The Unidata Program Center is an organization working with the University
Center for Atmospheric Research (UCAR), in Colorado. It provides a broad variety
of meteorological data, which is used by researchers in many real-world applications.
This data is obtained from observation stations and distributed to various universities
worldwide, using UnidataâÂÂs own Internet Data Distribution (IDD) system, and
software called the Local Data Manager (LDM).
The existing solution for data distribution has many limitations, like high end-toend
latency of data delivery, increased bandwidth usage at some nodes, poor scalability
for future needs and manual intervention for adjusting to changes or faults in the
network topology. Since the data is used in so many applications, the impact of these
limitations is often substantial. This thesis removes these limitations by suggesting
improvements in the IDD system and the LDM. We present new algorithms for constructing
an application-layer data distribution network. This distribution network
will form the basis of the improved LDM and the IDD system, and will remove most
of the limitations given above.
Finally, we perform simulations and show that our algorithms achieve better
average end-to-end latency as compared to that of the existing solution. We also
compare the performance of our algorithms with a randomized solution. We find
that for smaller topologies (where the number of nodes in the system are less than
38) the randomized solution constructs efficient distribution networks. However, if the number of nodes in the system increases (more than 38), our solution constructs
efficient distribution networks than the randomized solution. We also evaluate the
performance of our algorithms as the number of nodes in the system increases and
as the number of faults in the system increases. We find that even if the number of
faults in the system increases, the average end-to-end latency decreases, thus showing
that the distribution topology does not become inefficient.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/4798 |
| Date | 25 April 2007 |
| Creators | Shah, Saurin Bipin |
| Contributors | Pike, Scott M. |
| Publisher | Texas A&M University |
| Source Sets | Texas A and M University |
| Language | en_US |
| Detected Language | English |
| Type | Book, Thesis, Electronic Thesis, text |
| Format | 1250041 bytes, electronic, application/pdf, born digital |
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