Homomorphic encryption based data security on federated cloud computing

Anitha R. and Vijayakumar V.

Cloud computing usage has increased rapidly in both industries and in research. In recent days as the data grows rapidly, in order to meet the business needs federated cloud is adopted. In federated cloud, as the data is stored and processed away from the user and the cloud service provider, privacy and integrity of the data plays a crucial role. This paper proposes a practical and efficient method for providing security to the data stored at the federated cloud environment using homomorphic techniques. This method provides security by storing the encrypted data in the cloud. The cipher key which is generated for encrypting the data plays a major role. This paper explores important aspects within this context and examines the role of metadata in data security which improves the performance in a secured manner. The proposed novel homomorphic based key distribution protocol is the key area under focus. This proposed work aims to promote the use of homomorphism in multi-clouds due to its ability to reduce security risks using the enhanced modified feistel technique.

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Intrusion detection model using integrated clustering and decision trees

Ranita Pal and Sumaiya Thaseen

This paper proposes a hybrid technique for intrusion detection model using K-means clustering, attribute selection and decision tree. K-means clustering is a very simple and convenient clustering method when it comes to grouping anomalies and the different attack types in network traffic. An enhanced mechanism is developed using the Cluster center initialization algorithm for k-means clustering and decision trees using the entropy method. After the clustering is done, attribute subset selection is done using entropy method and final classification of attack categories is done using decision trees. It works in two modes: online and offline. Offline mode works on the sample data which is processed to obtain the rule set of the decision tree. The data from the online mode is then compared against those rules to determine their category and identify the intrusions in the packet.

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An insight on reputation based incentive scheme and throughput feedback routing in MANET’s

Christy Jackson, V. Vijayakumar, Subramaniyaswamy V. and Anusooya G.

A Dynamic wireless network which is composed without any actual infrastructure is a mobile ad-hoc network (MANET). Every potential node in the network deports as a router. These mobile networks are much more vulnerable than wired networks because of their restricted physical security, power constraints, network topology which keeps altering dynamically, and due to improper centralized administration. This paper portrays few attacks on each of OSI’s network layer. It also confines some of the attacks faced by MANET. These attacks include packet drop, flooding, black hole, link spoofing, and wormhole. The intention of this paper is to survey the attacks on mobile ad-hoc networks and routing protocols.

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Capacity predictor with varying pricing scheme and interoperablity decision in a bursting situation for cloud computing environemnt

N. S. Gowri Ganesh and A. Rajiv Kannan

The usage of the cloud computing services is increasing rapidly across all the domains, thereby inducing the cloud service providers to increase their underlying cloud resource capacity. If service providers keep on increasing the capacity, it may not be an optimal utilization of resources. Since one of the main characteristics of cloud is optimal utilization of resources, we provide an analysis method, to aid both cloud service provider and cloud service consumer that both are benefited from the cloud. Our first approach is to determine whether the resource request from user and actual usage is over provisioned or under provisioned or optimally provisioned. Based on the usage pattern, we propose a capacity predictor for service providers, that for a specified period of time, the predicted capacity requirement for his entire cloud. This helps the administrators to make a decision among the options of whether to augmenting more resources into cloud, fetching resources from other cloud, migrating workload into other cloud. Along with this decision, we also propose a dynamic pricing scheme that the service cost pattern varies based on the demand and supply. The pricing scheme should be beneficial to both the service providers and service consumers. Our approach ensures optimal utilization of resources with increased service usage with available resources.

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Penalty-based pagerank algorithm

B. Jaganathan and Kalyani Desikan

In this paper we give a brief overview of the original Page Rank algorithm that is used in the Google search engine. This algorithm exploits the link structure of the web and greatly improves the results of Web search. We propose a new method for the computation of page rank on the basis of penalty scores assigned to web pages which are accessed through Advertisement links. We compare the page ranks obtained using the original page rank algorithm and our proposed penalty-based page rank method.

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An efficient and fast brain CT image classification using hybrid technique

A. Veeramuthu, S. Meenakshi and Yalavarthi Dharma Tejaswi

Nowadays, brain tumor is a standout amongst the most hazardous maladies happening regularly among people. The shots of survival can be expanded if the tumor is located accurately at its initial stage. A CT brain imaging technique is extensively used to conceptualize the perusal and structure of the brain. The images created by CT are high in tissue variance and have fewer artifacts. It has a few points of interest over other imaging procedures, giving high differentiation between delicate tissues. Nonetheless, the measure of information is a great deal excessively for manual examination, which has been one of the greatest deterrents in the compelling utilization of CT image. The recognition and forecast of tumor obliges a few courses of action on CT image which incorporates image preprocessing, segmentation, feature extraction, feature selection and classification. The concluding classification process using hybrid technique concludes that a status of CT image like normal, begnin, moderate or malignant. Finally, we shown experimentally our proposed framework is very effective and efficient prediction of tumor disease rather than other frameworks.

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Distributed cloud brokerage: solution to real world service provisioning problems

Prashant Khanna, Sonal Jain and BV Babu

This research analyzes the performance of a distributed cloud broker in a live cloud environment, utilizing a government owned, private, federated cloud. The paper explores functioning of a distributed cloud broker that assists in the provisioning of services to geographically distributed data centers. The data centers have volunteered to federate and expose their utilization metrics to each other through the cloud broker. The experimental infrastructure utilizes the closed schema for federation. The cloud broker is responsible for match making and bundling/provisioning of services from multiple private cloud providers, through volunteer and federated data centers. This has been tested under multiple load conditions. The proposed distributed cloud broker handles the load on the cloud ecosystem through a strictly controlled mechanism in a private cloud ecosystem, custom routing all overload conditions (cloud bursting scenario) on specific private clouds through a common interface visible to the Amazon Web Services (AWS). The proposed broker mechanism shows high efficiency and lesser cloud bursting instances compared to a pure AWS based ecosystem. The work also analyzes real world issues faced by organizations handling cloud brokerage frameworks in a distributed manner. The research asserts that it is possible to create customized distributed cloud brokers and the perspective of using a hybrid cloud approach using distributed broker in federated clouds is feasible, albeit in a tightly integrated and fine tuned cloud environment.

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Seasons: A scalable 4-tier cloud architecture for handling heterogeneity of mobile devices in live multimedia streaming

Preetha Evangeline D. and Anandhakumar P.

