IEEE Big Data Projects
IEEE Big Data Projects offer par-excellence way to succeed in your academics with the ultimate achievements. Our Team of world certified experts is created our organization as a “universal Top Organization” by their collaborative work. We offer best project and research guidance for predominance of students and research members from various departments such as Electrical and Communication Engineering, Electrical and Electronic Engineering, Computer Science, Information Technology, and Computer Application. On these days, we are serving immense of students and researchers by our standardized IEEE Big Data Projects. Daily working is always leaded to exceptional results. For further information, you can contact out experts without any hesitation.
IEEE Big Data Projects
IEEE Big Data Projects is our top-notch service which is started for the purpose of enriches scholars profile to get outstanding achievements in their future. Our certified big data professionals grant important information about latest algorithms, strategies, mechanisms, big data supported tools, process including structured v Unstructured Data, R, Streaming Processing, Machine Learning, NoSQL, Internet of Things, ETL, Hadoop, Distributed File System, Data Lake and more for upgrade scholars knowledge big data research.
IEEE Big Data Projects associated with the following challenges, including:
- Relevant Vs. Irrelevant Data Recognition
- Distributed Data Collection
- Accuracy, timeliness and completeness of data
- Flexible and insightful presentation
- Intelligent analysis
- Economic and Scalable Data implementation
- Efficient transfer and storage
Big Data based Research Areas:
- Scalable, Parallel and Distributed Algorithms
- Big Data Visualization
- Evaluation Technologies
- Data Streaming Processing
- Data Mining Algorithms in Non-Traditional Formats
- Format mining and Heterogeneous Sources
- New Programming Model Beyond Hadoop
- Explore Applications of Big Data
- Issues of Big Data related to clouds and streaming system
- Autonomic Cloud Provisioning
- Elastic Techniques for Hadoop Processing
- Autonomic Resource Management
- Runtime configuration strategies
- Self-adaptive Scheduling and Placement techniques
Application Fields of Big Data:
- Social Media
- Internet of Things
- Smart Grid
- Web Intelligence
- Astrophysics
- Social networks
- Humanities
- Climate Change
- Geoscience applications
- Smart Transportation Systems
- Stock Market Analysis
- Large Scale Recommendation Systems
- Scalable Cloud Data Management
- Social Media Systems
- Biomedical Informatics
- Advanced Manufacturing
- Sustainable Development
- Privacy and Security Applications
- Social Network Systems
- Scientific Data Mining
- Supply and Manufacturing Chains
- Environmental And Other Large Mining Applications
IEEE Big Data Projects Focus on the following Themes:
- Detect Quasi Periodicities in ECG Signals as a Anesthesia Monitor Depth Using Phase Rectified Signal Averaging
- K-Means Clustering Algorithm for Bengali Documents by an Extractive Text Summarization Mechanism
- Analyze Security Pitfalls for Wireless Sensor Networks Using Practical Access Control Protocols
- Energy Efficiency Resource Allocation Based on Terminal in OFDMA Based Wireless Multicast Systems
- Design and Implement Big Data and Internet of Things Based Intelligent HVAC System
- Latent Embedding for Structured Lifelong Learning Topic Model
- Parallel Processing to Massive Industrial Data Analysis Using MapReduce Paradigm
- Improve Large Scale Matrix Multiplication Concurrency Execution on Distributed Data Parallel Paradigms
- Efficient Key Management in Dynamic Sensor Networks for Big Data Gathering
- Predicting Requests Based Cloud Bursting Strategy for Business Critical Web Systems
- Big Data Processing to Improve Shuffle I/O Performance Using Hybrid Storage
- Framework Based on Machine Learning for Massive Scale Image Data Verification and Validation
- Reliable Cascade Computation Decoding and Physical Layer Network Coding for Non- Orthogonal Multiple Access Scheme
- MLC NAND Flash Memory Storage Frameworks Using Block Level Log Block Management Strategy
- Bidirectional Local Search and Non-Dominated Sorting Based Multi Objective Evolutionary Algorithm for Big Data
