In the online balanced graph repartitioning problem, one has to maintain a clustering of $n$ nodes into $\ell$ clusters, each having $k = n / \ell$ nodes. During runtime, an online algorithm is given a stream of communication requests between pairs of nodes: an inter-cluster communication costs one unit, while the intra-cluster communication is free. An algorithm can change the clustering, paying unit cost for each moved node. This natural problem admits a simple $O(\ell^2 \cdot k^2)$-competitive algorithm COMP, whose performance is far apart from the best known lower bound of $\Omega(\ell \cdot k)$. One of open questions is whether the dependency on $\ell$ can be made linear; this question is of practical importance as in the typical datacenter application where virtual machines are clustered on physical servers, $\ell$ is of several orders of magnitude larger than $k$. We answer this question affirmatively, proving that a simple modification of COMP is $(\ell \cdot 2^{O(k)})$-competitive. On the technical level, we achieve our bound by translating the problem to a system of linear integer equations and using Graver bases to show the existence of a ``small'' solution.
翻译:在在线平衡图再分配问题中,人们需要将美元节点组合成美元= ell美元组合,每个节点都有美元= n /\ ell $ 节点。 在运行期间, 给在线算法提供对结点之间一系列通信请求: 组合间通信费用为1个单位, 而集群内通信是免费的。 算法可以改变组合, 支付每个移动节点的单位成本。 这个自然问题承认了一个简单的美元( ell=2\ cdot k% 2), 具有竞争力的算法 Comp Comp, 其性能远远不同于最已知的美元= omega (ell\\\ cdot k) 。 一个尚未解决的问题是, 对$\ ell 的依赖能否成为线性; 这个问题具有实际重要性, 因为在典型的数据中心应用程序中, 虚拟机器被组合在物理服务器上, $\ ell$ 是几个比 $k$ 更大的数量。 我们肯定地回答这个问题, 能够证明, Compaticle mang a rial deal deal lemental le lemental develop lemental lexal lexal lexal lement lement lements legroqut lex lement legreal legropal lex legal lexxild lex lex lexxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx