Adaptive reliable multicast in 802.11 networks

Geithner, Thomas; Sivrikaya, Fikret

doi:10.1109/wcnc.2018.8377288

Cited by 4 publications

(6 citation statements)

References 28 publications

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“…In our previous work, we presented an experimental multicast rate control approach [25] that used sampling in conjunction with aggregated receiver feedback but did not provide full reliability at the link layer. Instead, a controlled level of packet losses was delegated to the transport layer, where the NORM protocol [26] was used to ensure reliable multicast.…”

Section: Multicast Transmission Rate Selection In 80211mentioning

confidence: 99%

“…Our multicast rate control approach combines the concept of data rate sam-pling (which is the common approach for unicast rate controls like minstrel [24]) with an aggregated receiver feedback mechanism as we introduced in our previous work [25]. In contrast to our previous approach, the receiver feedback information is polled individually in a round robin manner for all members in the multicast group to avoid collisions of response frames.…”

Section: Transmission Rate Sampling and Selectionmentioning

confidence: 99%

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Transmission Rate Sampling and Selection for Reliable Wireless Multicast

Geithner

Sivrikaya

2020

Wireless Communications and Mobile Computing

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The multicast communication concept offers a scalable and efficient method for many classes of applications; however, its potential remains largely unexploited when it comes to link-layer multicasting in wireless local area networks. The fundamental lacking feature for this is a transmission rate control mechanism that offers higher transmission performance and lower channel utilization, while ensuring the reliability of wireless multicast transmissions. This is much harder to achieve in a scalable manner for multicast when compared with unicast transmissions, which employs explicit acknowledgment mechanisms for rate control. This article introduces EWRiM, a reliable multicast transmission rate control protocol for IEEE 802.11 networks. It adapts the transmission rate sampling concept to multicast through an aggregated receiver feedback scheme and combines it with a sliding window forward error correction (FEC) mechanism for ensuring reliability at the link layer. An inherent novelty of EWRiM is the close interaction of its FEC and transmission rate selection components to address the performance-reliability tradeoff in multicast communications. The performance of EWRiM was tested in three scenarios with intrinsically different traffic patterns; namely, music streaming scenario, large data frame delivery scenario, and an IoT scenario with frequent distribution of small data packets. Evaluation results demonstrate that the proposed approach adapts well to all of these realistic multicast traffic scenarios and provides significant improvements over the legacy multicast- and unicast-based transmissions.

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Section: Multicast Transmission Rate Selection In 80211mentioning

confidence: 99%

Section: Transmission Rate Sampling and Selectionmentioning

confidence: 99%

Transmission Rate Sampling and Selection for Reliable Wireless Multicast

Geithner

Sivrikaya

2020

Wireless Communications and Mobile Computing

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“…In one scenario, we are using the NORM protocol for reliable multicast content transmissions. Since no NORM implementations were available for the Network Simulator 3 (ns3) environment, we used the Naval Research Laboratory (NRL) NORM [32] implementation in the Direct Code Execution (DCE) framework [33] (similarly to one of our previous publications [34]). The current DCE implementation relies on outdated versions of the glibc library.…”

Section: Evaluation and Resultsmentioning

confidence: 99%

Joint Link Rate Selection and Adaptive Forward Error Correction for High-Rate Wireless Multicast

Geithner

Sivrikaya²,

Albayrak

2022

IEEE Open J. Commun. Soc.

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Multicast communication over wireless networks has many potential applications, such as real-time audiovisual content distribution or digital signage systems with multiple remote terminals. However, today's common 802.11 networks cannot fully support such applications at the link layer due to the technical challenges in achieving both high transmission rate and high reliability for multicast data transfers. Those challenges primarily emerge from the inapplicability of immediate acknowledgment mechanisms of unicast transmissions to the multicast case and the need for finding a common transmission rate for all receivers with diverse channel conditions. The research literature in this domain mainly addresses the problem at the higher layers of the protocol stack. In this article, we present a novel approach that combines wireless link rate selection with an adaptive packet-level Forward Error Correction (FEC) mechanism in order to achieve high-rate and highly reliable multicast in 802.11 wireless networks. The integration of FEC into the 802.11 MAC layer allows direct interaction between the transmission rate and the coding scheme. As a result, potential packet losses caused by higher link rates can be compensated by the adjustable redundancy provided by FEC. In combination with an aggregated receiver feedback mechanism, this yields improved transmission efficiency and reliability for wireless multicast. We investigate this approach in a simulation environment under a realistic wireless channel model in various application scenarios with up to 50 receivers. The results represent significant performance improvements, in terms of throughput, channel utilization, and packet loss, over the state-of-the-art methods for reliable wireless multicast.

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“…Further, the authors of [20] proposed ATRaCt, a cross-layer rate control for wireless multicast that takes information from the transport layer to modify the data rate of the link layer. The transport layer information is taken using the NORM protocol [3].…”

Section: Related Workmentioning

confidence: 99%

“…Ultimately, it is up to the network administrator and the specific media content to set the %n range N ACK . In the experiments section and for performance testing purposes, we used a %n range N ACK = [10,20] MCS ← MCS(i) 8: end if…”

Section: Adaptive Modulation Algorithmmentioning

confidence: 99%

PROFEE: A Probabilistic-Feedback Based Speed Rate Adaption for IEEE 802.11bc

Gomez,

Camacho-Escoto,

Orozco-Barbosa

et al. 2023

Future Internet

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WiFi is a widely used wireless technology for data transmission. WiFi can also play a crucial role in simultaneously broadcasting content to multiple devices in multimedia transmission for venues such as classrooms, theaters, and stadiums, etc. Broadcasting allows for the efficient dissemination of information to all devices connected to the network, and it becomes crucial to ensure that the WiFi network has sufficient capacity to transmit broadcast multimedia content without interruptions or delays. However, using WiFi for broadcasting presents challenges that can impact user experience, specifically the difficulty of obtaining real-time feedback from potentially hundreds or thousands of users due to potential collisions of feedback messages. This work focuses on providing accurate feedback to the Access Point about the percentage of users not receiving broadcast traffic correctly so it can adjust its Modulation and Coding Scheme (MCS) while transmitting broadcast multimedia content to many users. The proposed method is comprised of two sequential algorithms. In order to reduce the probability of a collision after transmitting each message, an algorithm searches for the best probability value for users to transmit ACK/NACK messages, depending on whether messages are received correctly or not. This feedback allows the Access Point to estimate the number of STAs correctly/incorrectly receiving the messages being transmitted. A second algorithm uses this estimation so the Access Point can select the best MCS while maintaining the percentage of users not receiving broadcast content correctly within acceptable margins, thus providing users with the best possible content quality. We implemented the proposed method in the ns-3 simulator, and the results show it yields quick, reliable feedback to the Access Point that was then able to adjust to the best possible MCS in only a few seconds, regardless of the user density and dimensions of the scenario.

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Adaptive reliable multicast in 802.11 networks

Cited by 4 publications

References 28 publications

Transmission Rate Sampling and Selection for Reliable Wireless Multicast

Transmission Rate Sampling and Selection for Reliable Wireless Multicast

Joint Link Rate Selection and Adaptive Forward Error Correction for High-Rate Wireless Multicast

PROFEE: A Probabilistic-Feedback Based Speed Rate Adaption for IEEE 802.11bc

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