Informatics Publishing Limited

C. Dhanasekaran ¹, R. S. Ponmagal ¹

Affiliations
1 Department of CSE, Dr. M.G.R. University, Maduravoyal, Chennai, Tamil Nadu 600095, IN

Abstract

Ad hoc networks are wireless dynamic networks that possess self configuration character which leads to high vulnerable threats to networks. Earlier the malicious nodes that cause the threats are completely removed from the network, which may cause the network partition and diversion. In the proposed work, the isolation technique is used to maintain the network stability to protect the network infrastructure.

Keywords

Dynamic, Self-Configuration, Malicious, Isolation, Network Infrastructure.

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B. Vidhyalakshmi ¹, R. S. Ponmagal ¹, J. M. Gnanasekar ¹

Affiliations
1 Department of Computer Science, Anna University of Technology, Tiruchirappalli, IN

Abstract

The motto of this paper is to analyze the performance of Service Oriented Sensor Network by utilizing Cloud technology. Cloud offers a way to share sensor information enhancing the performance of whole system. Wireless Sensor networks have become a vital part of many fields that involves remote sensing applications. The technical advancements are achieved at the cost of increased power consumptions of the sensors which will diminish the life-time of the sensors. The power of the sensors is spent by transmitting data continuously to the sink node. Moreover the autonomy of the system is considerably less. So, our intent is to develop an energy efficient architecture which is highly dynamic, flexible, scalable that provides an autonomous environment by making use of the Sensor Profiles as a placeholder. The concept is conceived based on identification of a particular sensor and data based on the Sensor Profile which is said to be unique for each and every sensor. The incorporated Cloud architecture in the proposed architecture ensures well managed data access and also provides an increased speed in data access. Obviously the deployment of Sensor Profile and sensed data in the Cloud enhances high degree of scalability and increased power efficiency. The Cloud SenPro architecture provides considerable pros such as rapid data access leading to quicker throughput and furthermore the architecture leads to an autonomous, power effective, dynamic, flexible and scalable environment.

Keywords

Sensor Profile, Cloud, XML and XSLT.

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B. Premkumar ¹, R. S. Ponmagal ²

Affiliations
1 Dr. M.G.R Educational and Research Institute University, Chennai, IN
2 Dr. M.G.R Educational and Research Institute University, Chennai, IN

Abstract

Cloud-based outsourced storage relieves the client’s burden for storage management and maintenance by providing a comparably low-cost, scalable, location-independent platform. However, the fact that clients no longer have physical possession of data indicates that they are facing a potentially formidable risk for missing or corrupted data. Provable data possession (PDP), which is a cryptographic technique for verifying the integrity of data without retrieving it at a distrusted server, can be used to realize audit services. We prove that our construction holds these properties based on the computation Diffie–Hellman assumption and the rewind able black-box knowledge extractor. We also propose an efficient mechanism with respect to probabilistic queries and periodic verification to reduce the audit costs per verification and implement abnormal detection timely. In addition, we present an efficient method for selecting an optimal parameter value to minimize computational overheads of cloud audit services. Our experimental results demonstrate the effectiveness of our approach. This kind of outsourced storage services in clouds have become a new profit growth point by providing a comparably low-cost and scalable.

Keywords

Provable Data Possession, Audit Services, Probabilistic Queries, Periodic Verification.

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R. S. Ponmagal ¹, J. Raja ²

Affiliations
1 Department of CSE, Anna University of Technology, Tiruchirappalli, TamilNadu, IN
2 Department of ECE, Anna University of Technology, Tiruchirappalli, Tamilnadu, IN

Abstract

This paper aims to examine how the sensor information can be deployed as a service, through a new resource called ―cloud‖. The recent research issue in integrating Wireless sensor Networks with Cloud is to find a method to establish a faster communication link between the two. The wireless sensor networks are used to sense and collect the information required. The sensor information is deployed into the cloud through the sensor profile for web services. The Sensor Profile for Web Services specifies a lightweight subset of the overall Web services protocol suite that is appropriate for network-connected sensors. Cloud generally offers resources on demand. Since wireless sensor networks are limited in their processing power, battery life and communication speed, cloud computing usually offers the opposite, which makes it attractive for long term observations, analysis and use in different kinds of environments. In this paper a model is presented, which combines the concept of wireless sensor networks with the cloud computing paradigm, and show how both can benefit from this combination. Sensor data access is thus moved from loosely managed system to a well managed cloud. The integration of sensor information into the cloud through the sensor as a service paradigm proves the faster communication establishment. The scalability of this approach seems to be unlimited, since wireless sensor networks operate independently, and are connected to the cloud computing environment through a scalable number of wireless sensor network communication gateways. The cloud computing environment leads to the concept of green engineering, because it offers a massive storage of information at a distance place, which makes it very attractive. The main goal is to design a flexible architecture in which sensor network‘s information can be accessed by applications efficiently.

Keywords

Cloud, Information, Resources, Sensors, Sensor Profiles, Scalability, Web Services.