Cloud based live Media streaming is becoming one of the prominent scope among researchers. The growing popularity of the cloud has moved the Multimedia technology from being traditional to be highly modernized. Mobile devices have replaced the traditional way of viewing videos through PC’s. According to the recent survey there is an exponential hike in mobile video consumption, approximately 90% of consumers use a mobile devices to watch online videos when compared with 61% in 2012. Dealing with Device heterogeneity serves to be one of the biggest challenges for live media streaming as Mobile devices comes with various resolutions, OS’s, audio and video codec. It is hard to adapt live streaming contents according to the specification of the device on the fly. This paper proposes SEASONS, a 4-Tier Novel architecture that handles Device heterogeneity and concentrates on providing efficient and scalable media dissemination system. The proposed system takes 9 sec on an average for transcoding on the fly and 14 sec on an average for end-to-end delivery of videos when heterogeneous devices are considered.

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Effect of big data characteristics on security-leveraging existing security mechanisms for protection

K.V.S.N. Rama Rao, M. Pranava and A. Mounika

Big Data is the surge of data which was caused by growing technology and the increase in online computing. Several characteristics that define Big Data are Volume, Velocity and Variety. The inherent nature of these characteristics will certainly introduce several vulnerabilities and threats for the entire data. These security concerns in Big Data must be addressed. The traditional systems security concerns were addressed by several strong security mechanisms. All these mechanisms are proved to be efficient and well functioning. In this paper, we discuss about the security issues that arise due to Big Data characteristics like Volume and Variety. Further, we focus on leveraging existing security mechanisms to overcome the effects of Big Data characteristics.

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Radial basis function neural network for software engineering measures- A survey

Umamaheswari. E and D. K. Ghosh

In Software Quality, the Software reliability is the very essential part where it has the capability to manage its individual functions at various conditions. Now-a-days, Software measurements are entirely depends on different techniques like Fuzzy Logic, Neural Network, and Genetic Algorithm etc. This paper reviews SVM (Support Vector Machine) and RBFN to the issues of software measurement in order to increase the correctness as well as the performance. RBF (Radial Basis Function) and SVM has some secure relationship among them where they both are identified in many applications like in face verification, optical character recognition, text categorization and object detection etc. The results examines both the performance analyzes about RBFN and SVM Gaussian Radial Basis Kernel Function. This paper also compares the RBFN and SVM with parameter MRE.

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Semantic retrieval of spatial objects on location based services for everyday essentials

R. Jeberson Retna Raj and T. Sasipraba

Omnipresence of internet and advance of technologies helps the user to locate and access various socio physical services. Geospatial Information System (GIS) integrate GPS data and location information for providing spatial objects to the user. Location based services for every day is essential for an Information system which can provides the desired services to the user in a day to day life. In a city like Chennai one who wander around the places where to get the services like hospitals, insurance, community certificates, licenses for running shops, educational institutions and other government services etc. It is a tiresome process as no system physically available to fulfill the needs. Therefore, the need of an hour is to propose a system which can able to provide the details of day to day needs of a user. The system covers 600 sqkm of Chennai city, and large number of data is collected for implementation.

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Towards greater customer experience: role of network parameters on key business drivers

JoshiSujata, Bhatia Sanjay, Raikar Kiran and Athnikar Rohan

The purpose of the present study is to propose the importance of Network experience on Customer experience and Customer behavioral intentions for Cellular Service Providers. This research paper examines customers’ feedback on experience across various stages in customer lifecycles and interactions with their telecom operator and attempts identifying the determinants of network experience and their significant impact on customer behavioral intentions of churn, advocacy and purchase more. Primary research was conducted and more than 5000 respondents spread over 36 centres all over the country were surveyed. Questionnaire was used as the primary research instrument along with personal interviews. This paper establishes that Network experience has the highest impact among the 6 determinants of Customer experience for Cellular Service Providers. It also establishes the relation between Network experience parameters and customer behavioral intentions (churn, advocacy and intention to purchase more) through statistical backing of EFA and logistic regression tests. This is an initial paper to identify the determinants of network experience and customer experience in telecom industry. With the growth of data usage, further research is required to drill down into data experience parameters as well to establish the overall impact of network on customer experience and customer behavioral intentions. This paper helps to establish the tangible and intangible parameters of network experience and customer experience which in turn helps to understand the impact on customer behavioral intentions (churn, advocacy, purchase more, complaints). The Cellular Service Provider’s can use this relation between Network experience and Customer behavior for strategizing their investments and customer offers. The paper identifies the determinants of network experience and its direct impact on customer experience through a measurement yardstick. The method adopted incorporates various determinants across the customer lifecycle which are sufficient in defining customer experience holistically. The paper also establishes relation between Network experience parameters and customer behavioral intentions of churn, advocacy and purchase more.

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Evaluating metrics at class and method level for java programs using knowledge based systems

Umamaheswari. E, N. Bhalaji and D.K. Ghosh

Software metrics is considered to be the most important tool in software process management. It is also measure of property for a specific piece of software. Metrics also serves as a resource to anticipate and avoid the problems. Since there are only few measurement tools available, the need for metrics tool in testing the software is increasing. Although many metrics have been proposed by researchers they are used in isolation or ignored because they are not focused much. Therefore, an open source tool called “JAM (java metrics)” is to be developed to calculate various metrics and to display the metrics in graphical representation for java code. This learning tool allows software engineers to measure their code and to improve their software quality. It calculates the metrics at class level and method level. This tool also provides some basic information about the metrics calculated.

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Two factor authentications for secured login in support of effective information preservation and network security

S. Vaithyasubramanian, A. Christy and D. Saravanan

In the present digital day with remarkable development in Computer sector, Single factor authentication, e.g. passwords, is no more examined as secure in the World Wide Web. It has never been less difficult in Securing the system and remote access. Simple, obvious and easy-to-guess passwords, such as names and age, are effortlessly found via computerized secret key gathering programs. The security and privacy threats through malware are always constantly growing both in quantity as well as quality. Expanded access to information increases weakness to hacking, cracking of passwords and online frauds. In this association the conventional login/password authentication is taken into account inadequately secure for several security-critical applications such as login to Mailing Accounts, Social Networks, Gadgets, Financial accounts, official secured networks, commercial websites online etc. Obliging more than one independent factor increases the difficulty of providing false credentials. Two-factor authentication proposal guarantee a higher protection level by extending the single authentication factor. This paper focuses on the implementation of two-factor authentication methods by using both users friendly traditional Alphanumeric Password and graphical Password as gateway for authentication. An attempt has been made by using two factor Authentication, and in this paper we describe the two factor Authentication system design and design implementation. Thus affording an additional password adds an extra layer of security.

