首页> 外文学位 >Performance evaluation of wireless ad hoc networks and the presence of heavy-tails & LRD.
【24h】

Performance evaluation of wireless ad hoc networks and the presence of heavy-tails & LRD.

机译:无线ad hoc网络的性能评估以及重尾和LRD的存在。

获取原文
获取原文并翻译 | 示例

摘要

Multi-hop wireless networks lack widespread deployment due to their performance issues. There are very few models which can aid detailed analysis of performance bottlenecks and design improvements. Our objective is to develop hybrid (analytical and numerical) models which can efficiently approximate the performance of wireless multi-hop networks. We focus on modeling the MAC and routing protocol performance, and their impact on network performance. For MAC layer modeling, we improve a fixed-point loss network model to evaluate throughput and packet loss for 802.11 MAC protocol. For routing, we model the OLSR protocol, one of the popular routing protocols. Unlike any work before, we give a combined model of a MAC and Routing Protocol which captures the cross-layer interaction. Most of the performance models assume smooth or exponential input traffic models in the usual Markovian framework. However, it is known, at least for wired networks, that traffic sources can have heavy-tails and the traffic arrival pattern bursty even at large timescales, which is characterized by self-similarity and long-range dependence (LRD). This can significantly impact network performance through higher queue-occupancy, service times, packet losses, etc. Both the presence of these phenomenon and their impact on network performance of wireless multi-hop networks has not be studied before. Hence, we study traffic LRD in three stages, which form the main contributions of this work.;Heavy-tails in traffic sources, for example file sizes on the web, have been attributed as the main causes of traffic LRD. Previous protocol studies, for both wired and wireless networks, have argued that the network protocols dynamics affect only the small-time scale properties, and that they cannot create traffic LRD by themselves. However, recent work show that ALOHA protocol can lead to heavy-tailed delays in certain situations. With that as a motivation, we investigate the role of more complex 802.11 MAC protocols in shaping the delays and traffic burstiness. We show, through simulations, that service times for 802.11 MAC, can indeed have power-law (or truncated heavy-tail) distributions. However, even with complex topologies with hidden-nodes, the maximum MAC service times are bounded at a few seconds. Hence, they are not sufficient to create traffic LRD.;Secondly, due to variable link conditions in wireless networks, the routing protocol can also cause changes in multi-hop routes even in a static topology. The link 'failure' detection mechanisms are different for wireless networks; a certain number of consecutive packet drops is usually used as indicator of link failure, even though these packet drops can be due to fading or congestion. Thus, the wireless medium can introduce spurious route changes which can potentially affect traffic burstiness at large timescales. We show, contrary to conventional wisdom, wireless multi-hop network protocols indeed create traffic burstiness at large time-scales. In particular, routing control packet