Statistical Multiplexing

Chandra, Kavitha

doi:10.1002/0471219282.eot280

Cited by 8 publications

(4 citation statements)

References 84 publications

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“…Although work on reducing buffer sizes in the core network is necessary and important for the future, most current congestion is closer to the network edges, where there is not a high degree of statistical multiplexing. Chandra [160] divides congestion into packet-level and burst-level congestion. Packet-level congestion only requires small buffers, however congestion due to traffic burstiness and correlations requires much larger buffers.…”

Section: ) Smaller Network Buffersmentioning

confidence: 99%

Reducing Internet Latency: A Survey of Techniques and Their Merits

Briscoe

Brunström

Petlund

et al. 2016

IEEE Commun. Surv. Tutorials

148

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Latency is increasingly becoming a performance bottleneck for Internet Protocol (IP) networks, but historically networks have been designed with aims of maximizing throughput and utilization. This article offers a broad survey of techniques aimed at tackling latency in the literature up to August 2014, and their merits. A goal of this work is to be able to quantify and compare the merits of the different Internet latency reducing techniques, contrasting their gains in delay reduction versus the pain required to implement and deploy them. We found that classifying techniques according to the sources of delay they alleviate provided the best insight into the following issues: 1) the structural arrangement of a network, such as placement of servers and suboptimal routes, can contribute significantly to latency; 2) each interaction between communicating endpoints adds a Round Trip Time (RTT) to latency, especially significant for short flows; 3) in addition to base propagation delay, several sources of delay accumulate along transmission paths, today intermittently dominated by queuing delays; 4) it takes time to sense and use available capacity, with overuse inflicting latency on other flows sharing the capacity; and 5) within end systems delay sources include operating system buffering, head-of-line blocking, and hardware interaction. No single source of delay dominates in all cases, and many of these sources are spasmodic and highly variable. Solutions addressing these sources often both reduce the overall latency and make it more predictable.

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Section: ) Smaller Network Buffersmentioning

confidence: 99%

Reducing Internet Latency: A Survey of Techniques and Their Merits

Briscoe

Brunström

Petlund

et al. 2016

IEEE Commun. Surv. Tutorials

148

View full text Add to dashboard Cite

show abstract

“…One of the model features is that it is statistical multiplexer. Statistical multiplexing results in higher bandwidth utilization and minimum time complexity [20]. However, the major limitation here is that no minimum QoS requirements can be absolutely guaranteed.…”

Section: Model Analysismentioning

confidence: 99%

An adaptive multiplexer for multi-modal data communication

Eid

Cha

Saddik

2009

2009 IEEE International Workshop on Haptic Audio Visual Environments and Games

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Recent trends in multimedia applications strive to incorporate multi-modal media, such as audio, video, graphics, and particularly haptics to enhance the user's quality of experience. However each media type has a particular Quality of Service (QoS) requirement. The efficient use of network resources and the optimal distribution of these resources to all media streams remain an important challenge. This paper presents an adaptive and intelligent multiplexer for multiple input media streams based on the application requirements and the network conditions in a limited-resources network. The multiplexer adapts its multiplexing scheme and guarantees the allocation of minimum resources that are sufficient to make haptics interactions stable. The simulation results show that the proposed multiplexer provides the application immunity to dynamic changes in the network resources, and optimizes the communication of multimedia data based on their corresponding priorities.

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“…This is called statistical multiplexing. Statistical multiplexers are therefore modeled as queueing systems with finite buffer space for the incoming traffic, served (on a service discipline basis) by one or more transmission links of fixed or varying capacity [4].…”

Section: Introductionmentioning

confidence: 99%

Access Convergence for Heavy Load Markov Ethernet Bursty Traffic Using Two-level Statistical Multiplexing

2022

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A method for modeling aggregated heavy Markov bursty Ethernet traffic from different sources is proposed in this paper, particularly that prevailing between gateway services and internet routing devices, with the aim of achieving rate accommodation. In other words, to accommodate different rates while filtering out delays in the queue, to achieve access network convergence. Although gateway functions can be used to achieve this by adapting service rates, as many gateways as services are required. Instead of considering the distributed gateway services method, statistical multiplexing is chosen for this study for cost efficiency in network resources. Unfortunately, statistical multiplexing exhibits greater packet variation (jitter) and transfer delay. These delays, basically resulting from positive correlations or time dependency in the queue system, are addressed through infinitesimal queue modeling, based on the diffusion process approximated by Ornstein-Uhlenbeck, which deals with infinitesimal changes in the Markov queue. The related analysis has resulted in an exponential queueing model for univariate and/or multivariate servers obtained through Markov Gaussian approximation. An experiment based on two different voice algorithms shows rate accommodation, and a fluid solution, which is dynamically outputted according to the transmission link availability during each transition time, without any significant delay. Hence, better transfer delay and rate control is obtained through the proposed two multiplexing levels within an Ethernet LAN

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Statistical Multiplexing

Cited by 8 publications

References 84 publications

Reducing Internet Latency: A Survey of Techniques and Their Merits

Reducing Internet Latency: A Survey of Techniques and Their Merits

An adaptive multiplexer for multi-modal data communication

Access Convergence for Heavy Load Markov Ethernet Bursty Traffic Using Two-level Statistical Multiplexing

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