © Research India Publications. Source

Kanimozhi A.,Sathyabama University | Cyril Raj V.,Drmgr University
International Journal of Engineering and Technology

The main goal of this research is to build an enhanced learning environment for e-learner using the cognitive architecture ACT-R(Adaptive Control of Thought-Rational) [7,8]. This proposed new intelligent learning environment is applied to manage and monitor the dynamic behavior of the learner and capture the learner's emotional status like active, high arousal, displeasure and sleepy mood. This intelligent architecture will modulate the learning content based on the emotional status of the learner. So that learner's emotional status is also included in E-learning which is similar to the pedagogical method where the teacher can understand the general mood of learners and modulate the method of delivery. The model that we have developed for the subject System Software has proved that the learner's outcome is better in our model than some of the other existing models. We have also included learner's behavioral history as feedback to our system for the further improvement of the learning process. Source

Vijaya Prakash A.M.,Drmgr University | Gurumurthy K.S.,University Visvesvaraya College of Engineering
World Academy of Science, Engineering and Technology

In Image processing the Image compression can improve the performance of the digital systems by reducing the cost and time in image storage and transmission without significant reduction of the Image quality. This paper describes hardware architecture of low complexity Discrete Cosine Transform (DCT) architecture for image compression[6]. In this DCT architecture, common computations are identified and shared to remove redundant computations in DCT matrix operation. Vector processing is a method used for implementation of DCT. This reduction in computational complexity of 2D DCT reduces power consumption. The 2D DCT is performed on 8x8 matrix using two 1-Dimensional Discrete cosine transform blocks and a transposition memory [7]. Inverse discrete cosine transform (IDCT) is performed to obtain the image matrix and reconstruct the original image. The proposed image compression algorithm is comprehended using MATLAB code. The VLSI design of the architecture is implemented Using Verilog HDL. The proposed hardware architecture for image compression employing DCT was synthesized using RTL complier and it was mapped using 180nm standard cells. The Simulation is done using Modelsim. The simulation results from MATLAB and Verilog HDL are compared. Detailed analysis for power and area was done using RTL compiler from CADENCE. Power consumption of DCT core is reduced to 1.027mW with minimum area[1]. Source

Visu P.,Vel Technology Drrr And Drsr Technical University | Janet J.,Drmgr University | Kannan E.,Vel Technology Drrr And Drsr Technical University | Koteeswaran S.,Vel Technology Drrr And Drsr Technical University
European Journal of Scientific Research

Routing in the adhoc network is major critical issue which desires the performance of wireless networks. Providing optimal routing in wireless network is more complicated than wired networks due to many pitfalls like limited power, less bandwidth. Therefore, the routing protocol in wireless environment requires many additional considerations such as optimal energy management, clustering, providing congestion free communication, offering scalability, maintaining the Quality of Service (QoS). There are many traditional and advanced routing protocols are proposed in the past few years, which may further subdivided as active, pro-active and reactive protocols. And the same also divided as Traditional, Flat, Hybrid, Hierarchical routing protocols. In this paper, proposed energy efficient routing protocols using Artificial Bee Colony (ABC) based routing algorithm. The proposed method is implemented in NS2 and the performance of proposed algorithm is discussed in terms of response time and throughput. © 2012 EuroJournals Publishing, Inc. Source

Doss S.,St Peters University | Jeyaraj J.,Drmgr University
Journal of Computer Science

Recent days, research in wireless network becomes major area for the past few decades. In wireless routing many routing methods such as table driven, source driven; many characteristics such as reactive routing, proactive routing; many routing algorithms such as dijikstra's shortest path, distributed bell-man ford algorithm are proposed in the literature. For effective wireless routing, the recent ant colony optimization proves better result than the existing methodologies. The ant colony optimization is a swarm intelligence technique which widely used for combinatorial optimization problems such as travelling salesman, network routing, clustering. The ant colony optimization is a real time routing protocol which offers highly reliable and optimal routing for both single path and multi path routing. As the ant is a small tiny mobile agent, providing security is critical issue. In this study, a secured ant colony optimization using Chinese remainder theorem is proposed. © 2013 Science Publications. Source

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