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RESEARCH HIGHLIGHTS

Some of the project highlights of the Department are listed below:

Databases and Information Management

Adaptive Filtering for Efficient Subgraph Isomorphism in Graph Databases
Staff Dr. CHOI, Byron Koon Kau (Principal Investigator)
URL http://www.comp.hkbu.edu.hk/~bchoi/project/af.html
Abstract Graph/Network data model has been a powerful tool to model structures such as social networks, network traffic, biological databases and XML, among others. A typical task on graph data is to retrieve substructures embedded. The current state-of-the-art technique almost always comprise two phases -- the filtering and verification phases. We propose to adjust indexes adaptively, in response to query workloads.

Optimizations for the View Update Problem with Emerging Applications
Staff Dr. CHOI, Byron Koon Kau (Principal Investigator)
URL http://www.comp.hkbu.edu.hk/~bchoi/project/vu.html
Abstract Materialized views have been important in improving query evaluation performance in databases. Since materialized views are managed as real data, they are subjected to both queries and updates. While queries on materialized views are straightforward, updates on views are not. Materialized views play a crucial role in many emerging applications. These call for an investigation on the view update problem.

Updates of Bisimulation of Graphs
Staff Dr. CHOI, Byron Koon Kau (Principal Investigator)
URL http://www.comp.hkbu.edu.hk/~bchoi/project/ub.html
Abstract Updates have been an inseparable part of any bisimulation-based systems. However, updates of bisimulation receive less attention when compared to various applications of bisimulation. Previous theoretical studies on bisimulation report that updates on bisimulation are generally not localized. Hence, a simple update on a graph may result in a recomputation. This necessitates a detailed study on such updates.

Data-Centric Filter Management and Routing Optimization for Distributed Monitoring Systems
Staff Prof. XU, Jian Liang (Principal Investigator)
URL http://www.comp.hkbu.edu.hk/~xujl/research/defacto.html
Abstract This research project proposes to take data-centric designs to improve performance for distributed monitoring systems. Two issues namely filter management for approximate monitoring and routing optimization for in-network data aggregation are studied under this project.

Energy-Conserving Quality-Aware Data Collection in Wireless Sensor Networks
Staff Prof. XU, Jian Liang (Principal Investigator)
URL http://www.comp.hkbu.edu.hk/~xujl/research/ecoquad.html
Abstract Energy efficiency is a critical consideration in the design of a wireless sensor network. This project exploits the trade-off between data quality and communication cost to improve energy efficiency in sensor data collection.

iPDA: Privacy-Preserving Location-based Data Access in Mobile Environments
Staff Prof. XU, Jian Liang (Principal Investigator)
URL http://www.comp.hkbu.edu.hk/~xujl/research/ipda.html
Abstract With a location-aware wireless device, a mobile user can query his/her surroundings (e.g., finding the nearest gas station or all shopping centers within 5 miles) at any place, anytime. This project aims to support such location-based services while protecting users' location privacy.

Query Processing in Flash-Based Storage-Centric Sensor Networks
Staff Prof. XU, Jian Liang (Principal Investigator)
URL http://www.comp.hkbu.edu.hk/~xujl/research/qupos.html
Abstract In this project, we investigate innovative query processing algorithms for flash memory based storage-centric sensor networks. Of particular interest are distributed data management issues under sensor system workload given the unique read/write/erase characteristics of flash memories.

Transaction Management for Flash-based Database Systems
Staff Prof. XU, Jian Liang (Principal Investigator)
URL http://www.comp.hkbu.edu.hk/~xujl/research/flash.html
Abstract Owing to their superiority in access latency and energy consumption, flash memory drives have recently become a competitive alternative to magnetic hard disks as secondary storage. In this project, we plan to investigate a number of optimization techniques for transaction management in flash-based database systems by exploiting the characteristics of flash memory drives (e.g., out-of-place updating and partial page programming).


Project in Different Research Areas:

Computational Intelligence Databases and Information Management Networking and Systems Pattern Recognition and Machine Learning Others
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Department of Computer Science, Hong Kong Baptist University
Hong Kong Baptist University