Can I add a VoIP call?

Garg, Sachin; Kappes, Martin

doi:10.1109/icc.2003.1204432

Cited by 182 publications

(133 citation statements)

References 6 publications

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“…Cali et al, in [5], provide a theoretical throughput analysis based on a p-persistent model of the MAC. In [2] [9], Hwang and Cho [13] and Medapalli et al [17]. These authors do not model the evolution of the back-off process of the 802.11 MAC layer, but consider approximate constant values for back-off parameters like average back-off time ( [9] and [13]) and collision probability ( [17]).…”

Section: Introductionmentioning

confidence: 99%

Analytical models for capacity estimation of IEEE 802.11 WLANs using DCF for internet applications

et al. 2007

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Abstract-We provide analytical models for capacity evaluation of an infrastructure IEEE 802.11 based network carrying TCP controlled file downloads or full-duplex packet telephone calls. In each case the analytical models utilize the attempt probabilities from a well known fixed-point based saturation analysis. For TCP controlled file downloads, following [3], we model the number of wireless stations (STAs) with ACKs as a Markov renewal process embedded at packet success instants. In our work, analysis of the evolution between the embedded instants is done by using saturation analysis to provide state dependent attempt probabilities. We show that in spite of its simplicity, our model works well, by comparing various simulated quantities, such as collision probability, with values predicted from our model. Next we consider N constant bit rate VoIP calls terminating at N STAs. We model the number of STAs that have an uplink voice packet as a Markov renewal process embedded at so called channel slot boundaries. Analysis of the evolution over a channel slot is done using saturation analysis as before. We find that again the AP is the bottleneck, and the system can support (in the sense of a bound on the probability of delay exceeding a given value) a number of calls less than that at which the arrival rate into the AP exceeds the average service rate applied to the AP. Finally, we extend the analytical model for VoIP calls to determine the call capacity of an 802.11b WLAN in a situation where VoIP calls originate from two different types of coders. We consider N1 calls originating from Type 1 codecs and N2 calls originating from Type 2 codecs. For G711 and G729 voice coders, we show that the analytical model again provides accurate results in comparison with simulations.Index Terms-TCP throughput on WLAN, VoIP on WLAN, capacity of WLAN, performance modeling of DCF.

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Section: Introductionmentioning

confidence: 99%

Analytical models for capacity estimation of IEEE 802.11 WLANs using DCF for internet applications

et al. 2007

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“…We remark here that the chosen values of N max v always exceed the VoIP capacity as defined in [1], hence for each value of M and C we simulate both congested and non congested scenarios.…”

Section: A Simulation Setupmentioning

confidence: 99%

“…In our scenario, for every VoIP session, we measure the quality of the downlink flow only, since the downlink is known to be the bottleneck for VoIP over WLAN [1].…”

Section: B Measurements Gathered By the Mobile Terminalmentioning

confidence: 99%

“…In fact, even though the 802.11 standard provides the necessary protocol support to perform admission control, these algorithms are in practice not implemented in most deployments, in particular hotspots and domestic environments, due to the heterogeneity of users and applications. Hence, performing VoIP communications in these scenarios might result in poor VoIP quality due to the wireless channel being congested by other VoIP users [1] and/or other types of traffic such as web browsing, video streaming and peer-to-peer file sharing.…”

Section: Introduction and Related Workmentioning

confidence: 99%

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Cognitive Call Admission Control for VoIP over IEEE 802.11 Using Bayesian Networks

Quer

Baldo

Zorzi

2011

2011 IEEE Global Telecommunications Conference - GLOBECOM 2011

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Abstract-In this paper we address the problem of provisioning Quality of Service (QoS) to Voice over IP applications in a Wireless LAN scenario based on the IEEE 802.11 standard. We propose the use of a Cognitive Network approach to design a Call Admission Control (CAC) scheme, according to which each user stores relevant information on its past network experience and then uses such information to build a Bayesian Network (BN), a probabilistic graphical model to describe the statistical relationships among network parameters. The BN is exploited to predict the voice call quality, as a function of the Link Layer conditions in the particular scenario considered. Such prediction on the present and future values of the QoS provided is directly exploited to design the cognitive CAC scheme, which is shown to significantly outperform state of the art CAC techniques in a realistic scenario.

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“…Capacity models [3], [5]- [7] and measurement based works [4], [8], [9] show that 802.11b/g APs can carry a very small number of VoIP calls due to the overhead incurred by the 802.11 protocol when carrying small packets. This overhead causes VoIP calls to take up much more bandwidth at the physical layer than required by VoIP applications.…”

Section: A Motivation -Voip Over Wifimentioning

confidence: 99%

Packet aggregation in multi-rate wireless LANs

Majeed

Abu-Ghazaleh

2012

2012 9th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON)

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Abstract-In CSMA networks, there is a significant overhead associated with each packet including header overhead and contention overhead. The high overhead problem is exacerbated because some of these overheads are required to be at the lowest data rate to ensure that all contending nodes can compete fairly. For applications where packets are small, such as Voice over IP (VOIP), this means that a majority of the available transmission time is wasted on overhead. Packet aggregation is one of the techniques that has been proposed to amortize the per-transmission overhead over multiple aggregated packets. However, existing heuristics are limited, often not considering multi-rate wireless MAC, or operation in a WLAN environment. In this paper, we first formulate the problem of optimal aggregation for a multi-rate CSMA MAC protocol and show that it is NP-Hard. We then propose two heuristics that solve the aggregation problem for multi-rate WLANs. The first, which we call Data Rate based Aggregation protocol (DRA), divides packets in the MAC queue into groups based on the data rate they are to be transmitted at. The algorithm aggregates packets in the same group and broadcasts the aggregated frame at the data rate of that group. Empirically, DRA achieves several fold increase in throughput compared to basic aggregation. DRA also achieves up to a 200% increase in the number of VoIP calls supported by a single 802.11g AP compared to using state of the art aggregation protocols. The second heuristic, which we call Data Rate based Aggregation with Selective Demotion (DRA-SD), enables cross data rate aggregation. Through preliminary evaluation, we show that selectively demoting packets can further improve performance.

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Can I add a VoIP call?

Cited by 182 publications

References 6 publications

Analytical models for capacity estimation of IEEE 802.11 WLANs using DCF for internet applications

Analytical models for capacity estimation of IEEE 802.11 WLANs using DCF for internet applications

Cognitive Call Admission Control for VoIP over IEEE 802.11 Using Bayesian Networks

Packet aggregation in multi-rate wireless LANs

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