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雷达卡
摘要翻译：
本文研究了cache辅助内容传递在一个具有$P$服务器和$K$用户的多服务器系统中的应用，每个系统都配有一个本地cache存储器。在交付阶段，每个用户随机连接到$p$服务器中的任何$\rho$。由于多个服务器的可用性，这些服务器可以模拟存储容量有限的小型基站，可以在减少每个服务器的存储容量和降低每个服务器的交付率的情况下满足用户的需求；然而，与单个服务器同时服务于所有用户相比，这也导致减少了多播机会。提出了一种联合存储和主动缓存方案，该方案利用了跨服务器的编码存储、在用户处的非编码缓存放置和编码交付。研究了来自服务器的\textit{连续}和\textit{同时}传输的传递\textit{延迟}。结果表明，在连续传输的情况下，可达到的平均传递延迟与单个服务器的可达到的平均传递延迟相当，而两者之间的差距取决于服务器间的可用冗余，并可以通过增加SBSS的存储容量来减小。
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英文标题：
《Coded Caching in a Multi-Server System with Random Topology》
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作者：
Nitish Mital, Deniz Gunduz and Cong Ling
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最新提交年份：
2018
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分类信息：
一级分类：Computer Science 计算机科学
二级分类：Information Theory 信息论
分类描述：Covers theoretical and experimental aspects of information theory and coding. Includes material in ACM Subject Class E.4 and intersects with H.1.1.
涵盖信息论和编码的理论和实验方面。包括ACM学科类E.4中的材料，并与H.1.1有交集。
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一级分类：Electrical Engineering and Systems Science 电气工程与系统科学
二级分类：Signal Processing 信号处理
分类描述：Theory, algorithms, performance analysis and applications of signal and data analysis, including physical modeling, processing, detection and parameter estimation, learning, mining, retrieval, and information extraction. The term "signal" includes speech, audio, sonar, radar, geophysical, physiological, (bio-) medical, image, video, and multimodal natural and man-made signals, including communication signals and data. Topics of interest include: statistical signal processing, spectral estimation and system identification; filter design, adaptive filtering / stochastic learning; (compressive) sampling, sensing, and transform-domain methods including fast algorithms; signal processing for machine learning and machine learning for signal processing applications; in-network and graph signal processing; convex and nonconvex optimization methods for signal processing applications; radar, sonar, and sensor array beamforming and direction finding; communications signal processing; low power, multi-core and system-on-chip signal processing; sensing, communication, analysis and optimization for cyber-physical systems such as power grids and the Internet of Things.
信号和数据分析的理论、算法、性能分析和应用，包括物理建模、处理、检测和参数估计、学习、挖掘、检索和信息提取。“信号”一词包括语音、音频、声纳、雷达、地球物理、生理、（生物）医学、图像、视频和多模态自然和人为信号，包括通信信号和数据。感兴趣的主题包括：统计信号处理、谱估计和系统辨识；滤波器设计；自适应滤波/随机学习；（压缩）采样、传感和变换域方法，包括快速算法；用于机器学习的信号处理和用于信号处理应用的机器学习；网络与图形信号处理；信号处理中的凸和非凸优化方法；雷达、声纳和传感器阵列波束形成和测向；通信信号处理；低功耗、多核、片上系统信号处理；信息物理系统的传感、通信、分析和优化，如电网和物联网。
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一级分类：Mathematics 数学
二级分类：Information Theory 信息论
分类描述：math.IT is an alias for cs.IT. Covers theoretical and experimental aspects of information theory and coding.
它是cs.it的别名。涵盖信息论和编码的理论和实验方面。
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英文摘要：
Cache-aided content delivery is studied in a multi-server system with $P$ servers and $K$ users, each equipped with a local cache memory. In the delivery phase, each user connects randomly to any $\rho$ out of $P$ servers. Thanks to the availability of multiple servers, which model small base stations with limited storage capacity, user demands can be satisfied with reduced storage capacity at each server and reduced delivery rate per server; however, this also leads to reduced multicasting opportunities compared to a single server serving all the users simultaneously. A joint storage and proactive caching scheme is proposed, which exploits coded storage across the servers, uncoded cache placement at the users, and coded delivery. The delivery \textit{latency} is studied for both \textit{successive} and \textit{simultaneous} transmission from the servers. It is shown that, with successive transmission the achievable average delivery latency is comparable to that achieved by a single server, while the gap between the two depends on $\rho$, the available redundancy across servers, and can be reduced by increasing the storage capacity at the SBSs.
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PDF链接：
https://arxiv.org/pdf/1712.00649
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