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Throughput-Optimal Multihop Broadcast on Directed Acyclic Wireless Networks

机译:有向无环无线网络上的吞吐量优化多跳广播

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We study the problem of efficiently disseminating packets in multi-hop wireless networks. At each time slot, the network controller activates a set of non-interfering links and forward selected copies of packets on each activated link. The maximum rate of commonly received packets is referred to as the broadcast capacity of the network. Existing policies achieve the broadcast capacity by balancing traffic over a set of spanning trees, which are difficult to maintain in a large and time-varying wireless network. In this paper, we propose a new dynamic algorithm that achieves the broadcast capacity when the underlying network topology is a directed acyclic graph (DAG). This algorithm is decentralized, utilizes local information only, and does not require the use of spanning trees. The principal methodological challenge inherent in this problem is the absence of work-conservation principle due to the duplication of packets, which renders usual queuing modeling inapplicable. We overcome this difficulty by studying relative packet deficits and imposing in-order delivery constraints to every node in the network. We show that in-order delivery is throughput-optimal in DAGs and can be exploited to simplify the design and analysis of optimal algorithms. Our capacity characterization also leads to a polynomial time algorithm for computing the broadcast capacity of any wireless DAG under the primary interference constraints. In addition, we propose a multiclass extension of our algorithm, which can be effectively used for broadcasting in any network with arbitrary topology. Simulation results show that the our algorithm has a superior delay performance as compared with the traditional tree-based approaches.
机译:我们研究了在多跳无线网络中有效分发数据包的问题。在每个时隙,网络控制器都会激活一组无干扰的链接,并在每个激活的链接上转发选定的数据包副本。通常接收到的数据包的最大速率称为网络的广播容量。现有策略通过平衡一组生成树上的流量来实现广播容量,而这些生成树在大型且随时间变化的无线网络中难以维护。在本文中,我们提出了一种新的动态算法,当基础网络拓扑为有向无环图(DAG)时,该算法可实现广播容量。该算法是分散的,仅利用本地信息,并且不需要使用生成树。该问题固有的主要方法挑战是由于数据包的重复而缺乏工作保存原则,这使得常规排队建模不适用。我们通过研究相对的数据包不足和对网络中的每个节点施加有序交付约束来克服此困难。我们表明,按顺序交付在DAG中是吞吐量最佳的,可以用来简化优化算法的设计和分析。我们的容量表征还导致了多项式时间算法,该算法可在主要干扰约束下计算任何无线DAG的广播容量。此外,我们提出了算法的多类扩展,可以有效地用于具有任意拓扑的任何网络中的广播。仿真结果表明,与传统的基于树的方法相比,我们的算法具有更好的延迟性能。

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