Published in 2015
C.R.Kavitha
The biologically inspired Neural Networks are computer programs designed to simulate the way in which the
human brain processes information. Neural network gather their knowledge by detecting the patterns and relationships in
data and learn through experience. Neural network was not only used for classification of physiologically active substances
but also for solving the quantitative structure activity relationship problem. An important part of drug design and
discovery is to understand the structure-activity relationship of chemical molecules. Without this understanding, drug
design and discovery becomes an intractable, blind search problem. The goal of drug discovery in this study was to learn
structural pattern associated with Monoamine Oxidation both in high and low inhibition.
Drug Design, Drug Discovery, Monoamine Oxidation, Neural Network, Pattern Recognition
M.Marimuthu, A.Kannammal
Image encryption plays a crucial role in the field of information security. Most of the existing image encryption
techniques have some kind of security flaws and performance related issues. This paper proposes three level of security;
Image scrambling is first level security and second level security is chaotic based image encryption. Third level security is
achieved using random LSB based watermarking. Fingerprint is considered as original image and iris is considered as
chaotic image. Fingerprint and iris are scrambled; In order to obtain encrypted image, scrambled iris and fingerprint
image values are substituted using XoR operation. Finally encrypted image is embedded in face image. The decryption is
reverse process of encryption process and it restores the image to its original form. The proposed approach is evaluated
using standard security measures and statistical methods; result shows that proposed approach performs better than
existing method in the cryptography domain.
Biometrics, Fingerprints, Image encryption, Image scrambling, Watermarking
M.Sumathi, S.Krishnaveni
In this paper we explore the energy efficient approaches inside data centers from the site and IT infrastructure
perspective incorporating Cloud networking from the access network technologiesand network equipment point of view to give
a comprehensive prospect toward achieving energyefficiency of Cloud computing. Traditional and Cloud data centers would by
compared to figureout which one is more recommended to be deployed. Virtualization as heart of energy efficientCloud
computing that can integrates some technologies like consolidation and resourceutilization has been introduced to prepare a
background for implementation part. Finallyapproaches for Cloud computing data centers at operating system and especially
data centre levelare presented and Green Cloud architecture as the most suitable green approach is described indetails. In the
experiment segment we modeled and simulated Face book and studied the behavior in terms of cost and performance and
energy consumption to reach a most appropriatesolution.
energy efficiency, cloud computing, data centre
G.Satheesh, N.Suresh
Huge volume of detailed personal data is regularly collected and sharing of these data is proved to be
beneficial for data mining application. Such data include shopping habits, criminal records, medical history, credit
records etc .On one hand such data is an important asset to business organization and governments for decision making
by analyzing it .On the other hand privacy regulations and other privacy concerns may prevent data owners from sharing
information for data analysis. In order to share data while preserving privacy data owner must come up with a solution
which achieves the dual goal of privacy preservation as well as accurate clustering result. Trying to give solution for this
we implemented vector quantization approach piecewise on the datasets which segmentize each row of datasets and
quantization approach is performed on each segment using K means which later are again united to form a transformed
data set. Some details are presented which tries to finds the optimum value of segment size and quantization parameter
which gives optimum in the tradeoff between clustering utility and data privacy in the input dataset.
Data privacy, cluster, data mining, clustering, classification
K.R Palanisamy, A.Murugan
The risk of failure is an important property of a Grid resource, especially when scheduling jobs optimally in relation to
resources so as to achieve a business objective. However, in Grid computing, user-centric scheduling algorithms ignore the risk
factor and mostly address the minimization of the cost of the resource allocation, or the overall deadline by which the job must be
executed completely. Therefore, we propose a novel user-centric scheduling algorithm for scheduling Bag of Tasks (BoT)
applications. The algorithm, which aims to meet user requirements, takes into account the risk of failure, the cost of resources and
the job deadline. With this in mind, through simulation, we demonstrate that the algorithm provides a near-optimal solution for
minimizing the cost of executing BoT jobs. Also, we show that the execution time of the proposed algorithm is very low, and is
therefore suitable for solving scheduling problems in real-time.
