dc.contributor.author | Baldi, S. | en |
dc.contributor.author | Kosmatopoulos, E. B. | en |
dc.contributor.author | Pitsillides, Andreas | en |
dc.contributor.author | Lestas, Marios | en |
dc.contributor.author | Ioannou, Petros A. | en |
dc.contributor.author | Wan, Y. | en |
dc.creator | Baldi, S. | en |
dc.creator | Kosmatopoulos, E. B. | en |
dc.creator | Pitsillides, Andreas | en |
dc.creator | Lestas, Marios | en |
dc.creator | Ioannou, Petros A. | en |
dc.creator | Wan, Y. | en |
dc.date.accessioned | 2019-11-13T10:38:22Z | |
dc.date.available | 2019-11-13T10:38:22Z | |
dc.date.issued | 2016 | |
dc.identifier.isbn | 978-1-4673-8682-1 | |
dc.identifier.uri | http://gnosis.library.ucy.ac.cy/handle/7/53594 | |
dc.description.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. © 2016 American Automatic Control Council (AACC). | en |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | en |
dc.source | Proceedings of the American Control Conference | en |
dc.source | 2016 American Control Conference, ACC 2016 | en |
dc.source.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84992110482&doi=10.1109%2fACC.2016.7525004&partnerID=40&md5=35d241d98f03fc1d60f50e129f7166f0 | |
dc.title | Adaptive optimization for active queue management supporting TCP flows | en |
dc.type | info:eu-repo/semantics/conferenceObject | |
dc.identifier.doi | 10.1109/ACC.2016.7525004 | |
dc.description.volume | 2016-July | en |
dc.description.startingpage | 751 | |
dc.description.endingpage | 756 | |
dc.author.faculty | 002 Σχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied Sciences | |
dc.author.department | Τμήμα Πληροφορικής / Department of Computer Science | |
dc.type.uhtype | Conference Object | en |
dc.description.notes | <p>Sponsors: Adaptics | en |
dc.description.notes | et al. | en |
dc.description.notes | GE Global Research | en |
dc.description.notes | MathWorks | en |
dc.description.notes | Mitsubishi Electric Research Laboratory (MERL) | en |
dc.description.notes | Quanser | en |
dc.description.notes | Conference code: 123142 | en |
dc.description.notes | Cited By :1</p> | en |
dc.contributor.orcid | Pitsillides, Andreas [0000-0001-5072-2851] | |
dc.gnosis.orcid | 0000-0001-5072-2851 | |