Projects
Completed projects
Hilda: A High-Level Language for Data-Driven Web Applications. An important class of applications is data-driven web applications, i.e., web applications that are run on top of a back-end database system. Examples of such applications include online shopping sites, online auctions, and business-to-business portals. While developing data-driven web applications is a complex and challenging task, the application development interface provided by existing platforms is often too low-level or does not provide a unified model for the whole application stack. Hilda addresses the above shortcomings by providing a high-level language for developing data-driven web applications. The primary benefits of Hilda over existing development platforms are: (a) it uses a unified data model for all layers of the application, (b) it is declarative, (c) it models both application queries and updates, (d) it supports structured programming for web sites, (e) it enables conflict detection due to concurrent updates, and (f) it separates application logic from presentation.
Quark: Unifying Database Systems and Information Retrieval Systems. The data stored in most enterprises is a mix of structured and unstructured data. Traditionally, structured data has been queried using (relational) database systems, while unstructured data has been queried using information retrieval systems. In the Quark project, we are exploring a much tighter integration (or unification) of database systems and information retrieval systems. Specifically, we are developing a novel system architecture that allows users to issue complex structured queries and ranked keyword search queries over any mix of structured, unstructured, and semi-structured data.
Cougar: The Network is the Database . The widespread distribution and availability of small-scale sensors, actuators, and embedded processors is transforming the physical world into a computing platform. Sensor networks that combine physical sensing capabilities such as temperature, light, or seismic sensors with networking and computation capabilities will soon become ubiquitous. Applications range from environmental control, warehouse inventory, and health care to scientific and military scenarios. Existing sensor networks assume that the sensors are preprogrammed and send data to a central frontend where the data is aggregated and stored for offline querying and analysis. This approach has two major drawbacks. First, the user cannot change the behavior of the system dynamically. Second, communication in today's networks is orders of magnitude more expensive than local computation; thus in-network storage and processing can vastly reduce resource usage and extend the lifetime of a sensor network. In the Cougar project, we are developing data management technology for wireless sensor networks.
The PEPPER Peer-to-Peer Database Project. Peer-to-peer systems, such as Napster and Gnutella, provide a new paradigm for structuring massively distributed and fault-tolerant computer systems. However, existing peer-to-peer systems are mostly file systems, with limited query capability. In the PEPPER project, we are building a system for evaluating complex queries over millions/billions of peers.
The HIMALAYA Data Mining Project. Innovative research techniques for analyzing large datasets.