The term Big Data commonly refers to enormous bulk of data that is bring out by human (genomes) from highly used digital devices like cameras, internet, mobile phones, sensors etc. One can predict many possible outcomes such as human nature, his interest etc. By developing advanced analytics on the top of big data. Methods like encryption and decryption helps to address many issues related to Molecular DNA big data before making the use of it. Analysing and finalizing better technical solution for specific application is all time astonishing issue from the developers and analysts perspective. Xampp server tries to give the base for big data storage by the help of MySQL, PHP and Perl. Along with mentioned technologies there are many more data storage and processing technologies evolved related to Hadoop. This paper contains the survey on recent Molecular DNA big data technologies which gives the performance characteristic of each technique.

Kannadasan R

Department of Software Systems

School of Computer Science and Engineering

Vellore Campus

Arnold Emerson I

Department of Biotechnology

School of Bio Sciences and Technology

Saleembasha M.S

Fulltext

Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

Procedia Computer Science

Context aware applications are seeking for the technologies that provides regularly available data between internal and external environments. Wireless access infrastructure is integrating real time data and heterogeneous devices to establish ubiquitous communication. A wireless sensor network (WSN) is primarily undertaking remote monitoring of any task in any sensing field further to extend for context fetching and refining to collect essential context information for pervasive environment. The applications are well utilized on context observation and interpretation for mobile users. The proposed method assists to combine various basic low level contexts to provide reliable decision making in the pervasive environment using sensor networks and context aware computing. Pervasive computing has powerful and influencing factors to establish dynamic and smart environment with its dominant features in the backend. Pervasiveness provides the regulated smart interactions and interfaces together to avail the information for various applications. Using rich context for event notification than simple position and time, aim to bring automated decision along with accuracy information. The proposed model also facilitate users and group members to create and submit an event. It provides ability to submit an event using a various mode of input. © 2018 The Authors. Published by Elsevier Ltd.

Contexts enabled Decision Making using sensors to perceive pervasive environment

Cloud is referred to as a collection of infrastructure services, such as Infrastructure as a service (IaaS) and Platform as a service (PaaS), which are made available to us for utilization by various organizations in which the key factor is virtualization of data as it allow the user to manage, handle and compute a large number of tasks very easily. By referring to Cloud technologies we mean runtime such as Hadoop, Dryad and other Map Reduce frameworks. In this paper we would analyse the above mentioned software's and techniques for the cloud system by comparing them on the basis of its processing speed, its data handling capacity, the nature of user friendliness. We would discuss large scale data analysis using different implementations on the above mentioned tools and after that we would give a performance analysis of these tools on the given implementation like Cap3, HEP, Cloudburst. © 2018 The Authors. Published by Elsevier Ltd.

High Performance Parallel Computing with Cloud Technologies

This paper shows a compiler machine for adaptable figuring. Our technique assembles the flexibility and comfort in a way that grants to port the structure to different centers with an irrelevant effort. In light of a present arrangement stream, we endeavor to accomplish another tier of handiness in the way of exploring and dividing programs written in C on most hoisted able to be done delineation tier. We show that the examination on this level is more successful than on lower ones as a result of usage of more communicative fabricate of programming. The better examination comes to fruition merged with Static single assignment based estimation for data way creation might provoke upper game plan nature of the last structure setup. © 2017 IEEE.

Journal	Data powered by TypesetProcedia Computer Science
Publisher	Data powered by TypesetElsevier BV
ISSN	1877-0509
Open Access	Yes