Multi-Source Coded Downloads

Braun, Patrik J.; Malak, Derya; Médard, Muriel; Ekler, Péter

doi:10.1109/icc.2019.8761983

Cited by 6 publications

(8 citation statements)

References 12 publications

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“…We use this to compare amount of received packets that increase the DoF at the client to all received packets. We also compared our measurement results to our previous work [8], where we construct a model to analyze multi-source networks. Our analysis and our measurements show similar trends.…”

Section: Resultsmentioning

confidence: 99%

“…It sends a packet from a generation that has the least received DoF and in transiting packets. We chose this method of scheduling a generation for sending because it has already shown potential to improve throughput in RLNC enhanced distributed systems [8].…”

Section: B Coded Mutpmentioning

confidence: 99%

“…We have shown that Random Linear Network Coding (RLNC) [7] may also be used to improve the throughput of a multi-source network [8]. RLNC creates linear combinations of the original packets using random coefficients.…”

Section: Introductionmentioning

confidence: 99%

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Enabling Multi-Source Coded Downloads

Braun

Malak

Médard

et al. 2019

2019 IEEE International Conference on Edge Computing (EDGE)

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In this paper, we introduce two multi-source download protocols for loosely orchestrated edge cloud scenarios involving mobile devices. We focus on services with high bandwidth and low delay requirements, like video streaming. We propose MUlti-source Transmission Protocol (MUTP) for uncoded multi-source data delivery and extend it with network coding capabilities to create coded MUTP. We investigate their throughput using a custom designed testbed. We present measurement results collected over eight months that include more than 630 GBs of video download. We show that even when downloading from only two sources, our protocols can match the heavily optimized HTTP protocol. Furthermore, by increasing the number of sources to four or higher, MUTP protocols can outperform the HTTP approach, reaching an up to threefold goodput increase.

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Section: Resultsmentioning

confidence: 99%

Section: B Coded Mutpmentioning

confidence: 99%

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Enabling Multi-Source Coded Downloads

Braun

Malak

Médard

et al. 2019

2019 IEEE International Conference on Edge Computing (EDGE)

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“…In this paper, we extend our previous works on coded multisource download [15], [21]. We propose two protocols for multi-source download and evaluate their goodput through measurements.…”

Section: A Main Contributionsmentioning

confidence: 96%

“…We have previously shown that Random Linear Network Coding (RLNC) [14] may also be used to improve the throughput of a multi-source network [15]. RLNC creates linear combinations of the original packets using random coefficients.…”

Section: Introductionmentioning

confidence: 99%

Practical Evaluation of Multi-Source Coded Downloads

2019

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In this paper, we introduce two multi-source download protocols for loosely orchestrated networks that have high potential in Information-Centric Networking (ICN). We focus on services with high bandwidth and low delay requirements, such as video streaming. We propose MUlti-source Transmission Protocol (MUTP) for uncoded multi-source data delivery and extend it with network coding capabilities to create Coded MUTP. We investigate their throughput using a custom-designed system that includes browser extensions and proxy servers. The browser extensions intercept YouTube video downloads and forward them through our proxy server, using parallel HTTP requests, Uncoded MUTP or Coded MUTP approach. We present measurement results collected in 2018-2019, over eleven months that include 1,300,000 log records from more than 960 GBs of video download. We show that even when downloading from only two sources, our protocols can match the heavily optimized HTTP. Furthermore, by increasing the number of sources to four or higher, MUTP protocols can outperform HTTP, reaching an up to threefold goodput (useful throughput) increase. In addition, we show that the proposed solution avoids the straggler problem, therefore adding more sources to a network increases its goodput.

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SpaRec: Sparse Systematic RLNC Recoding in Multi-Hop Networks

et al. 2021

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Sparse Random Linear Network Coding (RLNC) reduces the computational complexity of the RLNC decoding through a low density of the non-zero coding coefficients, which can be achieved through sending uncoded (systematic) packets. However, conventional recoding of sparse RLNC coded packets at an intermediate node in a multi-hop network increases the density of non-zero coding coefficients. We develop and evaluate sparsity-preserving recoding (SpaRec) strategies that preserve the low density of non-zero coding coefficients of sparse RLNC with systematic packets. We develop SpaRec strategies with and without decoding at the intermediate nodes, with and without a specified coding rate, as well as with finite and infinite recoding window lengths. We evaluate the SpaRec strategies in multi-hop networks in terms of packet loss, packet delivery delay, as well as recoding and decoding (computation) throughput. We find that the SpaRec strategies substantially improve the RLNC performance compared to conventional recoding.

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Multi-Source Coded Downloads

Cited by 6 publications

References 12 publications

Enabling Multi-Source Coded Downloads

Enabling Multi-Source Coded Downloads

Practical Evaluation of Multi-Source Coded Downloads

SpaRec: Sparse Systematic RLNC Recoding in Multi-Hop Networks

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