Hadoop IEEE Projects 2016-2017
Hadoop IEEE Projects 2016-2017, Hadoop IEEE Projects Titles 2016-2017. We are offering ieee projects 2016-2017 in latest technology like Java ieee projects, dotnet ieee projects, android ieee projects, embedded ieee projects, matlab ieee projects, digital image processing ieee projects, vlsi ieee projects, hadoop ieee projects, power electronics ieee projects, power system ieee projects, mechanical ieee projects, civil projects ieee projects. IEEE Master is a unit of LeMeniz Technologies. We guide all final year M.E/M.Tech, B.E/B.Tech, MPhil, MCA, BCA, M.Sc, B.Sc, and Diploma students for their Academic Projects to get best results.
S.No | Code | Hadoop IEEE Projects Titles | Year |
Wide Area Analytics for Geographically Distributed Datacenters | |||
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 | |||
H2Hadoop: Improving Hadoop Performance using the Metadata of Related Jobs | |||
Adaptive Replication Management in HDFS based on Supervised Learning | |||
CaCo: An Efficient Cauchy Coding Approach for Cloud Storage Systems | |||
Distributed In-Memory Processing of All k Nearest Neighbor Queries | |||
clustering of electricity consumption behavior dynamics toward big data applications | |||
Processing Cassandra Datasets with Hadoop-Streaming Based Approaches | |||
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 | |||
Hadoop Performance Modeling for Job Estimation and Resource Provisioning | |||
Novel Scheduling Algorithms for Efficient Deployment of MapReduce Applications in Heterogeneous Computing Environments | |||
K Nearest Neighbour Joins for Big Data on MapReduce: a Theoretical and Experimental Analysis | |||
On Traffic-Aware Partition and Aggregation in MapReduce for Big Data Applications | |||
Protection of Big Data Privacy | |||
Optimization for Speculative Execution in Big Data Processing Clusters | |||
RFHOC: A Random-Forest Approach to Auto-Tuning Hadoop’s Configuration |
Hadoop IEEE Projects 2016-2017
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