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Open platform cloud infrastructure model with enhanced virtualization

Abilash Rajasekaran, Sountharrajan Sehar, Elangovan Manickasundaram, Ezhilan Elangovan and Gowtham Kumar Thangaraj

Evolution of International network had led to growth in Cloud computing technology. Cost efficient personal computers with vast resource have been possible only by the evolution of Cloud Computing. The recent trend in Cloud computing technology emerges with the advancement of computing resources and hardware in single platform, provided to the user on-demand. The cloud computing has led to chief growth in the field of computer science and gave a major impact in business field with widespread adaption of virtualization and Service Oriented Architecture (SOA). In this paper, Infrastructure as a Service (IaaS) is provided on-demand to the user with enhanced virtualization technique to utilize third party resources. This may eventually lead third party user to compensate only addition charges towards their cloud vendor. Bare metal hypervisor maintains third party resource through Application Program Interface (API) during failure and data replication upon Service Level Agreement (SLA). This cloud setup would urge Business Enterprise to extend their resource across network and attract more users to cloud. Implementation of this setup provides openness to the world of Cloud Computing.

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Enhanced quality of service in visualizing the malaria data using cloud computing

A. Vijayalakshmi and B. Rajesh Kanna

Malaria disease is a major issue in public health problem and its spread in various tropical countries. Malaria forecasting was conducted in many tropical countries and typically uses data on environmental factors, human factors. There are variations in time on malaria causing incidence respect to geographical regions. The goal of the proposed work is to develop a cloud computing based application to insight the root cause of malaria.  It provides the enhanced quality of service like data filter, statistical data model, data view, data relation, which helps to forecast the environmental risk of malaria.  This forecast is inevitable because malaria prediction data are independent to each other, static in nature, hierarchical and complex. The proposed malaria forecasting application has been programmed using 'R' script and integrated with built-in IBM Bluemix container. Finally, it has been deployed as platform as a service under IBM cloud.  The developed application assists the malaria predictors to do seamless view of dense graphical informatics simultaneously.

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Banking on big data: A case study

Arti Chandani, Mita Mehta, B. Neeraja and Om Prakash

Big data; how big, is bigger than what the traditional application can handle and this gives a feel about the quantum of data which is being talked in the big data. Each day the technology is changing and everybody else is trying to cope up with the changes in the macro technological environment. Banks do generate a huge amount of data in their ordinary course of business which was being dumped in the books almost a decade back. Today the same data is being processed, analyzed and used for the benefits of the banks and customer. The data so generated can be used to customize services to the customer, to understand his needs, to design the most appealing marketing strategy to name a few. The big data, Peta-byte, can be efficiently used to analyze the financial behavior of a customer. A customer, who would have defaulted on a loan, may relocate making it difficult for the banks to trace but he still might be active on the social media, which can be used to trace the customer. This is one odd benefit which big data has to offer. All said and done, there are challenges to implement the big data technology for any bank. The biggest constraint comes from the finance front where any new technology requires a huge outlay of cash in the form of infrastructure, training and development cost and data warehouse and storage cost. The researchers have taken a hypothetical, yet practical, example to demonstrate the possible benefits of the adoption of the big data into a bank by calculating the net present value of the project. The researchers have used multiple rates instead of a single rate to help the users to take the net present value according to the rate applicable to them. The internal rate of return has also been calculated to understand the return which the project is generated itself and the same can be used by the users to compare with their internal rate of return to judge the viability of the project.

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Electronic medical records using NFC technology

A. Devendran, R. Jayam and P. Sindhuja

EMR-Electronic Medical Records are replacing Paper Medical Records which is now considered a key initiative in the Healthcare industry. It is because Paper medical records are easily lost and damaged and also disappears during emergencies. They are often incomplete with incorrect or missing information. Doctors therefore end up duplicating tests, making uninformed decisions and delaying care. But are EMR/Electronic charts really any better? - Unless it is available to providers at the right time.

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Analysis of the effectiveness in image compression for cloud storage for various image formats

Dasaradha Ramaiah K. and T. Venugopal

Digital image compression technology is of special interest for the fast transmission and real-time processing of digital image. However image compression is a trend of research grown for a long time and there are multiple sophisticated approaches which significantly improve the compression rate and down grade computation time, a basic comparison with the aspect of storage on cloud environment is required. This work analyzes about the background of image compression, including when image compression is needed, categories of techniques and their properties. However compression uses many algorithms that store an exact representation or an approximation of the original image in a smaller number of bytes that can be expanded back to its uncompressed form with a corresponding decompression algorithm. This work also analyzes the performance of multiple image formats for multiple compression algorithms over multiple cloud storage.

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Heterogeneous information management using ontology mapping

Kaladevi Ramar and T. T. Mirnalinee

Increase in web and information technologies has made available to large number of independently created and managed information systems. These systems include similar information from disparate sources cause information heterogeneity. To achieve interoperability between heterogeneous information systems and unified integration of those systems heterogeneities between information systems needs to be reduced. Mostly information heterogeneity occurs in three levels: syntactic, structural and semantic. The semantic heterogeneity issue is not completely addressed yet. In this research syntactic, structural, data and semantic heterogeneities between information systems is considered and a novel ontology mapping technique is developed to resolve semantic heterogeneity achieving semantic interoperability between ontologies. Background knowledge has been taken as reference ontology as a part of this work. The Ontology Mapping For Information Management (OMFIM) algorithm is evaluated with OAEI (Ontology alignment Evaluation Initiative) benchmark dataset and the performance is compared against S-match algorithm. Result shows that our proposed method outperforms the S-match algorithm for solving semantic heterogeneity and also best suitable for the systems with insufficient lexical overlap and poor structural correspondence.

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Cloud based search engine

Nithya G., Engels M. S., Gayathri S and Ganesh Kumar D.