losses at MAC due to congestion can lead to route oscillations in link-state routing protocols like OLSR. These route oscillations can create pseudo-traffic LRD. We modify our previous MAC and OLSR models to predict which network scenarios will lead to route oscillations. We also show, using our models, how we can appropriately tune the protocol design parameters to avoid route oscillations and traffic LRD.;Lastly, we investigate the impact of traffic burstiness on network performance. Service times of 802.11 MAC frames depends significantly on the congestion perceived in the wireless channel. Bursty traffic can also lead to increased retries or losses during periods to high load. We analyze the average achievable throughput at the MAC layer and the impact of traffic LRD. We show that traffic LRD can significantly impact network performance. However, contrary to our intuition, bursty traffic can lead to higher throughput in some scenarios. We give some models to explain and predict such behavior in simple 4 node topologies with two links. We use these models to characterize the 'capacity region' defined in terms of the MAC protocol functioning for these 2 link topologies. In particular, given bursty or smooth traffic on one link, we characterize what is the maximum achievable throughput ('capacity') on the other link as well as the sum capacity. The models show that the achievable / maximum throughput depends on the traffic burstiness at some load levels. Thus, it is important to use appropriate input traffic models for any good performance analysis.
机译:由于其性能问题,多跳无线网络缺乏广泛的部署。很少有模型可以帮助详细分析性能瓶颈和改进设计。我们的目标是开发能够有效估计无线多跳网络性能的混合(分析和数值)模型。我们专注于对MAC和路由协议性能及其对网络性能的影响进行建模。对于MAC层建模,我们改进了定点丢失网络模型,以评估802.11 MAC协议的吞吐量和数据包丢失。对于路由,我们对OLSR协议(流行的路由协议之一)进行建模。与以前的工作不同,我们给出了MAC和路由协议的组合模型,该模型捕获了跨层交互。大多数性能模型在通常的马尔可夫框架中都假定使用平滑或指数输入流量模型。但是,众所周知,至少对于有线网络,即使在较大的时间尺度上,流量源也可能具有重尾,并且流量到达模式会突然爆发,其特征是自相似性和远程依赖性(LRD)。这可能会通过更高的队列占用率,服务时间,数据包丢失等方式严重影响网络性能。这些现象的存在及其对无线多跳网络的网络性能的影响都尚未得到研究。因此,我们从三个阶段研究流量LRD,这构成了这项工作的主要贡献。;流量源中的重尾,例如网络上的文件大小,被认为是流量LRD的主要原因。先前针对有线和无线网络进行的协议研究都认为,网络协议动态性仅影响小规模规模的属性,并且它们本身无法创建流量LRD。但是,最近的工作表明,ALOHA协议在某些情况下可能导致严重的延迟。以此为动机,我们研究了更复杂的802.11 MAC协议在形成延迟和流量突发性中的作用。通过仿真,我们表明802.11 MAC的服务时间确实可以具有幂律(或截尾重尾)分布。但是,即使具有隐藏节点的复杂拓扑,最大MAC服务时间也限制在几秒钟之内。因此,它们不足以创建流量LRD。其次,由于无线网络中的可变链路条件,即使在静态拓扑中,路由协议也可能导致多跳路由发生变化。链路“故障”检测机制对于无线网络是不同的。通常将一定数量的连续数据包丢弃用作链接失败的指标,即使这些数据包丢弃可能是由于衰落或拥塞所致。因此,无线介质会引入虚假的路由更改,这可能会在较大的时间尺度上影响流量突发性。我们证明,与传统观点相反,无线多跳网络协议确实会在较大的时间尺度上造成流量突发性。特别是,由于拥塞导致MAC处的路由控制数据包丢失会导致链路状态路由协议(如OLSR)中的路由振荡。这些路线振荡会产生伪交通的LRD。我们修改了以前的MAC和OLSR模型,以预测哪些网络场景将导致路由振荡。我们还使用模型展示了如何适当调整协议设计参数,以避免路由振荡和流量LRD。最后,我们研究了流量突发性对网络性能的影响。 802.11 MAC帧的服务时间在很大程度上取决于无线信道中的拥塞程度。在高负载期间,突发流量还会导致重试次数增加或丢失。我们分析了MAC层上平均可实现的吞吐量以及流量LRD的影响。我们表明,流量LRD可以显着影响网络性能。但是,与我们的直觉相反,突发流量在某些情况下可能导致更高的吞吐量。我们提供一些模型来解释和预测具有两个链接的简单4节点拓扑中的行为。我们使用这些模型来表征根据这两种链路拓扑的MAC协议而定义的“容量区域”。特别是,考虑到一个链路上的突发流量或平稳流量,我们描述了另一条链路上最大可达到的吞吐量(“容量”)以及总容量。这些模型表明,可达到的/最大吞吐量取决于某些负载水平下的流量突发性。因此,重要的是要使用适当的输入流量模型进行任何良好的性能分析。

著录项

  • 作者

    Jain, Kaustubh.;

  • 作者单位

    University of Maryland, College Park.;

  • 授予单位 University of Maryland, College Park.;
  • 学科 Electrical engineering.
  • 学位 Ph.D.
  • 年度 2015
  • 页码 216 p.
  • 总页数 216
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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