Estimation and prediction of VBR traffic in high-speed networks using LMS filters

Randhawa, T.S.; Hardy, R.H.S.

doi:10.1109/icc.1998.682678

Cited by 7 publications

(8 citation statements)

References 10 publications

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“…It is well known that VBR video and audio traffic show this property. The LMS predictor is a simple prediction mechanism and has been shown to predict VBR traffic reasonably well [4].…”

Section: B Predicting Vbr Traffic Intensitiesmentioning

confidence: 99%

HCCA Scheduler Design for Guaranteed QoS in IEEE 802.11e Based WLANs

Rashid

Hossain

Bhargava

2007

2007 IEEE Wireless Communications and Networking Conference

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The IEEE 802.11e standard developed by IEEE 802.11TGe intends to provide the Quality of Service (QoS) support for the popular 802.11 based wireless local area networks (WLAN) through the introduction of Hybrid Coordination Function (HCF). The HCF Controlled Channel Access (HCCA) designed as a part of HCF is the medium access mechanism for parameterized QoS and is suitable for multimedia applications requiring hard QoS guarantees. The standard also defines scheduling and admission control schemes to complement HCCA in meeting these guarantees. However, the Reference scheduler has several limitations which renders it incapable of providing QoS guarantees to many multimedia applications. In this paper, we propose a new scheduling scheme which overcomes these limitations to provide critical performance guarantees. Simulation experiments show that the proposed scheme successfully enables the HCCA to fulfill the QoS guarantees for wide variety of multimedia applications.

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“…It is well known that VBR video and audio traffic show this property. The LMS predictor is a simple prediction mechanism and has been shown to predict VBR traffic reasonably well [4].…”

Section: B Predicting Vbr Traffic Intensitiesmentioning

confidence: 99%

HCCA Scheduler Design for Guaranteed QoS in IEEE 802.11e Based WLANs

Rashid

Hossain

Bhargava

2007

2007 IEEE Wireless Communications and Networking Conference

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“…Such capability can significantly improve the effectiveness of tasks such as preventative congestion control. The scheme involves estimating the current traffic state over small observation intervals and predicting the future traffic (Randhawa and Hardy [37,38,39]). Using this capability, the onset of congestion could be forecasted and, subsequently, a preventative control action could be taken ahead of time.…”

Section: Packet Level Controlmentioning

confidence: 99%

“…These models include Markov Modulated Fluid Flow (MMFF) model [31], Markov Modulated Poisson Process (MMPP) model [45,47,48], Markov Modulated Deterministic Arrival model (MMDA) [45,47,48], and AutoRegressive model [31]. In the proposed approach (Randhawa and Hardy [37,38]) an AR modulated model, derived from the one proposed by Maglaris et al [31], is assumed. The first and second order statistics of the traffic at the multiplexer output are derived.…”

Section: Packet Level Controlmentioning

confidence: 99%

Network Management in Wired and Wireless Networks

Randhawa¹,

Hardy²

2002

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“…Short-term (e.g., sec-onds or minutes) forecasting of Internet traffic is addressed in (Basu, 1999); (Sang, 2000); (Papadopouli et al, 2006). The authors in (Randhawa & Hardy, 1998) model the VBR sources as AutoRegressive AR(1) Modulated Deterministic Arrival process which characterizes the inter-frame as well as the intra-frame bit rate variations, and they model the call arrival process as conventional birthdeath Markov Process. The future traffic is predicted using a combination of linear prediction and transient state analysis of birth-death Markov Process.…”

Section: Arima Based Traffic Forecastingmentioning

confidence: 99%