With the advancement in science and technology, the problem of managing and maintaining expensive computing resources have become more complicated. In order to overcome this burden the recent trend is to effectively use cloud computing, supporting resource sharing, with many services. The goal is to aggregate idle network and to preserve resources such as CPU cycles and storage spaces to facilitate effective utilization and computing. For the above mentiones, we need to find an efficient method for identifying the services based on all the results from a cloud based search engine. The assignment and choosing of a cloud service should facilitate efficient problem solving and promote optimal use of resources. One such solution must be able to apply in a large array of information processing units. This project proposes to address the above problem using the Multi-Agent Brokering Approach, for the identification of services from the results of a cloud based search engine in a cloud environment. The Multi-Agent Approach ensures that the agents can specialize in identification of services made to process the requests. It also orders the results of the search with various ordering options such as CPU speed, memory and storage. For achieving this, the proper representation of provider capabilities and ontology relationships are essential.

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Analysis of "air-moving on schedule" big data based on crisp-dm methodology

Man-Seok Ha, Jung-II Namgung and Soo-Hyun Park

Punctuality of air traffic is one of the most important criteria for choosing an air service. In this paper, we would like to develop and implement an experimental model based on the CRISP-DM (Cross Industry Standard Process for Data Mining) methodology applied to Big Data Mining. In this case, we choose the data from the ASA (The American Statistical Association) air traffic data for the experiment and then analyzed the data by using the Hadoop Distributed File System, Hive and R studio.  The using the analysis, the arrival delay can be proposed for optimal airports. In fact there was a way to take advantage of the leverage results, so we got the best results when applying ANN (Artificial Neural Network) model.

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Adaptive modulation with multi-level securityusing sparse matrices

Navaneethan C. and K. Helen Prabha

In the wireless sensor network system, wide ranges of techniques have been developed for securing the data before transferring to the concerned destination. Cryptography and modulation are distinct techniques that are used in wide range to protect the information from the attackers. In this slog we came up with a work of “Adaptive Modulation with Multi-Level Security for Networks”, in which the plain text is encrypted by using the newly proposed Encryption and Decryption Based on Sparse Matrices algorithm. This algorithm is a multi-staged encryption and decryption. By deploying encryption algorithm at the sender side message is encrypted before operating with modulation and demodulation algorithm. Encrypted message is then modulated through modulator. At the receiver side demodulation is performed followed by decryption operation. This approach results in the secure adoption of modulation with effective cryptography in unsecured channel more effectively.

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Enhanced hybrid framework of reliability analysis for safety critical network infrastructure

Chandana Priyanka G. H., Aarthi R. S., Chakaravarthi S., Selvamani K. and Kannan A.

This work proposes enhanced hybrid frame work for reliability analysis for Safety Critical Network Infrastructure. The proposed frame work enables design and development of web service for the safety critical systems to identify the component failures in the network infrastructure. The enhanced hybrid frame work of reliability analysis for multilayer in Safety Critical Network Infrastructure results in accuracy of identifying the failure of the component, failure modes of the component that makes the system more reliable and reduces the error rate in the network infrastructure. The Safety Critical Network Infrastructure requires a monitoring mechanism that can be used for public sector enables to detect failures as early as possible in the layers of the network. In order to work as a service provider for the critical components to the user a web service was designed and these failure results are used as database for efficient utilization of the data.

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Increasing web services day by day and huge volume of data is also increasing exponentially. Processing a large amount of data efficiently can be a substantial problem. Currently, the method for processing a large amount of data comprises adopting parallel computing. Big data is an all-encompassing term for any collection of data sets so large and complex that it becomes difficult to process them using traditional data processing applications. The challenges comprise analysis, capture, creation, search, sharing, storage, transfer, visualization, and privacy violations. With pervasive sensors continuously collecting and storing enormous amounts of information leads to data flood. Learning from these large volumes of data is expected to bring significant science and engineering advances along with improvements in quality of life. However, with such a big blessing come big challenges. Billions of Internet users and machine-to-machine connections are producing a huge volume of data growth. Utilizing big data requires transforming information infrastructure into a more flexible, distributed, and open environment. In this paper, a survey has been prepared about the techniques available for optimization in big data with the presence of swarm intelligence. Using mathematical model based algorithm for optimization (Swarm Intelligence) in big data will yield better performance while handling of dynamic data in the non-stationary environments and dynamic environments.

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Data that resides in a fixed field within a record or file is called structured data and have a defined schema. Unstructured Data refers to information that either does not have a pre-defined data model and does not fit well into relational tables. Clustering gains importance in the fields of Libraries (book ordering), Insurance (identifying groups and identifying frauds), WWW (document classification and clustering weblog data). Available clustering algorithms work only with structured data and use medoids as parameter for clustering. Clustering big data is not feasible, as they are mostly unstructured. It is not possible to label large collection of objects and identifying subspace clusters in unstructured data is a difficult task because of time complexity. In this paper, we proposed and designed a new algorithm called uCLUST, which identifies clusters in unstructured data as traditional distance functions cannot capture the pattern similarity among the objects. The proposed algorithm is applied in 6 different datasets and results are tabulated.

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Group search optimizer algorithm for localization in wireless sensor networks

Harikrishnan R., Jawahar Senthil Kumar V. and Sridevi Ponmalar P.

In wireless sensor network, sensor nodes are deployed randomly depending on the application. The sensor node location is very much important to make a meaningful sense of the data gathered by the sensor network. The intelligence of the environment is assisted by wireless sensor network by using the location information of the sensor nodes. In this paper a novel algorithm named group search optimizer localization algorithm is proposed for sensor node location information detection. This algorithm is based on producer scrounger model of animal behavior. The location information detection is required to increase the performance and reliability of wireless sensor networks (WSN). It also increases the lifetime of the network by guiding the network without unwanted routing.

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Nature inspired flower pollen algorithm for WSN localization problem

Harikrishnan R., Jawahar Senthil Kumar V. and  Sridevi Ponmalar P.

Location of sensor node is required for improving efficiency and performance of node management. An accurate localization algorithm with better efficiency and lesser computing time is required. Moreover the complexity of the algorithm and the memory required should be less. The algorithm should be faster for the usage in sensor node self localization. In this paper a novel nature inspired based algorithm called flower pollen localization algorithm is introduced for sensor node localization problem. Flower pollination is a process of reproduction of plant species and survival of the fittest.

