Professor, Dept. of Analytical Information Systems,
St Petersburg University.
Move away from any narrow interpretation of databases
Research interests are in the wide area of information management and include design and use of database systems, transaction management, indexing, data structures, query processing and optimization, performance tuning, and management of distributed heterogeneous information resources. He also worked in the areas of software engineering, application design, and transaction management in distributed mobile systems.
The aim of this effort is to provide low-latency stream procesing based on deterministic computational model with certain consistency guarantees based on declarative specifications and constraints. More details (2017-)
This is a joint project with the research group leaded by Dr. Dr.Manoj Kumar Shukla, Harcout Butler Technical University, Kanpur, India.
An efficient fine-grained based secure document access when big data are handled from public cloud networks is a challenging issue since the scheme utilizes more computation, communication and storage complexities. The proposed group key management utilizes less computational complexity by performing reduced cryptographic operations in the data owner and cloud users to update and recover the group key. In addition, the proposed scheme also minimizes the storage complexity of the cloud users. To protect user’s identity information from the data owner and cloud service provider, a new computation efficient privacy preserving algorithms proposed in this project work. (2017-2018)
Automatic transformation of the application code to improve performance (2016-2017)
Capture and efficiently store/process multiple incomeing BIG DATA streams. Combine and confront multiple heterogeneous sources in an analytical workflow scenarios. Incrementally maintain pre-calculated support data (making them dynamic). Improve quality of prediction and planning, e.g. complex scheduling (2016-2017)
The goal is to exploit tightly restricted access patterns (append only etc.) to outperform noSQL systems supporting more flexible access patterns (2016).
This inter-disciplinary series of projects is done in tight co-operation with researchers from other groups. (2014-2016).
The query processing techniques provide several advantages but sometimes are not suitable in modern distributed environments. We develop an algebraic framework for adaptive approximate query optimization and processing in presence of variety of data models and querying paradigms. (2013-2016).
A complex access pattern involves sevral data objects in several contiguous time slots. The knowledge of these patterns is helpful for prediction of workload peaks with fluctuating periodic activities which harldy can be discovered otherwise. (2014-2015).
Although the business processes are supposed to be known prior to the information system development, this might not be the case for large-scale systems developed by several teams, or in a cloud environment. The information on actual business processes might be helpful for analysis and plannign. Prediction of system workload peaks may be helpful for system performance tuning, etc. 10-07-00156 (2011-2013).
This umbrella project is supported by Russian Foundation for Basec Research under grant No. 10-07-00156 (2010-2012).
The project is undertaken in cooperation with The Information Retrieval Group at the Faculty of Informatics of the University of Lugano and supported by Scientific and Technological Cooperation Programme Switzerland-Russia for 2010
This project is supported by Google Research Awards program for 2010-2011.
the goal is to develop a framework and algorithms for complex query evaluation for open heterugeneous distributed environment.
Boilding a simulation model for different hardware and software architectures for performance analysis of analitical query processing.
The goal is to develop techniques for detection of long-term access patterns in order to optimize data placement in a distributed storage systems with heterogeneous storage.
Additional information can be found on the official pages of