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Distributed Algorithms for Scheduling on Line and Tree Networks

机译:用于在线和树网络调度的分布式算法

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We have a set of processors (or agents) and a set of graph networks defined over some vertex set. Each processor can access a subset of the graph networks. Each processor has a demand specified as a pair of vertices (u.v), along with a profit; the processor wishes to send data between u and v. Towards that goal, the processor needs to select a graph network accessible to it and a path connecting u and v within the selected network. The processor requires exclusive access to the chosen path, in order to route the data. Thus, the processors are competing for routes/channels. A feasible solution selects a, subset of demands and schedules each selected demand on a graph network accessible to the processor owning the demand; the solution also specifies the paths to use for this purpose. The requirement is that for any two demands scheduled on the same graph network, their chosen paths must be edge disjoint. The goa.l is to output a solution having the maximum aggregate profit. Prior work has addressed the above problem in a distibuted setting for the special case where all the graph networks are simply paths (i.e. line-networks). Distributed constant factor approximation algorithms are known for this case. The main contributions of this paper are twofold. First we design a distributed constant factor approximation algorithm for the more general case of tree-networks. The core component of our algorithm is a tree-decomposition technique, which may be of independent interest. Secondly, for the case of line-networks, we improve the known approximation guarantees by a factor of 5. Our algorithms can also handle the capacitated scenario, wherein the demands and edges have bandwidth requirements and capacities, respectively.
机译:我们有一组处理器(或代理)以及在某个顶点集上定义的一组图形网络。每个处理器都可以访问图形网络的子集。每个处理器的需求指定为一对顶点(U.v),以及利润;处理器希望在U和V之间发送数据。朝向该目标,处理器需要选择可访问的图形网络以及连接所选网络内的u和v的路径。处理器需要对所选路径的独占访问权限,以便路由数据。因此,处理器正在竞争路由/通道。可行解决方案选择一个,需求子集,并在可访问的处理器上可访问的图形网络上调度每个选定的需求;该解决方案还指定用于此目的的路径。要求是,对于在相同的图形网络上计划的任何两个要求,它们所选择的路径必须是边缘不相交。 GOA.L是输出具有最大总利润的解决方案。在所有图形网络都是路径(即行网络)的特殊情况下,事先工作已经解决了上述问题。在这种情况下已知分布式恒定因子近似算法。本文的主要贡献是双重的。首先,我们设计一种分布式恒定因子近似算法,用于更常规的树网络。我们的算法的核心组件是一种树分解技术,可能具有独立的兴趣。其次,对于线网络的情况,我们将已知的近似保证提高了5倍。我们的算法还可以处理电容方案,其中需求和边缘分别具有带宽要求和容量。

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