Hadoop Projects

Hadoop is an open source distributed processing framework that manages data processing and storage for big data applications running in clustered systems. It is at the center of a growing ecosystem of big data technologies that are primarily used to support advanced analytics initiatives, including predictive analytics, data mining and machine learningapplications. Hadoop can handle various forms of structured and unstructured data, giving users more flexibility for collecting, processing and analyzing data than relational databases and data warehouses provide.

• FiDoop: Parallel Mining of Frequent Itemsets Using MapReduce
• Dache: A Data Aware Caching for Big-Data Applications Using the MapReduce Framework
• ClubCF: A Clustering-based Collaborative Filtering Approach for Big Data Application
• Big Data Challenges in Smart Grid IoT (WAMS) Deployment
• A data mining framework to analyze road accident data
• A Time Efficient Approach for Detecting Errors in Big Sensor Data on Cloud
• Big data, big knowledge: big data for personalised healthcare
• Deduplication on Encrypted Big Data in Cloud
• Processing Geo-Dispersed Big Data in an Advanced MapReduce Framework
• Recent Advances in Autonomic Provisioning of Big Data Applications on Clouds
• Privacy Preserving Data Analysis in Mental Health Research
• BFC: High-Performance Distributed Big-File Cloud Storage Based On Key-Value Store
• Performance Analysis of Scheduling Algorithms for Dynamic Workflow Applications
• PaWI: ParallelWeighted Itemset Mining by means of MapReduce
• Building a Big Data Analytics Service Framework for Mobile Advertising and Marketing
• Secure Sensitive Data Sharing on a Big Data Platform
• Load Balancing for Privacy-Preserving Access to Big Data in Cloud
• Enabling Efficient Access Control with Dynamic Policy Updating for Big Data in the Cloud
• MRPrePost-A parallel algorithm adapted for mining big data
• Privacy Preserving Data Analytics for Smart Homes
• Authorized Public Auditing of Dynamic Big Data Storage on Cloud with Efficient Verifiable Fine-grained Updates
• KASR: A Keyword-Aware Service Recommendation Method on MapReduce for Big Data
• Cost Minimization for Big Data Processing in Geo-Distributed Data Centers
• A Micro-video Recommendation System Based on Big Data
• Twitter data analysis and visualizations using the R language on top of the Hadoop platform
• QoS-Aware Data Replications and Placements for Query Evaluation of Big Data Analytics
• Traffic-aware Task Placement with Guaranteed Job Completion Time for Geo-distributed Big Data
• Online Data Deduplication for In-Memory Big-Data Analytic Systems
• Novel Common Vehicle Information Model (CVIM) for Future Automotive Vehicle Big Data Marketplaces
• Holistic Perspective of Big Data in Healthcare
• Focusing on a Probability Element: Parameter Selection of Message Importance Measure in Big Data
• CryptMDB: A Practical Encrypted MongoDB over Big Data
• Cost Aware Cloudlet Placement for Big Data Processing at the Edge
• Big-Data-Driven Network Partitioning for Ultra-Dense Radio Access Networks
• Big Data Set Privacy Preserving through Sensitive Attribute-based Grouping
• Big Data Driven Information Diffusion Analysis and Control in Online Social Networks
• Big Data Analytics of Geosocial Media for Planning and Real-Time Decisions
• An Approximate Search Framework for Big Data
• A Reliable Task Assignment Strategy for Spatial Crowdsourcing in Big Data Environment
• A Queuing Method for Adaptive Censoring in Big Data Processing
• Achieving Efficient and Privacy-Preserving Cross-Domain Big Data Deduplication in Cloud
• A Profile-Based Big Data Architecture for Agricultural Context
• Review Based Service Recommendation for Big Data