Fulcrum Network Codes: A Code for Fluid Allocation of Complexity
Fulcrum Network Codes: A Code for Fluid Allocation of Complexity
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支点网络代码：复杂性流体分配的代码
DOI：
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发表时间：
2014
期刊：
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通讯作者：
F. Fitzek
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文献类型：
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作者：
D. Lucani;M. Pedersen;J. Heide;F. Fitzek
本文提出了Fulfilling网络编码，它是一种网络编码框架，它实现了三个看似矛盾的目标：（i）在生成n个分组时，将编码系数开销减少到几乎每个分组n比特;（ii）在必要时，在中间节点仅使用GF（2）运算来操作网络，大大降低了网络的复杂性;（iii）为高端接收器提供接近于高端场网络编码系统的端到端性能，同时迎合在GF（2）中解码的低端接收器。由于（ii）和（iii），Fulfill码具有迄今为止在网络编码文献中缺失的独特特性：它们为网络提供了灵活性，可以根据当前负载，网络条件甚至分散的能量目标将计算复杂性分散到不同设备上。在我们的框架的核心在于使用扩展域GF（2 h）在源处进行预编码的想法，以使用线性映射来增加网络所看到的维数。富勒烯码可以使用任何高域线性码来进行预编码，例如，Reed-Solomon，预编码的结构决定了结果代码的一些关键特性。例如，系统结构提供在使用相同数据流的同时管理异构接收器的能力。我们的分析表明，在预编码过程中创建的额外维度的数量控制延迟，开销和复杂性之间的权衡。我们的实现和测量表明，Fulfill实现了类似的解码概率高场随机线性网络编码（RLNC）的方法，但编码器/解码器是一个数量级更快。
This paper proposes Fulcrum network codes, a network coding framework that achieves three seemingly conflicting objectives: (i) to reduce the coding coefficient overhead to almost n bits per packet in a generation of n packets; (ii) to operate the network using only GF(2) operations at intermediate nodes if necessary, dramatically reducing complexity in the network; (iii) to deliver an end-to-end performance that is close to that of a high-field network coding system for high-end receivers while simultaneously catering to low-end receivers that decode in GF(2). As a consequence of (ii) and (iii), Fulcrum codes have a unique trait missing so far in the network coding literature: they provide the network with the flexibility to spread computational complexity over different devices depending on their current load, network conditions, or even energy targets in a decentralized way. At the core of our framework lies the idea of precoding at the sources using an expansion field GF(2h) to increase the number of dimensions seen by the network using a linear mapping. Fulcrum codes can use any high-field linear code for precoding, e.g., Reed-Solomon, with the structure of the precode determining some of the key features of the resulting code. For example, a systematic structure provides the ability to manage heterogeneous receivers while using the same data stream. Our analysis shows that the number of additional dimensions created during precoding controls the trade-off between delay, overhead, and complexity. Our implementation and measurements show that Fulcrum achieves similar decoding probability as high field Random Linear Network Coding (RLNC) approaches but with encoders/decoders that are an order of magnitude faster.