[PDF] Top 20 AN EFFICIENT TRAFFIC-AWARE SEPARATION AND AGGRIGATION USING MAPREDUCE FOR BIG DATA APPLICATIONS
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AN EFFICIENT TRAFFIC-AWARE SEPARATION AND AGGRIGATION USING MAPREDUCE FOR BIG DATA APPLICATIONS
... network traffic because it ignores network topology and data size associated with each ...intermediate data of three keys K1, K2, and K3 are denoted by rectangle bars under each ...assigns ... See full document
7
Aggregation Methodology on Map Reduce for Big Data Applications by using Traffic-Aware Partition Algorithm
... ABSTRACT: Data clustering is an important data mining technology that plays a crucial role in numerous scientific ...cluster big data as the size of datasets has been growing rapidly to extra- ... See full document
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Network Traffic Separation and Aggregation in Mapreduce for Bigdata Applications
... intermediate data partition and aggregation in MapReduce to minimize network traffic cost for big data ...to big data, we design a distributed algorithm to solve the ... See full document
6
Traffic Aware Partition and Aggregation for Big Data Applications in Map Reduce
... to data partition, many efforts have been made on local aggregation, in-mapper combining and in-network aggregation to reduce network traffic within MapReduce ...of data to be shuffled and ... See full document
7
On Transit-Attentive Separation and Gathering in Mapreduce for Big data Application
... a MapReduce resource allocation system, to enhance the performance of MapReduce jobs in the cloud by locating intermediate data to the local machines or close-by physical ...network traffic in ... See full document
5
Reducing Network Traffic Cost For Big Data Applications With Using Distributed And Online Algorithms
... of MapReduce systems clearlydepends heavily on the scheduling of tasks belonging to thesethree ...of MapReduce jobs, they display blind eye to thenetwork visitors generated in the shuffle phase, which plays ... See full document
5
An Efficient Approach for Processing Big Data with Incremental MapReduce
... Hadoop MapReduce Framework, as Map Reduce lacks built-in-support for iterative programs HaLoop allows iterative applications to be assembled from existing Hadoop programs without modification, and ... See full document
5
A Study Of Traffic Aware Partition And Aggregation In Mapreduce For Big Data Applications
... Hadoop MapReduce framework that supports online aggregation is demonstrated, which allows users to see “early returns” from a job as it is being ...Locality aware resource allocation for mapreduce in ... See full document
6
On Traffic-Aware Partition and Aggregation in Mapreduce for Big Data Applications
... The MapReduce programming model simplifies large-scale data processing on commodity cluster by exploiting parallel map tasks and reduce ...of MapReduce jobs, they ignore the network traffic ... See full document
5
Optimized Mapreduce across Datacenter's Using Dache: a Data Aware Caching for Big-Data Applications
... of MapReduce jobs on a geo-distributed dataset across multiple ...of MapReduce jobs based on characteristics of the dataset, MapReduce jobs, and the datacenter ...possible data move has to be ... See full document
6
An Efficient Resource Aware Scheduling Algorithm for Mapreduce Clusters
... The MapReduce algorithm contains two important tasks, namely Map and ...of data and converts it into another set of data, where individual elements are broken down into tuples (key/value ...those ... See full document
7
Big Data Clustering Using Genetic Algorithm On Hadoop Mapreduce
... CLUSTERING USING HADOOP MAPREDUCE In this sub section we propose the format of GA we used for clustering based ...input data set is split according to the block size by the input ...are using ... See full document
5
Optimizing mapreduce functionality in big data using cache manager
... large data sets that is growing beyond the ability to manage and analysis using with the traditional data processing ...tools. Big data represents large and incremental volume of ... See full document
6
Big Data Processing Using Hadoop MapReduce Programming Model
... the applications and architecture built to support the data needsto be re- evaluated quite ...same data is re- evaluated with multiple angles and even though the original data is the same the ... See full document
6
Comparative Analysis Of Big Data Analytical Techniques Using Mapreduce
... support big data sets by paralleling the algorithms which can be implemented based on MapReduce framework of ...the data sets can be used mainly for sentiment analysis, by more filtering of ... See full document
6
Incremental Mapreduce In Big Data Environment
... for big data analysis. As new data and updates are being collected, the input data of a big data mining algorithm will gradually change, and the computed results will become ... See full document
6
An Efficient Method for Data Embedding and Image Encryption by using Dna and Chao’s Theory
... In [2], authors have proposed another encryption method for images in his work. The work mainly focus on RSA encryption. It is a public key cryptosystems. For an encryption to selected encryption key (two large prime ... See full document
7
Efficient UDP-Based Congestion Aware Transport for Data Center Traffic
... —Modern Data Centers (DCs) host hundreds of thou- sands of servers running diverse applications and ...these applications mandates distinct requirements such as latency and ...of efficient DC ... See full document
7
Internet-scale support for map-reduce processing
... Having the reducers receive all map replicas completely removes the server from the intermediate validation pro- cess. While this eliminates client-server intermediate file transfers, it also creates 2 significant ... See full document
17
International Journal of Computer Science and Mobile Computing
... files. Data files consist of records, each of which can be treated as a key- value ...Input data is partitioned and processed by Map processes, and their processing results are shaped into key-value pairs ... See full document
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