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Resolving the connectivity-throughput trade-off in random networks

机译:解决随机网络中的连接吞吐量问题

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The discrepancy between the upper bound on throughput scaling in wireless networks and the throughput scaling in random networks is due to the connectivity-throughput trade-off. In a random network with λ nodes, throughput scales by a factor of √logλ worse compared to the upper bound because of the uncertainty in the nodes'' location. In this work, nodes know their location and employ power control. The expected throughput-progress is analyzed for a nearest neighbor forwarding strategy, which benefits from power control by reducing spatial contention. By this, the connectivity-throughput trade-off is resolved and the upper bound is achieved.
机译:无线网络中吞吐量缩放的上限与随机网络中吞吐量缩放的上限之间的差异是由于连接吞吐量之间的权衡所致。在具有λ个节点的随机网络中,由于节点位置的不确定性,与上限相比,吞吐量的缩放系数为√logλ差。在这项工作中,节点知道其位置并采用功率控制。针对最近的邻居转发策略分析了预期的吞吐量进度,该策略可通过减少空间竞争而受益于功率控制。通过这种方式,解决了连接吞吐量的权衡问题并达到了上限。

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