词典编纂产品和非线性网络编码的力量

A. Błasiak, Robert D. Kleinberg, E. Lubetzky
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引用次数: 95

摘要

我们介绍了一种建立和放大网络编码和索引编码问题之间参数差距的技术。该技术使用线性规划来建立组合参数和编码理论参数之间的分离,并应用超图词典学产品来扩大这些分离。这需要组合字典乘数的对偶解,并证明这是乘积的有效对偶解。我们的结果具有足够的普遍性,可以应用于一大类线性规划。这种线性规划和词典编纂产物的混合提供了一种构造硬实例的方法,其中组合或编码理论参数之间的差距是多项式大的。我们发现多项式的差距在情况下,其中最大的先前已知的差距只是小的常数因素或完全未知。最值得注意的是,我们展示了线性和非线性网络编码率之间的多项式分离。这涉及到利用拟阵和索引编码之间的联系,在线性和非线性索引编码率之间建立以前未知的分离。我们还构造了在广播率和平凡下界之间存在多项式间隙的索引编码问题,该下界之前没有已知的间隙。
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Lexicographic Products and the Power of Non-linear Network Coding
We introduce a technique for establishing and amplifying gaps between parameters of network coding and index coding problems. The technique uses linear programs to establish separations between combinatorial and coding-theoretic parameters and applies hyper graph lexicographic products to amplify these separations. This entails combining the dual solutions of the lexicographic multiplicands and proving that this is a valid dual solution of the product. Our result is general enough to apply to a large family of linear programs. This blend of linear programs and lexicographic products gives a recipe for constructing hard instances in which the gap between combinatorial or coding-theoretic parameters is polynomially large. We find polynomial gaps in cases in which the largest previously known gaps were only small constant factors or entirely unknown. Most notably, we show a polynomial separation between linear and non-linear network coding rates. This involves exploiting a connection between matroids and index coding to establish a previously unknown separation between linear and non-linear index coding rates. We also construct index coding problems with a polynomial gap between the broadcast rate and the trivial lower bound for which no gap was previously known.
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