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During the recent 30 years of Internet evolution, traditional TCP congestion control architecture, though having a army of specially-engineered implementations and improvements over the original software, suffers increasingly more from surprisingly poor performance in today's complicated network conditions.

We argue the traditional TCP congestion control family has little hope of achieving consistent high performance due to a fundamental architectural deficiency: hardwiring packet-level events to control responses. In this thesis, we propose Performance-oriented Congestion Control PCC , a new congestion control architecture in which each sender continuously observes the connection between its rate control actions and empirically experienced performance, enabling it to use intelligent control algorithms to consistently adopt actions that result in high performance.

We first build the above foundation of PCC architecture analytically prove the viability of this new congestion control architecture. Specifically, we show that, controversial to intuition, with certain form of utility function and a theoretically simplified rate control algorithm, selfishly competing senders converge to a fair and stable Nash Equilibrium. With this architectural and theoretical guideline, we then design and implement the first congestion control protocol in PCC family: PCC Allegro.

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PCC Allegro immediate demonstrates its architectural benefits with significant, often more than 10X, performance gain on a wide spectrum of challenging network conditions. ECN testing of webservers with globally routable IPv6 adderesses showed a higher success rate SACK receiving analysis showed higher results to the earlier studies, with success increasing from For both of these SACK studies results for webservers with globally routable IPv6 addresses showed a higher success rate when errors remained low.

However we see that implementation and support for modern TCP features is increasing.

  1. Controlling congestion on complex networks: fairness, efficiency and network structure.
  2. Congestion control for the Internet: Modeling and Analysis?
  3. write good conclusion tok essay.

Type Thesis. Supervisors Luckie, Matthew John.


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Forecasting full-path network congestion using one bit signalling

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