Network coding delay: A brute-force analysis

Nistor, Maricica; Barros, João; Vieira, Fausto; Vinhoza, Tiago T. V.; Widmer, Joerg

doi:10.1109/ita.2010.5454144

Cited by 7 publications

(4 citation statements)

References 13 publications

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“…In addition, a non-asymptotic analysis of the delay distributions of RLNC [14] and various multicast scenarios [15], [16], [17] have also been investigated. Research looking at the in-order delivery delay in uncoded systems is provided in [2] and [18]; while [19], [20], and [21] consider the inorder delivery delay of non-systematic coding schemes. However, these non-systematic schemes may not be the optimum strategy in networks with a long RT T .…”

Section: Related Workmentioning

confidence: 99%

A coded generalization of selective repeat ARQ

Cloud

Leith

Médard

2015

2015 IEEE Conference on Computer Communications (INFOCOM)

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Reducing the in-order delivery, or playback, delay of reliable transport layer protocols over error prone networks can significantly improve application layer performance. This is especially true for applications that have time sensitive constraints such as streaming services. We explore the benefits of a coded generalization of selective repeat ARQ for minimizing the in-order delivery delay. An analysis of the delay's first two moments is provided so that we can determine when and how much redundancy should be added to meet a user's requirements. Numerical results help show the gains over selective repeat ARQ, as well as the trade-offs between meeting the user's delay constraints and the costs inflicted on the achievable rate. Finally, the analysis is compared with experimental results to help illustrate how our work can be used to help inform system decisions.

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Section: Related Workmentioning

confidence: 99%

A coded generalization of selective repeat ARQ

Cloud

Leith

Médard

2015

2015 IEEE Conference on Computer Communications (INFOCOM)

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“…If the code is not systematic, only the coded packets are transmitted. Previous work has primarily focused on the decoding delay of non-systematic constructions [20], [21], [22], [23], [24], [25], [26], [27], and show that the decoding delay is essentially proportional to the block size. The in-order delivery delay of systematic block codes is lower than that of non-systematic codes but remains essentially proportional to the block size (with a smaller pre-factor than for non-systematic codes), see Cloud et al [28] and references therein.…”

Section: Block Codesmentioning

confidence: 99%

“…The last step follows from the fact that the decoding failure probability is zero if S 1 = 0 and for all S 1 ≥ 1 the decoding failure probability is upper bounded by (1 − 1 Q 2 ) k following the theorem 5. Putting together equations (24), (25) and Corollary 1, we have lim t→∞…”

Section: Proof Of Theorem 3 Part IImentioning

confidence: 99%

FEC for Lower In-Order Delivery Delay in Packet Networks

Karzand¹,

Leith²,

Cloud³

et al. 2015

Preprint

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We consider use of Forward Error Correction (FEC) to reduce the in-order delivery delay over packet erasure channels. We propose a class of streaming codes that is capacity achieving and provides a superior throughput-delay trade-off compared to block codes by introducing flexibility in where and when redundancy is placed. This flexibility results in significantly lower in-order delay for a given throughput for a wide range of network scenarios. Furthermore, a major contribution of this paper is the combination of queuing and coding theory to analyze the code's performance. Finally, we present simulation and experimental results illustrating the code's benefits.

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“…In addition, a non-asymptotic analysis of the delay distributions of random linear network coding (RLNC) ( [14]) and various multicast scenarios ( [15], [16], [17]) using a variant of the scheme in Figure 1(b) have also been investigated. Furthermore, the research that looks at the in-order packet delay is provided in [2] and [18] for uncoded systems, while [19], [20], and [21] considers the in-order packet delay for non-systematic coding schemes similar to the one shown in Figure 1(b). However, these non-systematic schemes may not be the optimum strategy in networks or communication channels with a long RT T .…”

Section: Related Workmentioning

confidence: 99%

In-Order Delivery Delay of Transport Layer Coding

Cloud¹,

Leith²,

Médard³

2014

Preprint

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A large number of streaming applications use reliable transport protocols such as TCP to deliver content over the Internet. However, head-of-line blocking due to packet loss recovery can often result in unwanted behavior and poor application layer performance. Transport layer coding can help mitigate this issue by helping to recover from lost packets without waiting for retransmissions. We consider the use of an on-line network code that inserts coded packets at strategic locations within the underlying packet stream. If retransmissions are necessary, additional coding packets are transmitted to ensure the receiver's ability to decode. An analysis of this scheme is provided that helps determine both the expected in-order packet delivery delay and its variance. Numerical results are then used to determine when and how many coded packets should be inserted into the packet stream, in addition to determining the trade-offs between reducing the in-order delay and the achievable rate. The analytical results are finally compared with experimental results to provide insight into how to minimize the delay of existing transport layer protocols.

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Network coding delay: A brute-force analysis

Cited by 7 publications

References 13 publications

A coded generalization of selective repeat ARQ

A coded generalization of selective repeat ARQ

FEC for Lower In-Order Delivery Delay in Packet Networks

In-Order Delivery Delay of Transport Layer Coding

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