Data Intensive Computing Research Lab
Organisation Name
Data Intensive Computing Research Lab
Dean
Website
Description
The Data Intensive Computing Research Lab (DICL) was established by Dr. Herodotos Herodotou as part of the Department of Electrical Engineering, Computer Engineering and Informatics at the Cyprus University of Technology. Research in the DICL lab revolves around three main research themes:
1. Large-scale data processing systems (e.g., MapReduce, Spark)
2. Centralized and distributed database systems
3. Cloud computing (compute, storage, and networking)
In particular, the lab focuses on innovating and solving technically challenging problems related to all operational aspects of large-scale data intensive systems, including resource management, application performance, automated tuning, information management, and multi-tenancy. In addition, we strive at enabling flexible ways to store, organize, query, and browse rich data sets containing both structured and unstructured data as well as reducing the total cost of ownership of information management systems. At the same time, the group is interested in applying cloud and database techniques in other areas like maritime informatics, smart power grid/microgrids, scientific computing, bioinformatics, and social computing.
1. Large-scale data processing systems (e.g., MapReduce, Spark)
2. Centralized and distributed database systems
3. Cloud computing (compute, storage, and networking)
In particular, the lab focuses on innovating and solving technically challenging problems related to all operational aspects of large-scale data intensive systems, including resource management, application performance, automated tuning, information management, and multi-tenancy. In addition, we strive at enabling flexible ways to store, organize, query, and browse rich data sets containing both structured and unstructured data as well as reducing the total cost of ownership of information management systems. At the same time, the group is interested in applying cloud and database techniques in other areas like maritime informatics, smart power grid/microgrids, scientific computing, bioinformatics, and social computing.
results