Techniques and Applications of Overlay Networks
In this sub-project, we address the
research issues in the scalable overlay network infrastructure and its
application to continuous data stream processing.
Scalable
overlay network infrastructure
In
this part of the research, we will focus on the design and development of
scalable overlay networks for supporting data streaming applications. We will
research into related theories and algorithms, and build the infrastructure. It
will contain the following major components: a middleware or run-time
environment for creating and executing overlays, a development framework for
developing application-specific overlays, and a monitoring and management system
for the overlays.
Continuous
data stream management
Based on the scalable overlay network
infrastructure, we will continue to build up the basic components and for
managing continuous data streams on the overlay networks. With our research
experience in the fields of data broadcasting, distributed query processing and
optimization, web mining, content-based multimedia retrieval, multimedia
networking, parallel processing, and algorithm design, we will research into the
issues on querying, mining, and delivering continuous data streams and develop
efficient methods for the variety of streaming applications. Our works toward
this goal are divided into two parts. In the 1st and 2nd years, we will consider
the issues of continuous query indexing, time-varying summary maintenance, trend
analysis, and video stream delivery. We will design the mechanisms for
processing continuous/streaming queries, the one-pass mining algorithms for
finding frequent patterns and data/query clusters, and the scheme for delivering
video streams. In the 3rd and 4th years, we will further address the issues of
the blocking operators in continuous queries, data heterogeneity, approximate
matching and summarization for multimedia streams. We will construct the
mechanisms for processing complex queries with data heterogeneity and the
real-time algorithms for semantic object identification, high-level concept
derivation and maintenance for multimedia streams.
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