Topic
- Computing and Processing
- Components, Circuits, Devices and Systems
- Communication, Networking and Broadcast Technologies
- Power, Energy and Industry Applications
- Signal Processing and Analysis
- Robotics and Control Systems
- General Topics for Engineers
- Fields, Waves and Electromagnetics
- Engineered Materials, Dielectrics and Plasmas
- Bioengineering
- Transportation
- Photonics and Electrooptics
- Engineering Profession
- Aerospace
- Geoscience
- Nuclear Engineering
- Career Development
- Emerging Technologies
- Telecommunications
- English for Technical Professionals
Julio C. S. Dos Anjos
Also published under:Julio C. S. Anjos
Affiliation
Institute of Informatics, Federal University of Rio Grande do Sul, UFRGS/PPGC, Porto Alegre, Brazil
Topic
Big Data,Cloud Infrastructure,Data Transfer,Single Cloud,Apache Spark,Batch Size,Big Data Analytics,Big Data Applications,Big Data Stream,Chunk Size,Cloud Computing,Cloud Environment,Cloud Providers,Computational Memory,Computational Resources,Data Block,Data Center,Data Distribution,Data Partitioning,Data Processing,Data Sources,Data Storage,Data Strategy,Data Streams,Data-intensive Computing,Distribution Strategy,Expectation Maximization,Hadoop Distributed File System,High Latency,Huge Volume Of Data,Hybrid Infrastructure,Hybrid System,Internet Of Things,Load Balancing,Load Data,Local Area Network,Low Latency,Low Throughput,Map Tasks,MapReduce,Microsoft Azure,Model Predictive Control,Multiple Cloud,Network Latency,Phase Map,Pool Of Resources,Private Cloud,Public Cloud,Stream Processing,Task Allocation,
Biography
Julio C. S. Dos Anjos received the bachelor’s degree in electrical engineering with an emphasis on electronics from the Pontifical Catholic University of Rio Grande do Sul (PUC/RS), in 1991, the master’s degree in computer science from the Federal University of Rio Grande do Sul, in 2012, and the Ph.D. degree in computer science from the Federal University of Rio Grande do Sul (UFRGS/RS), in 2017. He has been holding a postdoctoral position in computer science with UFRGS since 2017. He is currently a Researcher in the areas of big data, MapReduce and streaming processing, distributed and heterogeneous systems, hybrid infrastructures, and big data analytics with machine learning and deep learning.