- Tytuł:
-
Wykorzystanie logiki rozmytej w algorytmach AQM
On a proposal of using fuzzy logic in AQM mechanism - Autorzy:
- Płachecki, K.
- Powiązania:
- https://bibliotekanauki.pl/articles/152196.pdf
- Data publikacji:
- 2009
- Wydawca:
- Stowarzyszenie Inżynierów i Techników Mechaników Polskich
- Tematy:
-
logika rozmyta
aktywne zarządzanie kolejkami
fuzzy logic
active queue management - Opis:
-
W obecnych czasach wymagania stawiane sieciom TCP/IP zostały znacznie zróżnicowane poprzez aplikacje wymagające odmiennych poziomów usług sieciowych QoS (ang. Quality of Service). Dodatkowo, wzrastający udział transmisji czasu rzeczywistego RTP wymusza poszukiwanie nowych metod aktywnego zarządzania obsługą pakietów w węzłach sieci. Autor wskazuje możliwość wykorzystania logiki rozmytej w mechanizmach adaptacyjnych AQM (ang. Active Queueing Management), w celu poprawy wydajności układów zarządzania przepływem pakietów.
Active Queue Management (AQM) is the name given to router mechanisms used in congestion control. AQM mechanisms manage queue lengths by dropping (or marking) packets during building up congestion, that is, before the queue is full. End-systems can then react to such losses by reducing their packet rate, hence avoiding severe congestion. AQM mechanisms are also relevant in the context of DiffServ. The DiffServ architecture has been defined to provide IP networks with scalable quality of service (QoS) processing of traffic aggregates, based on a special field in the IP header. This paper presents new active queue management mechanisms to provide congestion control in TCP/IP best-effort networks. The author propose how to use fuzzy logic to better solve the drop tail problem in the basic AQM mechanism (REM) with one buffer and a server. The objective of the fuzzy controller is to determine the optimal admission policies so as to maximise the average profit (reward minus cost). The proposed fuzzy logic approach for congestion control allows using linguistic knowledge to capture the dynamics of nonlinear probability marking functions. In the introduction the author defines a structure of Supervisory Expert Control System [10, 12, 14] and the project aims illustrated in Figs. 2 and 3 [15]. In Section 3 the author presents implementation of a new algorithm FREM that uses a Fuzzy Logic Controller. The model of FREM algorithm [8] is shown in Fig. 5. In Section 5 the author shows the plan on future works: a project of the FLC controller and verification of the FREM algorithm performance. The paper presents the FREM algorithm with nonlinear probability marking functions. There is shown a conception of applying Supervisory Expert Control System to congestion control in TCP/IP networks. The author proposes how to ensure the adaptation ability of the REM algorithm. The presented solution requires an additional FLC supervisory module. The objective of fuzzy controller is to determine the optimal admission policies so as to maximise the average profit (reward minus cost). The proposed fuzzy logic approach to congestion control allows using linguistic knowledge to capture the dynamics of nonlinear probability marking functions. - Źródło:
-
Pomiary Automatyka Kontrola; 2009, R. 55, nr 2, 2; 98-100
0032-4140 - Pojawia się w:
- Pomiary Automatyka Kontrola
- Dostawca treści:
- Biblioteka Nauki
Artykuł