论文标题
在线着色和在线图形问题的新型对手
Online Coloring and a New Type of Adversary for Online Graph Problems
论文作者
论文摘要
我们介绍了一种用于在线图形问题的新型对手。新的对手由单个整数$κ$进行参数化,该$κ$在在线图$ g $介绍期间随时可以使用的对手可以使用的连接组件数量上限。我们称这个对手为“ $κ$组件有界”,即简称$κ$ -CB。一方面,由于$κ$ -CB的约束,与经典对手相比,这种对手受到限制。另一方面,我们寻求仅通过$κ$参数的竞争比率,而不依赖输入长度$ n $,从而赋予了新的对手使用任意大型输入的对手。 我们在$κ$ -CB对手下学习在线着色。我们通过在新的对手下计算其在树木和二分图上的竞争比率来获得对现有算法$ firstFit $和$ cbip $的精细分析。令人惊讶的是,$ firstFit $胜过树木上的$ cbip $。在二手图方面,$ firstfit $在新的对手下不再具有竞争力,而$ cbip $最多使用$2κ$颜色。我们还研究了几类众所周知的图形类别,例如$ 3 $ - 可加油,$ C_K $ - free,$ d $ - 感应性,平面和有界的树宽,相对于$κ$ -CB的对手下的在线着色。我们证明,无界输入长度的额外对抗力大于对这些类别不存在竞争算法的连接组件数量的限制。
We introduce a new type of adversary for online graph problems. The new adversary is parameterized by a single integer $κ$, which upper bounds the number of connected components that the adversary can use at any time during the presentation of the online graph $G$. We call this adversary "$κ$ components bounded", or $κ$-CB for short. On one hand, this adversary is restricted compared to the classical adversary because of the $κ$-CB constraint. On the other hand, we seek competitive ratios parameterized only by $κ$ with no dependence on the input length $n$, thereby giving the new adversary power to use arbitrarily large inputs. We study online coloring under the $κ$-CB adversary. We obtain finer analysis of the existing algorithms $FirstFit$ and $CBIP$ by computing their competitive ratios on trees and bipartite graphs under the new adversary. Surprisingly, $FirstFit$ outperforms $CBIP$ on trees. When it comes to bipartite graphs $FirstFit$ is no longer competitive under the new adversary, while $CBIP$ uses at most $2κ$ colors. We also study several well known classes of graphs, such as $3$-colorable, $C_k$-free, $d$-inductive, planar, and bounded treewidth, with respect to online coloring under the $κ$-CB adversary. We demonstrate that the extra adversarial power of unbounded input length outweighs the restriction on the number of connected components leading to non existence of competitive algorithms for these classes.