arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1004.1379cs.ITmath.COmath.IT
收藏

通过线性规划的索引编码

Index coding via linear programming

Anna Blasiak, Robert Kleinberg, Eyal Lubetzky

摘要:

索引编码最近受到了相当大的关注,部分原因是现实世界的应用,部分原因是它与网络编码的联系。索引编码的基本设置将问题输入编码为无向图,并且基本参数是广播速率$β$,对于足够长的消息的每比特平均通信成本(即,非线性向量容量)。最近关于$β$的非平凡界限是从Bar-Yossef等人(2006)、Lubetzky和Stav(2007)以及Alon等人(2008)对其他索引编码能力(例如标量能力$β_1$)的研究中得出的。然而,这些间接的界限对$β$的行为没有什么启示:没有已知的多项式时间算法可以在一般网络中将$β$近似到非平凡(即$o(n)$)因子内,并且对于索引编码是非平凡的任何图,$β$的确切值仍然是未知的。我们的主要贡献是一个直接的信息理论分析的广播速率$β$使用线性程序,在以前的方法相比,$β$与图论参数。这使我们能够解决上述两个悬而未决的问题。我们提供了一个多项式时间的算法与非平凡的近似比计算$β$在一个一般的网络,以及一个多项式时间的决策过程,用于识别实例与$β=2$。此外,我们精确定位$β$的各类图(例如,循环群的各种凯莱图),从而同时提高了以前已知的上限和下限,这些图。通过这种方法,我们构造的图之间的差异$β$和它的平凡下界是线性的顶点数和那些$β$是一致有界的,而它的上限来自天真的编码方案是多项式差。

英文摘要:

Index Coding has received considerable attention recently motivated in part by real-world applications and in part by its connection to Network Coding. The basic setting of Index Coding encodes the problem input as an undirected graph and the fundamental parameter is the broadcast rate $β$, the average communication cost per bit for sufficiently long messages (i.e. the non-linear vector capacity). Recent nontrivial bounds on $β$ were derived from the study of other Index Coding capacities (e.g. the scalar capacity $β_1$) by Bar-Yossef et al (2006), Lubetzky and Stav (2007) and Alon et al (2008). However, these indirect bounds shed little light on the behavior of $β$: there was no known polynomial-time algorithm for approximating $β$ in a general network to within a nontrivial (i.e. $o(n)$) factor, and the exact value of $β$ remained unknown for any graph where Index Coding is nontrivial. Our main contribution is a direct information-theoretic analysis of the broadcast rate $β$ using linear programs, in contrast to previous approaches that compared $β$ with graph-theoretic parameters. This allows us to resolve the aforementioned two open questions. We provide a polynomial-time algorithm with a nontrivial approximation ratio for computing $β$ in a general network along with a polynomial-time decision procedure for recognizing instances with $β=2$. In addition, we pinpoint $β$ precisely for various classes of graphs (e.g. for various Cayley graphs of cyclic groups) thereby simultaneously improving the previously known upper and lower bounds for these graphs. Via this approach we construct graphs where the difference between $β$ and its trivial lower bound is linear in the number of vertices and ones where $β$ is uniformly bounded while its upper bound derived from the naive encoding scheme is polynomially worse.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