Search
Search Results
-
MapReduce scheduling algorithms in Hadoop: a systematic study
Hadoop is a framework for storing and processing huge volumes of data on clusters. It uses Hadoop Distributed File System (HDFS) for storing data and...
-
MapReduce with Deep Learning Framework for Student Health Monitoring System using IoT Technology for Big Data
The efficient well-being and health interventions of students are ensured by better knowledge of student’s health and fitness factors. Effective...
-
A MapReduce hybridized spotted hyena optimizer algorithm for travelling salesman problem
The Traveling Salesman (TSP) problem is one of the most common basic problems in the nondeterministic polynomial problems (NP-hard) category. TSP is...
-
Adaptive-CSSA: adaptive-chicken squirrel search algorithm driven deep belief network for student stress-level and drop out prediction with MapReduce framework
Stress is correlated with various illnesses that include diabetes, depression, and other chronic diseases and plays an important role in the...
-
MapReduce-based distributed tensor clustering algorithm
Cluster analysis is one of the most fundamental methods in data mining, and it has been widely used in economics, social sciences and computer...
-
A multi-threaded particle swarm optimization-kmeans algorithm based on MapReduce
The particle swarm optimization-K-Means algorithm is proposed by the related researchers to improve the clustering accuracy of the K-Means algorithm....
-
An optimized SVM-RFE based feature selection and weighted entropy K-means approach for big data clustering in mapreduce
In the digitalized world, efficient big data clustering is necessary for massive data generation. The clustering algorithm plays an important role in...
-
Reinforcement learning based energy efficient resource allocation strategy of MapReduce jobs with deadline constraint
Big Data applications require more energy consumption to process a massive volume of data in a heterogeneous environment. Moreover, reducing energy...
-
CLQLMRS: improving cache locality in MapReduce job scheduling using Q-learning
Scheduling of MapReduce jobs is an integral part of Hadoop and effective job scheduling has a direct impact on Hadoop performance. Data locality is...
-
An Efficient Fault Tolerance Strategy for Multi-task MapReduce Models Using Coded Distributed Computing
MapReduce is a programming framework designed for processing and analyzing large volumes of data in a distributed computing environment. Despite its...
-
Towards Efficient Ensemble Hierarchical Clustering with MapReduce-based Clusters Clustering Technique and the Innovative Similarity Criterion
Today, data plays an important and fundamental role in our daily lives. The increasing growth of data production has led to the big data revolution....
-
MapReduce distributed parallel computing framework for diagnosis and treatment of knee joint Kashin-Beck disease
To improve the accuracy and computational efficiency of the MapReduce distributed parallel computing framework, thereby mining the diagnosis and...
-
Efficient parallel derivation of short distinguishing sequences for nondeterministic finite state machines using MapReduce
Distinguishing sequences are widely used in finite state machine-based conformance testing to solve the state identification problem. In this paper,...
-
A Scalable Similarity Join Algorithm Based on MapReduce and LSH
Similarity joins are recognized to be among the most useful data processing and analysis operations. A similarity join is used to retrieve all data...
-
HTD: heterogeneous throughput-driven task scheduling algorithm in MapReduce
As one of the most popular parallel data processing models, data analysis system MapReduce has been widely used in many fields. Task scheduling is...
-
Scalable Centroid Based Fuzzy Min-Max Neural Network Ensemble Classifier Using MapReduce
Fuzzy Min-Max Neural Network (FMNN) Classifier has acquired significance owing to its unique properties of single-pass training, non-linear...
-
Budget Constraint Scheduler for Big Data Using Hadoop MapReduce
Over the past few years, data production has increased significantly due to the growth of Internet-dependent technologies. Big data allows for an...
-
An intelligent surveillance video analytics framework using NACT-Hadoop/MapReduce on cloud services
Video analytics has gradually increased in recent years. The intelligent CCTV cameras in public places, you-tube videos, etc. generate an enormous...
-
MuSe: a multi-level storage scheme for big RDF data using MapReduce
Resource Description Framework (RDF) model owing to its flexible structure is increasingly being used to represent Linked data. The rise in amount of...
-
A MapReduce-based K-means clustering algorithm
The partitioning-based k -means clustering is one of the most important clustering algorithms. However, in big data environment, it faces the problems...
