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Broadcasting on large scale heterogeneous platforms under the bounded multi-port model

机译:界限多端口模型下大规模异构平台广播

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We consider the problem of broadcasting a large message in a large scale distributed platform. The message must be sent from a source node, with the help of the receiving peers which may forward the message to other peers. In this context, we are interested in maximizing the throughput (i.e. the maximum streaming rate, once steady state has been reached). The platform model does not assume that the topology of the platform is known in advance: we consider an Internet-like network, with complete potential connectivity. Furthermore, the model associates to each node local properties (incoming and outgoing bandwidth), and the goal is to build an overlay which will be used to perform the broadcast operation. We model contentions using the bounded multi-port model: a processor can be involved simultaneously in several communications, provided that its incoming and outgoing bandwidths are not exceeded. For the sake of realism, it is also necessary to bound the number of simultaneous connections that can be opened at a given node (ie its outdegree). We prove that unfortunately, this additional constraint makes the problem of maximizing the overall throughput NP-Complete. On the other hand, we also propose a polynomial time algorithm to solve this problem, based on a slight resource augmentation on the outdegree of the nodes.
机译:我们考虑在大规模分布式平台中广播大型消息的问题。在接收对等体的帮助下,必须从源节点发送消息,这可能将消息转发给其他对等体。在这种情况下,我们有兴趣最大化吞吐量(即最大流速率,一旦达到稳态,稳定状态)。平台模型并不假设平台的拓扑预先知道:我们考虑一种互联网等网络,具有完全潜在的连接。此外,模型关联到每个节点本地属性(传入和传出带宽),并且目标是构建将用于执行广播操作的覆盖层。我们使用界限多端口模型模型:可以在几种通信中同时介绍处理器,但是提供了其传入和传出带宽。为了实现现实,还需要绑定可以在给定节点(即其oderegree)的同时连接的数量。我们证明,不幸的是,这一额外约束使得最大化整体吞吐量NP完成的问题。另一方面,我们还提出了一种多项式时间算法来解决这个问题,基于节点的oderegree上的略有资源增强。

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