首页> 外文期刊>Queueing systems >Concave switching in single-hop and multihop networks
【24h】

Concave switching in single-hop and multihop networks

机译:单跳和多跳网络中的凹切换

获取原文
获取原文并翻译 | 示例
       

摘要

Switched queueing networks model wireless networks, input-queued switches, and numerous other networked communications systems. We consider an (α, g)-switch policy; these policies provide a generalization of the MaxWeight policies of Tassiulas and Ephremides (IEEE Trans Autom Control 37(12):4936-1948, 1992) and the weighted α-fair with allocations of Mo and Walrand (IEEE/ACM Trans Netw 8(5):556-567, 2000) which are typically applied to Bandwidth Sharing Networks (Massoulie and Roberts in IEEE/ACM Trans Netw 10(3):320-328, 2002). For single-hop switch networks, we prove the maximum stability property for this class of randomized policies. Thus these policies have the same first-order behavior as the MaxWeight policies. However, for multihop networks some of these generalized polices address a number of critical weakness of the MaxWeight/BackPressure policies. For multihop networks with fixed routing, we consider a policy called the Proportional Scheduler (or (1, log)-policy). In this setting, the BackPressure policy is maximum stable, but must maintain a queue at each node for every route destination, which typically grows rapidly with a network's size. However, the Proportional Scheduler only needs to maintain a queue for each outgoing link, which is typically bounded in number. As is common with Internet routing, by maintaining per-link queueing, each node only needs to know the next hop for each packet and not its entire route. Further, in contrast to BackPressure, the Proportional Scheduler does not compare downstream queue lengths to determine weights; only local link information is required. This leads to greater potential for decomposed implementations of the policy. Through a reduction argument and an entropy argument, we demonstrate that, while maintaining substantially less queueing overhead, the Proportional Scheduler achieves maximum throughput stability.
机译:交换排队网络对无线网络,输入排队的交换机和许多其他联网的通信系统进行建模。我们考虑(α,g)切换策略;这些策略提供了Tassiulas和Ephremides(IEEE Trans Autom Control 37(12):4936-1948,1992)的MaxWeight策略的一般化,以及Mo和Walrand分配的加权α-fair(IEEE / ACM Trans Netw 8(5) ):556-567,2000),通常应用于带宽共享网络(IEEE / ACM Trans Netw 10(3):320-328,2002中的Massoulie和Roberts)。对于单跳交换网络,我们证明了此类随机策略的最大稳定性。因此,这些策略具有与MaxWeight策略相同的一阶行为。但是,对于多跳网络,其中一些通用策略解决了MaxWeight / BackPressure策略的许多严重缺陷。对于具有固定路由的多跳网络,我们考虑一种称为比例调度程序(或(1,对数)策略)的策略。在此设置中,BackPressure策略是最大稳定的,但是必须为每个路由目的地在每个节点上维护一个队列,该队列通常随着网络的大小而迅速增长。但是,比例调度程序仅需要为每个传出链接维护一个队列,该队列通常以数字为界。与Internet路由一样,通过维护每个链路队列,每个节点仅需要知道每个数据包的下一跳,而不必知道其整个路由。此外,与BackPressure相比,比例调度程序不比较下游队列长度来确定权重;只需要本地链接信息。这导致分解该政策的实施的更大潜力。通过减少参数和熵参数,我们证明了,在保持队列开销少得多的同时,比例调度程序实现了最大的吞吐量稳定性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号