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Composite extension finite fields for low overhead Network Coding: Telescopic codes

机译:低开销网络编码的复合扩展有限域:伸缩码

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Although Network Coding (NC) has been proven to increase throughput and reliability in communication networks, its adoption is typically hindered by the additional complexity it introduces at various nodes in the network and the overhead to signal the coding coefficients associated with each coded packet. This work advocates the use of multiple composite extension finite fields to address these challenges. The key of our approach is to design a series of finite fields where increasingly larger fields are based on a previous smaller field. For example, the design of a field with 256 elements F is based on polynomial arithmetic over a field with 16 elements F, in turn based on a field with 4 elements F. We propose a technique to modify standard Random Linear Network Coding (RLNC) to utilize a set of these fields instead of a single field and analyze the performance. The results show that total overhead is reduced due to reduced size of the coding vector, while maintaining low linear dependency between coded packets. The overhead can in some cases be reduced to less than one-fifth compared to standard RLNC and importantly the ability to recode is preserved.
机译:尽管已经证明网络编码(NC)可以提高通信网络的吞吐量和可靠性,但是它的采用通常受到其在网络中各个节点引入的额外复杂性以及用信号发送与每个编码数据包相关的编码系数的开销的阻碍。这项工作提倡使用多个复合扩展有限域来应对这些挑战。我们方法的关键是设计一系列有限域,其中越来越大的域基于先前的较小域。例如,具有256个元素F的字段的设计基于对具有16个元素F的字段的多项式算法,进而基于具有4个元素F的字段。我们提出了一种修改标准随机线性网络编码(RLNC)的技术利用一组这些字段而不是单个字段来分析性能。结果表明,由于减小了编码矢量的大小而减少了总开销,同时保持了编码分组之间的低线性相关性。在某些情况下,与标准RLNC相比,开销可以减少到不到五分之一,并且重要的是保留了重新编码的能力。

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