✦ LIBER ✦

Load Estimation and Control in Best-Effort Network Domains

✍ Scribed by Piergiulio Maryni; Franco Davoli

Book ID: 111561986
Publisher: Springer US
Year: 2000
Tongue: English
Weight: 124 KB
Volume: 8
Category: Article
ISSN: 1064-7570
DOI: 10.1023/a:1026434517164

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

HMM based estimation of NCS network load

HMM based estimation of NCS network load and its application in switching control

✍ Yan Wang, Longfei Tian 📂 Article 📅 2013 🏛 Springer US 🌐 English ⚖ 548 KB

Fair bandwidth sharing between unicast a

Fair bandwidth sharing between unicast and multicast flows in best-effort networks

✍ Fethi Filali; Walid Dabbous 📂 Article 📅 2004 🏛 Elsevier Science 🌐 English ⚖ 388 KB

Stochastic observability in network stat

Stochastic observability in network state estimation and control

✍ Andrew R. Liu; Robert R. Bitmead 📂 Article 📅 2011 🏛 Elsevier Science 🌐 English ⚖ 561 KB

A hidden Markov model for the traffic congestion control problem in transmission control protocol (TCP) networks is developed, and the question of observability of this system is posed. Of specific interest are the dependence of observability on the congestion control law and the interaction between

[Communications in Computer and Informat

[Communications in Computer and Information Science] Advances in Computer Science and Engineering Volume 6 || Best Effort Flow Control in Network-on-Chip

✍ Sarbazi-Azad, Hamid; Parhami, Behrooz; Miremadi, Seyed-Ghassem; Hessabi, Shaahin 📂 Article 📅 2008 🏛 Springer Berlin Heidelberg ⚖ 160 KB

Robust control of induction motor with a

Robust control of induction motor with a neural-network load torque estimator and a neural-network identification

✍ Chich-Yi Huang; Tien-Chi Chen; Ching-Lien Huang 📂 Article 📅 1999 🏛 IEEE 🌐 English ⚖ 216 KB

Artificial neural networks in process es

Artificial neural networks in process estimation and control

✍ M.J. Willis; G.A. Montague; C. Di Massimo; M.T. Tham; A.J. Morris 📂 Article 📅 1992 🏛 Elsevier Science 🌐 English ⚖ 692 KB

In this contribution, the suitability of the artificial neural network methodology for solving some process engineering problems is discussed. First the concepts involved in the formulation of artificial neural networks are presented. Next the suitability of the technique to provide estimates of dif