Parallel downloads for streaming applications—a resequencing analysis

Nebat, Y.; Sidi, M.

doi:10.1016/j.peva.2004.11.006

Cited by 9 publications

(10 citation statements)

References 17 publications

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“…This is different from the previous works [15]- [17] which only focus on mean value of the random delay. The rest of this paper is organized as follows.…”

Section: Introductioncontrasting

confidence: 70%

Section: Introductionmentioning

confidence: 99%

“…In [15], authors analyze the resequencing buffer occupancy distribution based on discrete Markov-chain and propose a new packets assignment method to reduce buffer occupancy. Based on [15], [11] provides a simulation framework about the re-sequencing buffer occupancy and performs an analysis on the fundamental factors for packet re-ordering in CMT. In [16], a mathematical model is proposed to find transmission rate over each path, and a packet scheduling scheme is designed to effectively minimize the impact of packet re-ordering at the receiver.…”

Section: Introductionmentioning

confidence: 99%

“…Furthermore, paper [11] shows by simulation that in case of a transmission over two paths with equal distribution the buffer occupancy depends mainly on the standard deviation. However, the analysis in [15][16] [17] is based on discrete event and only considers the mean value of the random transmission delay.…”

Section: Introductionmentioning

confidence: 99%

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Analysis of re-sequencing buffer overflow probability based on stochastic delay characteristics

Zhou

2013

2013 IEEE 24th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC)

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With the development of multi-interface terminals, a host can connect to the Internet simultaneously by multiple access technologies. Under multi-access technology, a multi-path transmission can obtain high throughput, increased available bandwidth and enhanced reliability. However, the multi-path transmission with multi-access technology also has the problems that the packet re-ordering is unavoidable, and the fast retransmission is unnecessarily requested. Considering the stochastically varying transmission delay, the problems above may eventually result in a degradation of throughput. As a result, in this paper, we focus on the analysis of buffer overflow probability problem which is influenced by the transmission interval. First, we utilize Reinforcement Learning method to estimate the stochastic delay of end-to-end paths. Then, we discuss problems of re-sequencing buffer occupancy distribution and the overflow probability. In this paper, we model the stochastic delay as a continuous random variable, and then, discuss its mean value and variance. Simulation result shows that the re-sequencing buffer overflow probability is influenced by the transmission intervals and the variance of stochastic delay.

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“…This is different from the previous works [15]- [17] which only focus on mean value of the random delay. The rest of this paper is organized as follows.…”

Section: Introductioncontrasting

confidence: 70%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Analysis of re-sequencing buffer overflow probability based on stochastic delay characteristics

Zhou

2013

2013 IEEE 24th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC)

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“…Packet reordering is of course also studied in many additional networking contexts, such as the parallel download of multiple parts of a given file [23], or in ARQ (Automatic Repeat reQuest) protocols [24]. Recently, Leith et al [25] considered the problem of encoding packets with independent probabilistic delays such that the probability that a packet can be decoded within a given decoding deadline is maximized.…”

Section: Related Workmentioning

confidence: 99%

The Switch Reordering Contagion: Preventing a Few Late Packets from Ruining the Whole Party

Rottenstreich

Horev

et al. 2014

IEEE Trans. Comput.

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Packet reordering has now become one of the most significant bottlenecks in next-generation switch designs. A switch practically experiences a reordering delay contagion, such that a few late packets may affect a disproportionate number of other packets. This contagion can have two possible forms. First, since switch designers tend to keep the switch flow order, i.e., the order of packets arriving at the same switch input and departing from the same switch output, a packet may be delayed due to packets of other flows with little or no reason. Further, within a flow, if a single packet is delayed for a long time, then all the other packets of the same flow will have to wait for it and suffer as well. In this paper, we suggest solutions against this reordering contagion. We first suggest several hash-based counter schemes that prevent inter-flow blocking and reduce reordering delay. We further suggest schemes based on network coding to protect against rare events with high queueing delay within a flow. Last, we demonstrate using both analysis and simulations that the use of these solutions can indeed reduce the resequencing delay. For instance, resequencing delays are reduced by up to an order of magnitude using real-life traces and a real hashing function.Index Terms-Switching theory, packet-switching networks • O. Rottenstreich and I. Keslassy are with the

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Packet reordering analysis for concurrent multipath transfer

Gao

Zhou

Yang

2013

Int J Communication

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SUMMARYPath diversity of different concurrent paths inevitably introduces out-of-order packet delivery, which leads to unnecessary retransmissions and a severely lowered data throughput. In order to analyze the fundamental behavior and influencing factors of packet reordering, several sets of simulation-based multipath experiments are conducted with different aggregating paths. In addition, the relationship between reordering and number of paths are discussed. Furthermore, an end-to-end measurement study of packet reordering in concurrent multipath transfer is presented. To simply the analysis process, a cumulative distribution function of transmission delay for each packet is used. The model is proved to be an effective one by contrastive analysis. Finally, some solutions to handle it are provided with a further discussion.

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Parallel downloads for streaming applications—a resequencing analysis

Cited by 9 publications

References 17 publications

Analysis of re-sequencing buffer overflow probability based on stochastic delay characteristics

Analysis of re-sequencing buffer overflow probability based on stochastic delay characteristics

The Switch Reordering Contagion: Preventing a Few Late Packets from Ruining the Whole Party

Packet reordering analysis for concurrent multipath transfer

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