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ASE noise analysis in cascaded EDFA-EYCDFA

S. Semmalar and S. Malarkkan

The scope of this paper is to analyze  ASE (Amplified Spontaneous Emission ) noise power using the simulation model  EDFA (Erbium Doped Fiber Amplifier) cascaded with EYCDFA (erbium-ytterbium co-doped fiber amplifier) in 4-16 channels of transmitters combined by optical multiplexer and sent the output to EDFA in series with EYCDFA in single backward pumping using the wavelength of 980nm. This simulation model performance was analyzed with the parameters Gain, forward output signal power and ASE noise was measured and the values are tabulated. The simulation model consists of 2- 16 channels of RZ transmitter and 2- 16 channels of NRZ transmitter’s outputs were multiplexed with optical multiplexer and multiplexed signal sent to cascaded Erbium amplifiers with pumping CW (continuous wave) Laser source with wavelength 980nm and Filter. The resulting model accurately represents EDFA Gain and output signal power and ASE noise.  Simulation results shows that by choosing careful fiber length 20m and pump power 1mw in single pumping gives ASE noise 0.005mw using EDFA and  EYCDFA gives zero mill watts.

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Design and analysis of silicon diaphragm of a MEMS pressure sensor

S. Maflin Shaby

Pressure measurements in industries, biomedical and marine environment are of utmost importance to better understand the process stability, ocean processes. The influence of in-plane stresses of silicon plate with square, rectangular and circular shape have been investigated. The area of square ,rectangular and circular form of elastic element has been approximated to be equal and the thickness is about 1μm. It was shown, that in-plane stresses can have a great influence on plate deflection and stresses distributions that should be taken into account at designing of piezoresistive pressure sensors. Finite element method (FEM) is adopted to optimize the sensor parameters, such as the membrane shape the deflection and stress caused by the different elastic membrane was analysised to achieve higher sensitivity, larger full scale span and linearity.

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Implementation of message authentication scheme with elliptic curve cryptography

G. Indumathi and T. Kiragapushpam

Transmission of private information over the public channels requires security or data protection against unauthorized access. Elliptic Curve Cryptography (ECC) is one of the efficient encryption technique can be used to secure the private data. High level security requirement of Restricted Services of Indian Regional Navigation Satellite System (IRNSS) to transmit the navigation data through wireless channel, can be achieved by ECC with minimum key size. ECC is based on Elliptic Curve Scalar Multiplication (ECSM) which is the process of multiplying a point on elliptic curve by a scalar value. The operations has been performed on National Institute of Standards and Technology (NIST) recommended elliptic curves over binary field E (2233).The performance of ECC algorithm is influenced by the implementation of elliptic curve finite field operations. Therefore, field operations play vital role in ECC. Among finite field operations such as squaring, multiplication and inversion, multiplication is very important in cryptosystem. Karatsuba algorithm with polynomial multiplication is more efficient for large numbers. The encryption algorithm, point operations and field operations have been implemented in Xilinx Virtex-5 FPGA board.

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A fully differential read-decoupled 7-T SRAM cell to reduce dynamic power consumption

Soumitra Pal and Shahnawaz Arif

To improve the performance of an SRAM cell and reduce the area consumption, researchers are scaling down the technology node of MOSFET. But power consumption is not yet improved below 65-nm technology node. Since then the VDD (supply voltage) remains more or less constant and dynamic power consumption improvement is almost stagnated, while leakage current increases exponentially. Hence, prime area of concern of present days circuit is to reduce the power consumption with minimum device size. In this article a fully differential read decoupled 7T SRAM cell is proposed that consumes substantial amount of less read and write power. Side by side it shows 4% (10.57×) shorter read (write) delay and 4×/9.24% improvement in RSNM/WSNM (Read static noise margin/write static noise margin) @ 700 mV.

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Ontogeny smart bulletin board

S. Karthikeyan

At present days every advertisement is going to be digital. Some large shopping malls and shopping centers are using the digital moving displays. In railway stations and bus Stations, ticket information, platform number etc. are displaying in digital moving message display. But in these case if they wants to change the information they have to go there and connect the display to PC or laptop and then change it. Suppose the same information, if the person wants to display in main centers of the cities or longer distance places, he has to go there with laptop and change the information by connecting to the PC. In this application we are implementing wireless communication to change the information which is displayed on the VGA monitor. Here we are implementing this idea for college notice board with the help of VGA monitor. This paper is to display the color image and text by using ARM7 (LPC2148).

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Tone mapping and image enhancement using recursive mean separate histogram equalization (RMSHE) technique

J. Kanimozhi, P. Vasuki and S. P. Shamilee

This work aims to develop a Novel Image Enhancement technique to enhance contrast and tone of digital Imagery. Contrast Enhancement and White Balancing used for Image Enhancement. Contrast Enhancement is achieved by Recursive Mean Separate Histogram Equalization (RMSHE). White Balancing is used for Tonal correction. Parameter such as PSNR, MSE, MAE are calculated to identify the better Histogram Equalization for contrast enhancement.

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Design methodology for the field orientation control of a non-linear vector controlled sinusoidal permanent magnet AC motor

P. Ramana, M. Surya Kalavathi, K. Alice Mary and V. Dinesh Gowri Kumar

Nearly all of the electrical power used throughout the world is generated by synchronous machines driven by either hydro or steam turbines or by combustion engines. Synchronous Machine is generally dedicated to high power due to the fact that they have a controllable power factor and a higher efficiency than the induction motor of corresponding rating. In recent years different control schemes using synchronous motors operating from static power converter have been a real competitor to both DC and Induction Motor drives, especially in high power, low speed range. Among them field oriented control employing vector control strategies has become quite popular in recent years. A disadvantage of the scheme when applied to synchronous motor drive is that the motor always operates at a lagging power factor. In this work a generalized design strategy is suggested for speed control loop of an inverter fed synchronous motor drive, in which, its inherent flexibility to generate the same torque for different combinations of currents is exploited. The closed loop system for the Permanent Magnet AC Motor is simulated using MATLAB and the performance figures of some typical cases such as unity power factor control, torque angle control and internal angle control are obtained.

