Research Areas of the Faculty
Distributed Systems and Information Security
This research group addresses issues in supporting emerging network infrastructures, with particular focus on wireless mobile ad-hoc networks, sensor networks, peer-to-peer overlays, grid and cloud computing. Research is centered around the design and analysis of networking protocols and algorithms to support efficient and reliable communication. The groups research focuses on application of graph algorithms to improve the lookup efficiency in P2P overlays, assessing the impact of P2P traffic on IDS/IPS designs, energy-aware routing algorithms for wireless sensor networks, adaptive load distribution algorithms, distributed mutual exclusion over MANETs. The group also works in grid computing security and access control modeling, wherein the focus is about modeling authorization frameworks for single domain and multi-domain grid environments. Ranking based cross domain role mapping algorithms are used in multi-domain grid systems. Cloud computing research of this group proposes solutions for access control, trust based generic security framework, and cloud forensics. In cloud forensics, the researchers have proposed ideas for regenerating events using system snapshots for forensic analysis.
Faculty: Dr Chittaranjan Hota, Dr Geetha M, Abhishek Thakur, Digambar Povar, Rakhee
Data Management
In a sensor network, sensor nodes monitor and collect physical data without any human intervention for weeks or months. A node should consume less power for the above said operations for keeping the battery life longer. Sensor deployments must be energy efficient, and hence energy efficient data management strategies are necessary. This group is working on issues like efficient data storage, caching, and query techniques for sensory data. This group also works on data dissemination, and management in Information systems.
Faculty: Dr Gururaj R, Kavitha K
Software Engineering
This research group focuses on enhancing software quality and productivity by applying data mining algorithms to various software engineering tasks. As the IT industry is getting matured there is so much of data representing experience and knowledge of systems that is available with the providers and this group addresses several challenges posed during the mining of software engineering data. Secondly, the group also focuses on the implementation challenges of cloud computing in particular SaaS (Software as a Service) model. The main challenges in SaaS are design and development, revenue models, sales and compensation, customer service, support and maintenance and the group is working on generic products that take care of licensing and billing of all services offered by a SaaS provider.
Faculty: Dr. N.L.Bhanu Murthy, C R Prasanna
Artificial Intelligence
This research group focuses on three main areas of research: Artificial Intelligence, and data mining. This group uses Data Mining and AI techniques to solve and create innovative and efficient solutions to complex problems like Smart playlist generation, Web Index Advertising Engine and Design and implementation of focused crawler for searching collaborators. In the playlist generation we attempt to suggest similar songs based on the seed songs selected by the user. Hybrid filtering techniques are used for finding similarity between the seed songs and the songs in the training set. In Web Index Advertising research, the group examines behavioural/contextual data of online consumers (who surf web pages) and also works on publishing more relevant advertisements efficiently improving user satisfaction over just in time, place and need parameters.
Faculty: Dr Aruna M, Mr. K.C.S.Murti, Prafulla K
Computer Graphics
The primary area of research of this group is in computer graphics, computational geometry and its applications in solving different scientific and engineering problems. One of the focus areas of work is mesh generation which spans variety of problem domains starting from CAD Model meshing to fluid flow simulation. In particular Delaunay based methods for mesh generation are deeply studied, along with their scalability issues and the quality of results obtained in actual simulation process. Problems such as mesh modification and optimization are also researched. Along with mesh generation, geometric reconstruction of boundary representation and their applicability for solving different scientific problem such as 3D surface reconstruction from different kind of volume data is also researched.
Dr Tathagata Ray