未来移动架构中一种高效的存储路由

S.Sumithra, A.Hena Rubavathy
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摘要

本文研究了通用存储感知路由(GSTAR)协议的设计和评估,该协议将用于移动优先的未来互联网架构。GSTAR协议使用网络内存储来提高无线接入网络的服务质量和吞吐量,无线接入网络具有不同的无线电链路质量和/或断开。这些增益是通过路由器的短期缓冲来消除路径质量的波动,以及延迟容忍存储来克服移动设备的完全断开连接来实现的。利用基于ns-3的仿真模型,评估了GSTAR协议在典型无线接入网场景下的性能,并对关键设计参数进行了研究。GSTAR中的每个节点维护两种拓扑信息。分区内图包含了当前网络分区中所有节点之间的路径质量信息。路径质量由两个指标决定:短期和长期预期传输时间。每个no de使用存储/转发决策阈值比较这两个指标,并在发现路径退化并期望它在未来可能得到改善时存储数据。分区间图给出了网络中无节点之间连接模式的概率视图。它用于断开连接或分区的情况。结果表明,当链路质量波动是随机的时,移动平均方案效果较好,而对于周期性中断的开关信道,建议采用指数加权移动平均方案。在每种情况下都提供了模拟结果,显示了自适应阈值设置相对于早期工作中考虑的基线非自适应情况的好处。
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An Efficient Storage Routing In FutureMobile Architecture
This thesis presents an investigation of the designand evaluation of the generalized storage aware routing (GSTAR) protocol proposed for use in the Mobility First future Internet architecture. The GSTAR protocol uses innetwork storage to improve service quality and throughput in wireless access networks with varying radio link quality and/or disconnection. These gains are achieved using a combination of short-term buffering at routers to smooth out fluctuations in path quality along with delay-tolerant storage, to overcome total disconnection of the mobile device. The performance of the GSTAR protocol is evaluated for exemplary wireless access network scenarios using ns-3 based simulation models, and key design parameters are investigated. Each node in GSTAR maintains two kinds of topology information. The intrapartition graph contains information about path quality between no des in the current partition of the network. The path quality is determined using two metrics: short term and long term expected transmission time. Every no de compares these two metrics using the store/forward decision threshold and stores the data on finding that the path is degraded with the expectation that it may improve in the future. Inter-partition graph gives a probabilistic view of the connection patterns between no des in the network. It is used in the event of disconnections or partitions. The results show that if link quality fluctuations are random, the moving average scheme works well, while an exponentially weighted moving average is recommended for on-off channels with periodic outages. Simulation results are provided in each case, showing the benefit of adaptive threshold settings over the baseline non-adaptive case considered in earlier work.
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