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Analysis of MEL based features for audio retrieval

R. Christopher Praveen Kumar and S. Suguna

Nowadays the electronic gadgets have been updated to store large amount of music information. It is necessary to have an efficient retrieval system to choose the required data. The important task in audio retrieval system is feature extraction.  In the feature extraction stage, the feature which gives relevant   information about music has to be extracted. In this paper, various Mel based feature which includes Mel Frequency Cepstral Coefficient (MFCC), Delta MFCC (DMFCC), Double Delta MFCC (DDMFCC), hybrid feature (MFCC+DMFCC+DDMFCC) has been analyzed for audio retrieval system. It has been found out that the audio retrieval system which makes use of hybrid feature will provide better result compared to the other features.

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Energy efficient wireless classroom and bus monitoring system

Vijaya baskar V. and Sakthivel E.

The main objective of this work is to develop a system for monitoring the class room to update the students’ strength in the class room automatically. The students entry and exit can be tracked through the IR transceiver pair. This system also uses the RF reader to find the active staff present in the class. Then finally the desired information can be sent to the control centre, which may be the principal or HOD room. The control centre and class room module communicates through the ZigBee; thereby the information monitored is stored in the centre PC. The purpose of monitoring is to find the number of students present in the class in each hour.  This system minimizes energy consumption and human intervention. This system can also be used to monitor the bus arrival time at the university campus.  The ‘IN’ time, ‘OUT’ time of a bus and the number of persons boarding on the buses can also be monitored and these data can be sent to the admin location.

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Development of real time monitoring system under smart grid environment

M. Krishna Paramathma, D. Devaraj and Malaikannan R.

Real time monitoring of power system is essential for its continuous and reliable operation. This paper presents a low cost, low power consuming system that can be used for quick and accurate power system parameter monitoring under smart grid environment. The designed system will continuously measures, processes and display the power system parameters like voltage, current, phasor difference, power factor, power consumption using ultra low power microcontroller. Measurement of power system parameters of resistive and inductive loads are monitored using PIC16F877A microcontroller. Sampling theorem is used to calculate the phase difference between voltage and current utilizing zero crossing detectors. Simulations of the voltage, current, phasor difference were done using NI Multisim software.

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DCT based partial transmit sequence technique for PAPR reduction in OFDM transmission

R. Jayashri, S. Sujatha and P. Dananjayan

OFDM is used as a resource sharing multiple access technique in 4G technology which has several advantages of high data rate, good spectral efficiency, robust against frequency selective fading, etc. Major disadvantage of this system is high peak-to-average power ratio which degrades the performance of power amplifier. In order to overcome this problem, several distortion and distortion-less algorithms have been proposed. Partial Transmit Sequence (PTS) is one of the distortions-less technique which divides the input sequence into subsequences and chooses the phase optimized minimum PAPR signal for transmission. In turn to minimize the PAPR further, signal energy compaction and reduced autocorrelation of input data sequences is required which will be provided by Discrete Cosine Transform. The proposed method combines Discrete Cosine Transform (DCT) with PTS technique. The proposed scheme applies DCT before and after PTS technique. Simulation results shows that DCT before PTS is having better PAPR reduction performance than the DCT after PTS, conventional PTS and conventional OFDM system. The simulation result for the proposed approaches are discussed which reduces PAPR efficiently.

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On the metric dimension of silicate stars

F. Simon Raj and A. George

A minimum resolving set or a metric basis M for a graph G(V, E) is a small subset of vertices of V such that for every pair of vertices x and y of V  \ M, there exist at least one  vertex m in  M  such that the distance between x and m is not equal to the distance between y and m. The number of elements of the metric basis M of  G is called metric dimension and the elements of a metric basis are called landmarks. A metric dimension problem for a graph G is to find a metric basis for G.  In this paper a new silicate graph called Silicate Stars or Star of Silicate Networks SSL(n) has been derived from Star of David Networks SD(n).  The metric dimension problem has been solved for SSL(n) , Single Oxide chain, and single  Silicate chain. The problem of finding the metric dimension of a general graph is an NP Complete Problem.

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Implementation of signed VEDIC multiplier targeted at FPGA architectures

Paldurai K. and K. Hariharan

Signed Multiplications are very expensive and used in many of the Digital Signal Processing (DSP) applications such as Multiple-Accumulate unit and Fast Fourier Transforms (FFT). The performance of DSP computational blocks are often dominated by the speed at which a multiplication operation can be executed.  Therefore a high speed signed multiplier is highly desirable to achieve high speed DSps. This paper proposes design and implementation of a novel high speed signed multiplier based on Vedic mathematics. The proposed architecture has the advantages of reduced delay and less area over conventional Booth radix-2 multiplier. It uses unsigned multiplier based on Urdhva Tiryakbhyam and 2s complement circuit. The proposed signed multiplier and conventional booth multiplier are coded in Verilog, synthesized and simulated using ISE simulator. It is implemented on the iwavesystems Unified Learning Kit Spartan6 family xc6slx25t-2fgg484 FPGA. The Area and maximum combinational path delay of proposed Signed Multiplier and conventional Booth Multiplier are compared.

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Multi-user MIMO transmission modes for transmit diversity and spatial multiplexing in long term evolution

Patteti Krishna, Kalithkar  Kishan  Rao and Tipparti Anil Kumar

Third Generation Partnership Projects Long Term Evolution –LTE downlink multiuser Multiple Input Multiple Output (MIMO) systems are analyzed in this paper. Two Spatial  Multiplexing and transmit diversity multiuser MIMO schemes .To achieve high throughput required by the downlink LTE system, Adaptive Modulation and Coding (AMC) has to ensure a Block Error  Rate(BLER) value . In this paper, we made a comprehensive study to evaluate the performances of open loop spatial multiplexing (OLSM) and transmit diversity (TxD) in downlink LTE system for different transmission mode are investigated.

