Abstract
An adaptive decentralized strategy for active queue management of TCP flows over communication networks is presented. The proposed strategy solves locally, at each link, an optimal control problem, minimizing a cost composed of residual capacity and buffer queue size. The solution of the optimal control problem exploits an adaptive optimization algorithm aiming at adaptively minimizing a suitable approximation of the Hamilton-Jacobi-Bellman equation associated with the optimal control problem. Simulations results, obtained by using a fluid flow based model of the communication network and a common network topology, show improvement with respect to the Random Early Detection strategy. Besides, it is shown that the performance of the proposed decentralized solution is comparable with the performance obtained with a centralized strategy, which solves the optimal control problem via a central unit that maintains the flow states of the entire network.
Original language | English |
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Title of host publication | Proceedings of the 2016 American Control Conference (ACC2016) |
Editors | George Chiu, Katie Johnson, Danny Abramovitch |
Place of Publication | Piscataway, NJ, USA |
Publisher | IEEE |
Pages | 751-756 |
ISBN (Electronic) | 978-1-4673-8682-1 |
DOIs | |
Publication status | Published - 2016 |
Event | American Control Conference (ACC), 2016 - Boston, MA, United States Duration: 6 Jul 2016 → 8 Jul 2016 |
Conference
Conference | American Control Conference (ACC), 2016 |
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Abbreviated title | ACC 2016 |
Country/Territory | United States |
City | Boston, MA |
Period | 6/07/16 → 8/07/16 |
Bibliographical note
Accepted Author ManuscriptKeywords
- Protocols
- Communication networks
- Optimal control
- Mathematical model
- Delays
- Optimization