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C. Menaka ¹, R. S. Ponmagal ²

Affiliations
1 Dept. of CS, St. Claret College, Bangalore, IN
2 Dept. of CSE, Dr. M.G.R. Educational and Research Institute, University, Chennai, IN

Abstract

Presently the users can store their information in a remote server and utilize the required services from collective computing resources dynamically without maintaining large amount of information in their local servers. This leads to the concept of cloud computing. Hospital Information system such as Telemedicine is an important application which is recently gaining momentum on cloud. As telemedicine not only promises to dramatically reduce the costs, but at the same time it makes access to care easier for patients and makes more revenue attainable for practices. Despite cloud's attractiveness, it has got tremendous security concerns including accessibility issues, user authentication, confidentiality concerns, and verification of data integrity, risk identification and mitigation, as well as insider threats from cloud provider staff. Precise identification of the patient/clinician during authentication process is a vital requirement for telemedicine cloud services as it involves sensitive physiological data. This paper proposes a secure cloud architecture which includes an authentication system for telemedicine cloud using a set of different unobtrusive physiological sensors (ECG) and web camera that continuously authenticate the identity of the user. This new type of authentication is called dynamic authentication. In the proposed Architecture auditing of the data providers are also included using third Party Auditing (TPA).

Keywords

Authentication, Cloud, TPA, Telemedicine.

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G. Dhineshkumar ¹, R. S. Ponmagal ¹, P. Dineshkumar ¹

Affiliations
1 Department of CSE, Dr. M.G.R. Educational and Research Institute University, Chennai, IN

Abstract

Administration recommender frameworks have been demonstrated as important apparatuses for giving fitting suggestions to clients. In the most recent decade, the measure of clients, administrations and online data has developed quickly, yielding the huge information examination issue for administration recommender frameworks. Subsequently, conventional administration recommender frameworks frequently experience the ill effects of adaptability and wastefulness issues when transforming or dissecting such expansive scale information. In addition, the majority of existing administration recommender frameworks show the same evaluations and rankings of administrations to diverse clients without considering various clients' inclination, and thusly neglects to meet clients' customized prerequisites. In this paper, we propose a Keyword-Aware Service Recommendation system, named KASR, to address the above difficulties. It goes for showing a customized administration suggestion rundown and prescribing the most fitting administrations to the clients adequately. In particular, catchphrases are utilized to show clients' inclination, and a client based Collaborative Filtering calculation is received to create proper suggestions. To enhance its versatility and effectiveness in enormous information environment, KASR is actualized on Hadoop, a broadly received dispersed processing stage utilizing the MapReduce parallel handling ideal model. At long last, broad tests are directed on genuine information sets, and results exhibit that KASR fundamentally enhances the exactness and adaptability of administration recommender frameworks over existing methodologies.

Keywords

Recommender System, Preference, Keyword, Big Data, Map Reduce, Hadoop.

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S. Nalini Poornima ¹, R. S. Ponmagal ¹

Affiliations
1 Dept. of CSE, IN

Abstract

The main aim of the cloud is to store boundless data with location independence. Once the data is bring in contact with the cloud it is known to be an outsourced data. This proposed work safeguards the outsourced data in cloud storage against degradation, malicious attacks, and malwares and stealth viruses. Since the users don’t have any control over the cloud, cloud admin takes care of protecting the data over a period of time. But now the scenario has been changed .No more the data owners stay online. Thus to lower the burden of the data owners to monitor continuously, a public auditing scheme has been introduced. This comprises of a third party auditor and a semi-trusted proxy. Regenerating code simply means the exact replication of the data which plays a vital role here. The privacy preservation of the data and the security will be assured in this proposed system.

Keywords

Cloud Admin, Public Auditing, Regenerating Codes, Semi-Trusted Proxy, Third Party Auditor.

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V. Srividhya ¹, K. Sujatha ¹, R. S. Ponmagal ²

Affiliations
1 EEE/CSE Department, Center for Electronics, Automation and Industrial Research (CEAIR), Dr. M.G.R. Educational & Research Institute, Maduravoyal, Chennai, Tamil Nadu, IN
2 EEE Department, Meenakshi College of Engineering, Maduravoyal, Chennai – 560064, Tamil Nadu, IN

Abstract

Objective of the Work: The highlight of this research work is to discover the ethylene gas level used for ripening of fruits by detecting ethylene gas (C2H4 in ppm) level employing soft sensor built using image processing and Artificial Neural Networks (ANN) algorithms. Methods/Statistical Analysis: The proposed method relies on the color which denotes the various stages in ripening and in turn indicates the amount of ethylene gas required. The changes in color, texture, intensity variation, mean, variance and standard deviation extracted from the images are the features which enable the personnel to determine the amount of ethylene gas. The Feed Forward Neural Network (FFNN) is used for ethylene gas estimation. This is made possible using Back Propagation Algorithm (BPA) for training the FFNN. As a part of image processing the intensity values in color images and its variation are tracked by dithering which is used as a unique feature input to train the FFNN. Major Findings: The novelty of the proposed method depends on the FFNN estimating the ethylene gas needed for ripening process in a feed forward fashion thereby providing the precision and recall values spontaneously for every instance. Application/Improvements: Earlier a circuit with capacitance model is used to generate ethylene gas for this purpose. Nearly 51 images are considered for training and testing respectively. Testing and confirmation result shows the required precision and recall level are in range of 80 to 89% and 100% respectively.

Keywords

Back Propagation Algorithm, Ethylene Gas, Feed Forward Neural Network Feature Extraction, Image Processing.

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