THESIS
2016
xiii, 117 pages : illustrations ; 30 cm
Abstract
Today’s Internet is no longer fit for the user traffic patterns that it is serving. To remedy this
cognitive mismatch between the service platform and the traffic it serves, several future Internet
architectures such as Content-Centric Networking (CCN) have been proposed recently with the
aim of re-engineering the Internet towards supporting content-oriented communication. With the
mechanisms to transform the Internet from being host-centric to becoming content-centric well
spelt-out in the CCN standard, the problem of how to manage congestion and control traffic flows
in CCN is still left open. Existing congestion control mechanisms for the current Internet have been
shown to be ill-suited for CCN making the case for a clean-slate design of congestion control and
traffic manage...[
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Today’s Internet is no longer fit for the user traffic patterns that it is serving. To remedy this
cognitive mismatch between the service platform and the traffic it serves, several future Internet
architectures such as Content-Centric Networking (CCN) have been proposed recently with the
aim of re-engineering the Internet towards supporting content-oriented communication. With the
mechanisms to transform the Internet from being host-centric to becoming content-centric well
spelt-out in the CCN standard, the problem of how to manage congestion and control traffic flows
in CCN is still left open. Existing congestion control mechanisms for the current Internet have been
shown to be ill-suited for CCN making the case for a clean-slate design of congestion control and
traffic management mechanisms for CCN.
In this thesis, we identify the fact that congestion in CCN can take place not only in the transmission
buffer but also in the pending interest table (PIT), a data structure that keeps track of all
requests received from downstream nodes and forwarded to upstream nodes. Keeping this in mind,
we make three contributions in this thesis: First, we characterize the PIT occupancy distribution
using a 2-dimensional continuous-time Markov chain model to study the impact of PIT entry timeout
and interest retransmission on the interest blocking probability. Second, given the dependence
of the PIT occupancy on the PIT entry timeout and interest retransmission, we investigate the performance of two types of routers in lossy networks: no-rtx routers that do not retransmit pending
interests upon timeout, and rtx routers that do retransmit pending interests periodically. Based on
this, we further introduce a novel adaptive method to estimate the PIT entry timer that relies on the
data chunk response delays to replace the currently used fixed-value method introduced in CCN. Finally,
identifying that content requesters should be responsible for retransmitting timeout requests
and that estimates of the retransmission timeout should reflect the network load conditions, we propose
a novel congestion control mechanism for CCN that takes into account both the PIT and the
transmit buffer. Using the PIT occupancy as a good estimator for the data flight size to arrive to the
node in the near future, we design a congestion avoidance mechanism that adjusts the request rate
based on anticipated congestion.
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