2016-2017 BIG DATA HADOOP PROJECTS



2016 - 2017 HADOOP IEEE BIG DATA FINAL YEAR Projects
A Big Data Clustering Algorithm for Mitigating the Risk of Customer Churn
A Parallel Patient Treatment Time Prediction Algorithm and Its Applications in Hospital Queuing-Recommendation in a Big Data Environment
Adaptive Replication Management in HDFS based on Supervised Learning
CaCo: An Efficient Cauchy Coding Approach for Cloud Storage Systems
Clustering of Electricity Consumption Behavior Dynamics toward Big Data Applications
Distributed In-Memory Processing of All k Nearest Neighbor Queries
Dynamic Job Ordering and Slot Configurations for MapReduce Workloads
Dynamic Resource Allocation for MapReduce with Partitioning Skew
FiDoop-DP: Data Partitioning in Frequent Itemset Mining on Hadoop Clusters
H2Hadoop: Improving Hadoop Performance using the Metadata of Related Jobs
Hadoop Performance Modeling for Job Estimation and Resource Provisioning
K Nearest Neighbour Joins for Big Data on MapReduce: a Theoretical and Experimental Analysis
Novel Scheduling Algorithms for Efficient Deployment of MapReduce Applications in Heterogeneous Computing Environments
On Traffic-Aware Partition and Aggregation in MapReduce for Big Data Applications
Optimization for Speculative Execution in Big Data Processing Clusters
Processing Cassandra Datasets with Hadoop-Streaming Based Approaches
Protection of Big Data Privacy
RFHOC: A Random-Forest Approach to Auto-Tuning Hadoop’s Configuration
Service Rating Prediction by Exploring Social Mobile Users’ Geographical Locations
Wide Area Analytics for Geographically Distributed Datacenters