Grid Computing , job scheduling, Resource management
V.Kalaivani, N.Keerthi
Cloud computing is still a rather new field, which is not yet entirely defined. As a result, many interesting research
problems exist, often combining different research areas such as databases, distributed systems or operating systems. This paper
focuses data storage Consistency Rationing as a new transaction paradigm, which not only allows defining the consistency
guarantees on the data instead of at transaction level, but also allows for automatically switching consistency guarantees at runtime. We present a number of techniques that make the system dynamically adapt the consistency level by monitoring the data
and/or gathering temporal statistics of the data. The last part of the paper is concerned with XQuery as a unified programming
model for the cloud and, in particular, the missing capabilities of XQuery for windowing and continuous queries. XQuery is able to
run on all layers of the application stack, is highly optimizable and parallelizable, and is able to work with structured and semi
structured data.
Cloud computing, data storage, XQuery, transactions
E.Elayaraja, K.Gopinath
Multidimensional data has been a challenge for data analysis because of the inherent sparsely of the points. In this
paper, we have present a novel data preprocessing technique called shrinking which optimizes the inherent characteristic of
distribution of data. This data reorganization concept can be applied in many fields such as pattern recognition, data clustering
and signal processing. Then, as an important application of the data shrinking preprocessing, we propose a shrinking-based
approach for multi-dimensional data analysis which consists of three steps: data shrinking, cluster detection, and cluster
evaluation and selection. The process of data shrinking moves data points along the direction of the density gradient, thus
generating condensed, widely-separated clusters. The data-shrinking and cluster-detection steps are conducted on a sequence
of grids with different cell sizes. The clusters detected at these scales are compared by a cluster-wise evaluation measurement,
and the best clusters are selected as the final result. This paper shows that this approach can effectively and efficiently detect
clusters in both low- and high-dimensional spaces.
Clustering, Shrinking algorithm, data processing, multi dimensional data
M.Karthika, R.Rathika
Over the past few years, a range of new Media Access Control (MAC) protocols have been proposed for use in wireless
networks. Medium access control (MAC) protocols provide a means to nodes to access the wireless medium efficiently and collision
free to the best of their ability. MAC layer protocols allow a group of users to share a communication medium in a fair, stable, and
efficient way. MAC protocols set defined rules to force distributed users/nodes to access the wireless medium in an orderly and
efficient manner. MAC layer is sub layer of Data Link Layer involves the functions and procedures necessary to transfer data
between two or more nodes of the network. It is responsible for error correction of anomalies occurring in the physical layer,
framing, physical addressing, and resolving conflicts occurring in number of nodes to access the channel.
Medium access control, Collision Avoidance, Carrier Sense Multiple Access
T.Arunprakasam, Dr.M.Gunasekaran
Task scheduling plays a crucial role in optimizing resource utilization and enhancing performance in cloud computing
environments. Efficient scheduling algorithms help manage workloads, minimize execution time, balance resource allocation,
and ensure Quality of Service (QoS) compliance. This paper provides a comprehensive study aboubt task scheduling techniques,
various applications of cloud task scheduling, ranging from big data processing to IoT integration and high-performance
computing. Furthermore, we analyze widely used scheduling tools such as CloudSim, iFogSim, and WorkflowSim. Performance
evaluation metrics, including makespan, load balancing, and energy efficiency, are discussed to highlight key factors influencing
scheduling decisions. Finally, we outline current research challenges and future directions, emphasizing the need for adaptive
and intelligent scheduling mechanisms to enhance cloud computing efficiency
Task Scheduling, Cloud Computing, Resource Allocation, Heuristic and Metaheuristic Algorithms, AI-based Scheduling, Performance Optimization, Load Balancing, QoS-Aware Scheduling