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Modeling and Routing for Predictable Dynamic Networks: This paper is only for copyright protection, and unpublished to the top-level version
The topologies of predictable dynamic networks are continuously dynamic in
terms of node position, network connectivity and link metric. However, their
dynamics are almost predictable compared with the ad-hoc network. The existing
routing protocols specific to static or ad-hoc network do not consider this
predictability and thus are not very efficient for some cases.
We present a topology model based on Divide-and-Merge methodology to
formulate the dynamic topology into the series of static topologies, which can
reflect the topology dynamics correctly with the least number of static
topologies. Then we design a dynamic programing algorithm to solve that model
and determine the timing of routing update and the topology to be used.
Besides, for the classic predictable dynamic network---space Internet, the
links at some region have shorter delay, which leads to most traffic converge
at these links. Meanwhile, the connectivity and metric of these links
continuously vary, which results in a great end-to-end path variations and
routing updates. In this paper, we propose a stable routing scheme which adds
link life-time into its metric to eliminate these dynamics. And then we take
use of the Dijkstra's greedy feature to release some paths from the dynamic
link, achieving the goal of routing stability. Experimental results show that
our method can significantly decrease the number of changed paths and affected
network nodes, and then greatly improve the network stability. Interestingly,
our method can also achieve better network performance, including the less
number of loss packets, smoother variation of end-to-end delay and higher
throughput