The analysis of real social, biological and
technological networks has attracted a lot of attention as technological advances
have given us a wealth of empirical data. For, analysis and investigation time
varying graphs are used to understand the relationship, contact duration,
repeated occurrence of contact. It is under exploring in intermittently connected
networks. Now, by extending the same concept in intermittent networks, the
efficiency of the routing protocol can be improved. This paper discusses about
the temporal characterizing algorithm. Such characterization can help in accurately
understanding dynamic behaviors and taking appropriate routing decisions.
Therefore, the present research provokes exploring different possibilities of
utilizing the same time varying network analyses and designing an Adaptive
Routing protocol using temporal distance metric. The adaptive routing protocol
is implemented using ONE simulator and is compared with the Epidemic and
PropHET for delivery ratio, overhead and the number of dropped messages. The
result reveals that Adaptive routing performs better than Epidemic and PropHET
for real and synthetic datasets.
Cite this paper
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