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intensive computing

Data classification algorithm for data intensive computing environments

Data classification algorithm for data intensive computing environments

... data-intensive computing involve expanding and improving classic outlier mining ...data-intensive computing environ- ments is of great ...

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Big Data Clustering Using Heuristic Data Intensive Computing and Self Organizing Maps

Big Data Clustering Using Heuristic Data Intensive Computing and Self Organizing Maps

... Data Intensive Computing (HDIC) Heuristic means set of rules that are used to increase the probability of solving a ...Data Intensive Computing is a class of parallel computing ...

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Data Management in Data Intensive Computing Systems - A Survey

Data Management in Data Intensive Computing Systems - A Survey

... data intensive computing capabilities from raw data processing to high performance query processing and data ...specific computing paradigm (programming model-machine ...

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F l u χ: a quality-driven dataflow model for data intensive computing

F l u χ: a quality-driven dataflow model for data intensive computing

... of intensive data processing, address- ing the evaluation of air quality, pollution and health risks, for a city based on sensory data, gathered asyn- chronously, from thousands of ...

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Case Studies in Data Intensive Computing: Large Scale DNA Sequence Analysis as the Million Sequence Challenge and Biomedical Computing

Case Studies in Data Intensive Computing: Large Scale DNA Sequence Analysis as the Million Sequence Challenge and Biomedical Computing

... Many areas of science are seeing a data deluge coming from new instruments, myriads of sensors and exponential growth in electronic records. We take two examples – one the analysis of gene sequence data (35339 Alu ...

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Biomedical Case Studies in Data Intensive Computing

Biomedical Case Studies in Data Intensive Computing

... As data sets increase in size, we expect some applications to require particularly robust algorithms that are as insensitive as possible to well known difficulties such as “trapping in local minima”. This increases ...

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Data Intensive Computing for Bioinformatics

Data Intensive Computing for Bioinformatics

... Dimension reduction and follow-up visualization of large and high-dimensional data in low dimensions is a task of growing importance in many fields of data mining and information retrieval to understand data structures, ...

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A Review of Replica Replacement Techniques in Grid Computing and Cloud Computing

A Review of Replica Replacement Techniques in Grid Computing and Cloud Computing

... data-intensive computing platform, encountered in some grid and cloud computing applications, includes numerous tasks that process, transfer or analysis large data ...distributed computing ...

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Implementation of Log Based Analytical Engine using Hadoop and Spark

Implementation of Log Based Analytical Engine using Hadoop and Spark

... [8] N. Ramasubramanian, Srinivas V.V. :- The stream logging application which is computed over a distributed _le system can be used to facilitate applications that involve transaction based computing. Since, the ...

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Analysis on Optimization of Computation Load in Mobile Device using Mobile Cloud

Analysis on Optimization of Computation Load in Mobile Device using Mobile Cloud

... compute intensive rendering is performed on cloud servers instead of on mobile devices, can be a complete result oriented approach to enable rich rendering based multimedia applications on battery and CPU ...

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A SOA based Resource Intensive and Data Aware (RIADA) Approach for Grid Computing

A SOA based Resource Intensive and Data Aware (RIADA) Approach for Grid Computing

... Each has their beginnings in academia and study wherever complicated diagnostic strategies running around big knowledge models were getting the norm. The surfacing of computational Grids as recent high-performance ...

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Supporting End to End Social Media Data Analysis with the IndexedHBase Platform

Supporting End to End Social Media Data Analysis with the IndexedHBase Platform

... data intensive applications evolve, many research projects involving Big Data require efficient extraction and analysis of specific data subsets, rather than the whole ...

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An Energy Efficient QoS Based Replication Strategy

An Energy Efficient QoS Based Replication Strategy

... Cloud computing is a model that relies on sharing computing resources rather than having local servers or personal devices to handle ...years.Cloud computing provides the tools and technologies to ...

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Cloud-based Geophysical Inversion Modeling Using GNU Octave and MatlabMPI on Amazon EC2

Cloud-based Geophysical Inversion Modeling Using GNU Octave and MatlabMPI on Amazon EC2

... Cloud computing has opened up new avenues for the scientific researchers with limited resources to do complicated simula- ...cloud computing is suitable for modeling and simulation, we first describe how to ...

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Data Intensive Dynamic Scheduling Model and Algorithm for Cloud Computing Security

Data Intensive Dynamic Scheduling Model and Algorithm for Cloud Computing Security

... From the above mentioned view of researchers we can cite that the security of data at rest and in transmission is one of the most important issues in cloud computing. The security goals that are related to data ...

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HYBRID WORKFLOW POLICY MANAGEMENT FOR HEART DISEASE IDENTIFICATION DONG-HYUN KIM *1 , WOO-RAM JUNG 1, CHAN-HYUN YOUN1

HYBRID WORKFLOW POLICY MANAGEMENT FOR HEART DISEASE IDENTIFICATION DONG-HYUN KIM *1 , WOO-RAM JUNG 1, CHAN-HYUN YOUN1

... We propose a Hybrid Workflow Policy Management system to handle SLA guarantee issues in Grid workflow management area. In this proposed system, Grid workflows are managed and scheduled just in-time in terms of a ...

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EMERGING PARADIGMS FOR ANALYZING, PROCESSING AND MAKING SENSE OF LARGE HETEROGENEOUS DATASETS.

EMERGING PARADIGMS FOR ANALYZING, PROCESSING AND MAKING SENSE OF LARGE HETEROGENEOUS DATASETS.

... Challenges arise from both themes of research. The Web is heterogeneous: data lives in various formats that are best modeled in different ways. Effectively extracting information requires careful design of algorithms for ...

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Extending Data Facilities using the Framework –
HadoopMapReduce
  M.Sanjay  ,  A.Kumaravel  Abstract PDF  IJIRMET160208001

Extending Data Facilities using the Framework – HadoopMapReduce M.Sanjay , A.Kumaravel Abstract PDF IJIRMET160208001

... performance computing and Grid Computing Communities have been doing large scale data processing by using API's as Message Passing ...Performance Computing distributes the work across the cluster of ...

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ARCHITECTURE AND PERFORMANCE OF RUNTIME ENVIRONMENTS FOR DATA INTENSIVE SCALABLE COMPUTING

ARCHITECTURE AND PERFORMANCE OF RUNTIME ENVIRONMENTS FOR DATA INTENSIVE SCALABLE COMPUTING

... Performance Computing (HPC) applications based on MPI, have long lifespans in the applications; most of the time, they utilize high performance communication infrastructures to communicate fine grain messages with ...

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LATEST DATA STORAGE TECHNIQUES IN CLOUD COMPUTING FOR DATA INTENSIVE APPLICATIONS

LATEST DATA STORAGE TECHNIQUES IN CLOUD COMPUTING FOR DATA INTENSIVE APPLICATIONS

... cloud computing there are many possibilities of hardware failure as well as software ...data- intensive applications unable to read data from disks ...data intensive applications in cloud ...

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