This dissertation investigates novel middleware mechanisms for building streaming
applications. Developing streaming applications is a challenging task
because (i) they are continuous in nature; (ii) they require fusion of data coming from multiple sources to derive
higher level information; (iii) they require
efficient transport of data from/to distributed sources and sinks;
(iv) they need access to heterogeneous resources spanning sensor networks and high
performance computing; and (v) they are time critical in nature. My thesis is that an
intuitive programming abstraction will make it easier to build dynamic,
distributed, and ubiquitous data streaming applications. Moreover, such an abstraction will
enable an efficient allocation of shared and heterogeneous computational resources thereby making it easier for
domain experts to build these applications. In support of the thesis, I present a novel programming abstraction, called DFuse,
that makes it easier to develop these applications. A domain expert only needs to specify the input and output
connections to fusion channels, and the fusion functions. The subsystems developed in
this dissertation take care of instantiating the application,
allocating resources for the application (via the scheduling heuristic developed in this dissertation) and dynamically
managing the resources (via the dynamic scheduling algorithm presented in this dissertation). Through extensive
performance evaluation, I demonstrate that the resources are allocated efficiently to optimize the throughput and latency
constraints of an application.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/34836 |
| Date | 07 July 2010 |
| Creators | Agarwalla, Bikash Kumar |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Detected Language | English |
| Type | Dissertation |
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