Matching Data Dissemination Algorithms to Application Requirements

 

Authors:

John Heidermann, Fabio Silva, Deborah Estrin

 

Presented by:

Bryan Wong

 

Summary of Paper:

The main goal of this paper is to demonstrate that it is very important to select a data dissemination algorithm that suits the application's requirements.  Also, the paper introduces One Phase Pull diffusion and Push diffusion that are suitable for complementary applications.

 

Through systematic testing, the authors show that one phase pull is best for applications with many sources and a few sinks and push is best for applications with many sinks and few sources.  The break even point between the two algorithms depends upon specific control message frequency as well as application data rates.  For networks with more than a few dozen nodes, the benefits of geographically-scoped queries can outweigh other algorithmic choices.

 

Discussion:

-Possibility of detecting the number of sources and sinks and then using the appropriate dissemination algorithm

  It seems possible, however the attempts the authors made did not work

 

-Systematic Evaluation of the algorithms

  How valid are the evaluations, taking sample size and sample environment into consideration

 

-One of the key contributions of the paper was to "demonstrate the importance of matching data dissemination algorithm to application"

  We already know that data dissemination algorithms are application specific; is it really necessary to perform experiments to prove this point?

 

Additional References:

lhttp://www.cens.ucla.edu/Education/RR_Posters/Research%20Review/015_Silva.pdf
 

 

 

Slides