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Signal Processing for Caching Networks and Non-volatile Memories

机译:缓存网络和非易失性存储器的信号处理

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The recent information explosion has created a pressing need for faster and more reliable data storage and transmission schemes. This thesis focuses on two systems: caching networks and non-volatile storage systems. It proposes network protocols to improve the efficiency of information delivery and signal processing schemes to reduce errors at the physical layer as well.;This thesis first investigates caching and delivery strategies for content delivery networks. Caching has been investigated as a useful technique to reduce the network burden by prefetching some contents during off-peak hours. Coded caching proposed by Maddah-Ali and Niesen is the foundation of our algorithms and it has been shown to be a useful technique which can reduce peak traffic rates by encoding transmissions so that different users can extract different information from the same packet. Content delivery networks store information distributed across multiple servers, so as to balance the load and avoid unrecoverable losses in case of node or disk failures. On one hand, distributed storage limits the capability of combining content from different servers into a single message, causing performance losses in coded caching schemes. But, on the other hand, the inherent redundancy existing in distributed storage systems can be used to improve the performance of those schemes through parallelism. This thesis proposes a scheme combining distributed storage of the content in multiple servers and an efficient coded caching algorithm for delivery to the users. This scheme is shown to reduce the peak transmission rate below that of state-of-the-art algorithms.;Then we study the trade-off between the network traffic load and disk I/O for caching networks. Coded caching can reduce traffic load by broadcasting coded messages that can benefit multiple users but, in the case with redundant requests, it requires reading some data segments multiple times to compose different coded messages. Hence, coded caching requires more disk I/Os than uncoded transmission. This thesis proposes caching and delivery algorithms which combine coded and uncoded transmission to strike a trade-off between traffic load and disk I/Os. Our algorithms can improve both the average and worst case performance in terms of the user requests.;Finally, we broaden our perspective to look at the storage hardware. Two methods are proposed which are suitable for NAND flash technology: multi-page read and spreading modulation. The first one reads multiple wordlines simultaneously and returns a combination of their stored information. This multi-page read method is shown to be useful for equalizing the inter-cell interference, reduce the damage caused by erase operations, and speed up the decoding of some codes, such as WOM codes. Then a new data representation scheme is proposed which increases endurance and significantly reduces the probability of error caused by inter-cell-interference. This data representation scheme is based on using an orthogonal code to spread each bit across multiple cells, resulting in lower variance for the voltages being programmed. We also study an up-and-coming memory technology, ReRAM, with a different set of challenges. Specifically, we build a simple analytic model for the voltage drop and sneak currents in MLC-ReRAM arrays as a form of inter-cell-interference and proposes two techniques to minimize the resulting BER: distribution shaping and spreading modulation, which is extended from that of NAND flash.
机译:最近的信息爆炸已经迫切需要更快,更可靠的数据存储和传输方案。本文主要研究两个系统:缓存网络和非易失性存储系统。提出了提高信息传递效率的网络协议,并提出了减少物理层错误的信号处理方案。本文首先研究了内容传递网络的缓存和传递策略。缓存已被研究为通过在非高峰时段预取一些内容来减轻网络负担的有用技术。 Maddah-Ali和Niesen提出的编码缓存是我们算法的基础,它已被证明是一种有用的技术,可以通过对传输进行编码来降低峰值流量速率,以便不同的用户可以从同一数据包中提取不同的信息。内容交付网络存储分布在多个服务器上的信息,以平衡负载并避免在节点或磁盘出现故障时造成不可恢复的损失。一方面,分布式存储限制了将来自不同服务器的内容组合为单个消息的能力,从而导致编码缓存方案的性能下降。但是,另一方面,分布式存储系统中存在的固有冗余可用于通过并行提高这些方案的性能。本文提出了一种将内容在多个服务器中的分布式存储与有效的编码缓存算法相结合的方案,以将其交付给用户。该方案可将峰值传输速率降低到最先进的算法之下。然后,我们研究了缓存网络中网络流量负载和磁盘I / O之间的权衡。编码缓存可以通过广播编码消息来减少流量负载,这可以使多个用户受益,但是在有冗余请求的情况下,它需要多次读取某些数据段以组成不同的编码消息。因此,编码缓存比未编码传输需要更多的磁盘I / O。本文提出了一种缓存和传递算法,该算法结合了编码和非编码传输,以在流量负载和磁盘I / O之间进行权衡。我们的算法可以根据用户请求提高平均性能和最坏情况的性能。最后,我们扩大了视野,着眼于存储硬件。提出了两种适用于NAND闪存技术的方法:多页读取和扩频调制。第一个同时读取多个字线并返回其存储信息的组合。该多页读取方法显示出可用于均衡小区间干扰,减少擦除操作造成的损坏以及加快某些代码(例如WOM代码)的解码。然后提出了一种新的数据表示方案,该方案可以增加耐久性,并显着降低由小区间干扰引起的错误概率。该数据表示方案基于使用正交码将每个位扩展到多个单元中,从而导致所编程电压的方差较小。我们还研究了一种新兴的存储技术ReRAM,它面临着一系列不同的挑战。具体来说,我们以小区间干扰的形式针对MLC-ReRAM阵列中的电压降和潜电流建立了一个简单的分析模型,并提出了两种使BER最小化的技术:分布整形和扩展调制,从此扩展了NAND闪存。

著录项

  • 作者

    Luo, Tianqiong.;

  • 作者单位

    Purdue University.;

  • 授予单位 Purdue University.;
  • 学科 Electrical engineering.
  • 学位 Ph.D.
  • 年度 2018
  • 页码 134 p.
  • 总页数 134
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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