SCHEDULE: NOV 16-22, 2013
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Evaluating Named Data Networking For Large Scientific Data
SESSION: ACM Student Research Competition Poster Reception
EVENT TYPE: ACM Student Research Competition Posters, ACM Student Research Competition
TIME: 5:15PM - 7:00PM
AUTHOR(S):Susmit Shannigrahi
ROOM:Mile High Pre-Function
ABSTRACT:
With growing volume of scientific data, data management and retrieval are becoming increasingly complicated. Named Data Networking (NDN) is a potential next generation Internet architecture. In this preliminary work, we show that Named Data Networking (NDN) offers unique properties that can reduce complexities involving large scientific data. We discuss these built in properties of NDN for reducing the need for catalogs, complex middleware or applications. We then support these observations with results from experiments done using the ESNet testbed and real scientific data.
We have used a comparatively small dataset and simple testbed topology to demonstrate NDN's capabilities. We plan to extend this work for real scientific analysis involving larger datasets and different network topologies.
This poster focuses on demonstrating how NDN is useful for large scientific data. It also shows NDN's ability to reduce middleware and complex applications and at the same time, offer improved performance.
Chair/Author Details:
Susmit Shannigrahi - Colorado State University and Lawrence Berkeley National Laboratory
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