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Performance of four phase switched reluctance motor drive using single pulse width modulation technique under constant turn off angle and random turn off angle

J. Uma and A. Jeevanandham

This paper describes a comparative analysis of electronics switching control schemes to minimize the torque ripples and speed oscillation for 8/6 Sensorless Switched Reluctance Motor (SSRM) drive and development of Fuzzy supervisory control scheme to control the speed of the drive. The Fuzzy logic was used to adjust the classical PI controller parameter in on-line. The electronic control schemes include single pulse width modulation at both level switches and random turn-off angle generation. The switching methods and speed controller have been developed and tested using Matlab/Simulink. To demonstrate the effectiveness, the switching methods have been implemented in PI based speed control system drive and its performance was evaluated. The performance of PI-Fuzzy speed controller was compared with conventional PI controller.

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Traffic sign detection and recognition in driver support system for safety precaution

Y.  Mary Reeja, T.  Latha and A. Mary Ansalin Shalini

In this paper, an efficient algorithm for the detection and recognition of traffic signs is presented. The proposed system identifies candidate regions as interest region extraction, which offers strength to variations in lighting conditions and wave equation (WaDe) algorithm. A HOG based Support Vector Machine (SVM) is used to classify the traffic signs. The methodology is established on videos under changing weather conditions and poor illumination. The image preprocessing based on the red color channel enhancement improves the detection rate. The SVM classifier also achieve high classification rate.

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Design of CSRR embedded metamaterial monopole antenna for WIMAX applications

Anandhi Meena B., Thiruvalar Selvan P., Raghavan S. and Suganthi S.

A novel design and development of a simple monopole antenna based on composite metamaterial resonators for multiband operation is presented.  The antenna has frequency notched function since the composite CPW (Co-Planar Waveguide) metamaterial resonators CSRR (closed-ring resonator and SRR) which is embedded on the planar monopole that resonates for multiple frequency bands. The antenna resonates for the frequency of (Wi-MAX) 3.4 to 3.5GHz and 5.725 – 5.875GHz which have good impedance matching and radiation performance.

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Tensile properties of reinforced plastic material composites with natural fiber and filler material

Rakshit Agarwal, M. Ramachandran and Stanly Jones Ratnam

Usage of natural fibers in reinforced plastic material with natural fibers as a composite had a positive approach for the development of green composites in our day today life. In this paper we are studying the tensile properties of woven bamboo bidirectional natural fiber with coconut shell powder in micro and nano size reinforced polymer composite with an angle of 0o/90o orientation. The tensile properties were studied before and after water absorption test on specimens. The water absorption test will shows the deviation in the tensile properties of the natural fiber reinforced composites before and after water absorption in material. More deviations can be reduced by various chemical treatment of the natural bamboo fiber. It is analyzed and proved that bamboo fiber absorbs less water when compared to all other natural fibers. Bonding between the matrix and the natural fibers are shown in the SEM analysis report.

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Study on pressure drop characteristics of single phase turbulent flow in pipe bend for high Reynolds number

P. Dutta and N. Nandi

Pressure drop characteristics of turbulent flow through 90 degree pipe bends are numerically investigated by computational fluid dynamic simulation using k-ε RNG turbulence model with standard wall function.  After the validation of present model against existing experimental results, a detailed study has been performed to investigate the pressure distribution and pressure drop characteristics over a wide range of Reynolds number (Re = 1×105 to 10×105) and for different curvature ratio (RC/D = 1 to 5) to study pressure loss coefficient in terms of Reynolds number and curvature ration to provide cost effective solutions to design of the pipe bends. A number of important results have been achieved showing the distribution of pressure at different location throughout the bend for different Re and Rc/D. Numerical results shows the dependency of pressure distribution and pressure loss coefficient for different Reynolds number and curvature ratio throughout the bend.

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FE analysis of knuckle joint pin used in tractor trailer

Dinesh Shinde and Kanak Kalita

Tractor trailer is a useful equipment used in agriculture field for carrying heavy goods. To connect trailer to the tractor flexibly, a knuckle joint is used which consist of forks and a pin, a fork is attached to tractor rigidly and another fork is attached to the trailer by a pin. During acceleration of tractor, force acting on the joint is tensile and during deceleration it is compressive. Force acting over the joint is calculated by considering Newton’s Second Law of motion. At the time of carrying heavy weights, due to its fluctuation a pin is subjected to high stresses. As the pin is a flexible element which can easily be replaced, it is considered separately for the analysis and finite element analysis is done on it.

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A numerical study of SCF convergence using ANSYS

Mohit Thirumump, Kanak Kalita, M. Ramachandran and Ranjan Ghadai

In this paper a metallic plate made of steel with an elliptical hole, having fixed long radius and variable short radius is pressure loaded. A comparison is made between the results obtained from analytical equations (from reference 16) for a plate with an elliptical hole and the results obtained from FEA. To show that increasing the order of the element can be one way to improve the results obtained from FEA model two different finite elements (4 node and 8 node plane element) were used on the model. This was shown by measuring the length of the element at the tip of the ellipse. It is possible to produce a more accurate FEA model by increasing the number of elements in a mesh. To show this, the number of elements used to mesh the model were recorded and compared for each ellipse size.

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Green space distribution plays a imperative role in urban planning since they contribute significantly in enhancing ecological quality of metropolitan areas. It improves air quality, urban health, conserving biodiversity, reducing noise, etc. Removal of vegetation cover can be identified as one of the poorest effects of urbanization. Proper distribution of green spaces in urban environments is consequently more inevitable for the sustainable development and healthy living. Hence, it is necessary to identify the green space requirement quantitatively and spatially. To achieve the goal, high resolution Cartosat-1 satellite data, were used to analyse the spatial pattern. Spatial features like Point feature and polygon features were demarcated from imagery. Individual trees, group of trees, bushes, building area (covering both residential/industrial area), water bodies (lakes, ponds, reservoir, streams, rivers etc.), parks and temples has been considered. The tree cover area covers 72.82Sqkm, Buildings covers 241Sqkm, Parks covers 9.28Sqkm, Water bodies covers 35.73 Sq.km and other area 104.40Sqkm out of 464sq.km area coverage of Chennai municipality. Subsequently, green spaces required to be created are calculated with respect to WHO standards of green spaces per capita for healthy living (9.5 m2/ person) and a methodology is developed to spatially define appropriate areas to establish them.

