Network coding mythbusting: why it is not about butterflies anymore

Médard, Muriel; Fitzek, Frank H. P.; Montpetit, Marie José; Rosenberg, Catherine

doi:10.1109/mcom.2014.6852100

Cited by 19 publications

(11 citation statements)

References 13 publications

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“…As we meticulously presented in previous studies [8], [16], [22], there are three types of decoders that the receiver might exploit to recover the original packets: inner, outer, and combined. A receiver using an inner decoder needs to receive n + r linearly independent packets and decode using operations defined in GF (2), which are computationally fast. This costs an additional delay for waiting n + r linearly independent packets.…”

Section: ) Fulcrum Network Coding (Fnc)mentioning

confidence: 99%

“…To better understand the decoding process with an inner and outer decoder, let's consider the example in Figure 1 with n = 4 and r = 2. Let's assume that after the outer and inner encoding processes the receiver gets a coded packet x 1 with the coding coefficients (2). This packet can be understood by the receiver in two different ways.…”

Section: ) Fulcrum Network Coding (Fnc)mentioning

confidence: 99%

“…where is a N × (n + r) matrix composed of random coefficient elements λ i,j in GF (2). It is well known that N transmission packets are sufficient to recover the n source packets of a generation [29].…”

Section: A Transmittermentioning

confidence: 99%

“…For that reason, increasing throughput in such networks is definitely required and much research has been conducted to achieve this goal. According to [2], network coding (NC) [3] is one of the most promising techniques to achieve maximum throughput, and also to reduce both energy consumption and delay [4]. In addition, by realizing path diversity, NC improves both the max-flow min-cut limit of the network and the robustness against data loss [5].…”

Section: Introductionmentioning

confidence: 99%

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Advanced Adaptive Decoder Using Fulcrum Network Codes

et al. 2019

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Reliable and effective forward error correction is challenging, especially in a heterogeneous transmission environment, due to the differences in computation capabilities of end devices. Using a complex code to achieve reliable communication leads to high computation costs and long decoding delay at devices with low computing power. Fulcrum codes, a variation of random linear network coding (RLNC), addresses that problem by combining two codes of large and small Galois field sizes. Thus, a Fulcrum decoder can decode using either field size. However, state-of-the-art Fulcrum decoders select and operate on a predetermined Galois field throughout the transmission session regardless of current states of received packets. We propose an inclusive and adaptive decoding process that decide when to operate on which Galois field in accordance with the computational capabilities and varying channel environments. Our comprehensive evaluation shows that the proposed adaptive decoding significantly reduces the computation complexity at end devices while simultaneously maintaining a high decoding probability with substantially low overhead and decoding delay.INDEX TERMS Adaptive decoder, heterogeneous devices, reliable decoding, network coding, fulcrum network codes.

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Section: ) Fulcrum Network Coding (Fnc)mentioning

confidence: 99%

Section: ) Fulcrum Network Coding (Fnc)mentioning

confidence: 99%

Section: A Transmittermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Advanced Adaptive Decoder Using Fulcrum Network Codes

et al. 2019

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“…Network coding could work in unicast or multicast networks [15]. In most cases, network coding works in multicast networks.…”

Section: Network Modelmentioning

confidence: 99%

Secure-Network-Coding-Based File Sharing via Device-to-Device Communication

Wang

2017

Journal of Electrical and Computer Engineering

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In order to increase the efficiency and security of file sharing in the next-generation networks, this paper proposes a large scale file sharing scheme based on secure network coding via device-to-device (D2D) communication. In our scheme, when a user needs to share data with others in the same area, the source node and all the intermediate nodes need to perform secure network coding operation before forwarding the received data. This process continues until all the mobile devices in the networks successfully recover the original file. The experimental results show that secure network coding is very feasible and suitable for such file sharing. Moreover, the sharing efficiency and security outperform traditional replication-based sharing scheme.

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5G Communication System: A Network Operator Perspective

Jacobfeuerborn

Fitzek

2018

5G Networks: Fundamental Requirements, Enabling Technologies, and Operations Management

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Network coding mythbusting: why it is not about butterflies anymore

Cited by 19 publications

References 13 publications

Advanced Adaptive Decoder Using Fulcrum Network Codes

Advanced Adaptive Decoder Using Fulcrum Network Codes

Secure-Network-Coding-Based File Sharing via Device-to-Device Communication

5G Communication System: A Network Operator Perspective

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