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Wireless sensor networks are composed of a large number of sensor nodes with limited energy resources. One critical issue in wireless sensor networks is how to gather sensed information in an energy efficient way since the energy is limited. The clustering algorithm is a technique used to reduce energy consumption. It can improve the scalability and lifetime of wireless sensor network. In this paper, we introduce an adaptive clustering protocol for wireless sensor networks, which is called Adaptive Decentralized Re-Clustering Heterogeneous Protocol (ADRHP) for Wireless Sensor Networks. In ADRHP, the cluster heads and next heads are elected based on residual energy of each node and the average energy of each cluster. Clustering has been well received as an effective way to reduce the energy consumption of a wireless sensor network. Clustering is defined as the process of choosing a set of wireless sensor nodes to be cluster heads for a given wireless sensor network. Therefore, data traffic generated at each sensor node can be sent via cluster heads to the base station. The selection of cluster heads and next heads are weighted by the remaining energy of sensor nodes and the average energy of each cluster. ADRHP is an adaptive clustering protocol; cluster heads rotate over time to balance the energy dissipation of sensor nodes. The simulation results show that ADRHP achieves longer lifetime and more data message transmissions than current artificial neural network (ANN) based clustering protocol such as Residual Energy Based Clustering Self organizing map (R-EBCS) in wireless sensor networks.

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Dynamic analysis of rotating composite cantilever blades with piezoelectric layers

Abir Dutta, Kanak Kalita and Dinesh Shinde

Rotating plates in form of turbine blades or machinery parts are often encountered in industrial engineering. The dynamic characteristics of these plates are useful information from design point of view. This paper deals with vibrational analysis of the skew composite plates with piezoelectric layers. In this paper an attempt has been made to study the influence of skew angle and rotational velocity on the free vibration frequencies of a cantilever composite plate with piezoelectric layers. A commercial finite element package ANSYS is used as solver for the problem. The obtained results are compared with existing literature and good convergence in results is seen.

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Segmenting ripe fruits region in the foliage is an important step in agriculture sector applications of yield measurement, robot harvesting, and fruit grading. In this paper, we present a fundamental study of different color spaces RGB, HSV, L*a*b and YIQ with the motivation of analyzing, which color space is convenient for ripe fruits recognition from the background. The results show that ‘I’ component of the YIQ color space has the best criterion for recognizing the ripe fruits from the other regions.

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Subspace clustering developed from the group of cluster objects in all subspaces of a dataset. When clustering high dimensional objects, the accuracy and efficiency of traditional clustering algorithms are very poor, because data objects may belong to diverse clusters in different subspaces comprised of different combinations of dimensions. To overcome the above issue, we are going to implement a new technique termed Opportunistic Subspace and Estimated Clustering (OSEC) model on high Dimensional Data to improve the accuracy in the search retrieval. Still to improve the quality of clustering hubness is a mechanism related to vector-space data deliberated by the propensity of certain data points also referred to as the hubs with a miniature distance to numerous added data points in high dimensional spaces which is associated to the phenomenon of distance concentration. The performance of hubness on high dimensional data has an incapable impact on many machine learning tasks namely classification, nearest neighbor, outlier detection and clustering. Hubness is a newly unexplored problem of machine learning in high dimensional data spaces, which fails in automatically determining the number of clusters in the data. Subspace clustering discovers the efficient cluster validation but problem of hubness is not discussed effectively. To overcome clustering based hubness problem with sub spacing, high dimensionality of data employs the nearest neighbor machine learning methods. Shared Nearest Neighbor Clustering based on Unscented Transform (SNNC-UT) estimation method is developed to overcome the hubness problem with determination of cluster data. The core objective of SNNC is to find the number of cluster points such that the points within a cluster are more similar to each other than to other points in a different cluster. SNNC-UT estimates the relative density, i.e., probability density, in a nearest region and obtains a more robust definition of density. SNNC-UT handle overlapping situations based on the unscented transform and calculate the statistical distance of a random variable which undergoes a nonlinear transformation. The experimental performance of SNNC-UT and k-nearest neighbor hubness in clustering is evaluated in terms of clustering quality, distance measurement ratio, clustering time, and energy consumption.

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Electroless Ni-Cu-P coating was staked on a large concentration of pure Copper substrate. The purpose of present study is to analysis the variation in mass deposition with basis three parameters namely Ni-ion concentration, Cu-ion concentration and reducing agent concentration of the chemical bath. A central composite design of experiments has been considered here as the statistical analysis tool. The mass deposition is treated as the feedback in student’s test and it has been found that the concentrations of Ni –ion source and all other interactions significantly influence the mass deposition at 0.05% level of significance. A mathematical model has been developed considering response surface methodology. The optimum concentrations of Ni-ion source, Cu-ion source and reducing agent are obtained using evolutionary algorithms to maximize the mass-deposition per unit area. The coating is again deposited with the optimum concentrations of the parameters and maximum mass-deposition is observed. The XRD of the coatings has revealed that the coating is amorphous in nature.

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Modified K-best detection algorithm for MIMO systems

Shirly Edward A. and Malarvizhi S.

This paper presents a VLSI implementation of reduced hardware-complexity and reconfigurable signal detector for MIMO (Multiple-Input Multiple-Output) systems.MACROBUTTON NoMacro    In recent wireless communication system, MIMO technique is being adopted to meet the rapidly increasing demands for the multimedia services and to achieve better QoS(Quality of Service). Maximum likelihood (ML) detection is the optimal hard decision detection for MIMO systems. FPGA implementation of ML detector becomes infeasible as its complexity grows exponentially with the number of antennas. Therefore, we propose a modified K-best detector algorithm which employs parallel and distributed sorting strategy that has a constant throughput and near-ML detection solution. The proposed MIMO detector was implemented targeting Xilinx Virtex 6 device for a 2x2, 4 QAM system and it achieves throughput of 12.23Mbps. The resource utilization results are listed and compared with the existing algorithm. The total on-chip power estimated is 1.57W.

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The system-on-chip (SoC) revolution imposes a threat in the area of power dissipation by challenging designing as well as the testing process. Basically, a circuit or a system consumes more power in test mode than in normal mode. This increase in test power is due to increase in the number of switching activity in the device due to test pattern used for testing. This extra power consumption gives rise to severe hazards in circuit reliability and also can provoke instant circuit damage. Many techniques are available for test data compression. The “Proposed Tanimoto distance Based Reordering” technique is a modification to the earlier proposed “Hamming Distance based Reordering - Columnwise Bit Filling and Difference vector”.

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