Network Caching for Efficient Multimedia Content Delivery

呈指数级增长的多媒体信息内容已成为现代通信网络的核心问题。这是对传统通信网络的一种范式转变，传统通信网络的主要功能是信息传输，而服务改进的平等可以通过更好地确定带宽和交换资源的大小来实现。然而，在信息存储发挥核心作用的网络中，如果没有信息缓存、预取和/或镜像的帮助，服务质量的重大改善就不可能成功。可以争辩说，即使可用的空闲带宽是无限的，信息集中在少量服务器上也会导致服务器过载，导致不可接受的下载延迟。这一普遍问题导致了在网络系统工程文献中关于Web缓存的研究研究的爆炸性增长。虽然这项工作贡献了重要的工程解决方案，但其中大部分是临时的和非正式的。事实上，在大量关于缓存研究的文献中，很少有涉及数学基础的论文，特别是那些支撑随机模型的论文。此外，人们很少在缓存结构和算法的非平凡随机或平均情况性质的严格设置中找到证据。我们在这里的论点是，需要更系统的方法。这一提议描述了一个满足这一需求的项目；更广泛地说，我们概述了一种集中于基本设计问题的系统处理，在处理这些问题时，将实验、分析和统计测量结合在一起。网络缓存设计的目标是减少访问延迟、流量拥塞和服务器负载。这些目标只有通过深思熟虑的设计才能实现，该设计突出了许多重要的和具有挑战性的研究课题。一些基本的问题仍然没有明确的答案，包括：动态缓存和带有到期时间的缓存；易于实现的启发式算法的设计和分析；请求序列中的局部性对缓存性能的影响；低带宽访问环境中的缓存和预取，特别是无线Web访问；缓存分配和大小问题；以及Web图性能建模。扩展知识库并深入了解这些和其他几个同样基本的缓存系统设计问题是本提案的主要主题。最终目标是利用改进后的知识库开发一个实验测试平台，以实现实际可行和高效的网络缓存系统。这里确定的研究主题的内在复杂性，以及作为一个整体的网络缓存问题，必然会发挥所有可用的研究工具。因此，在方法论上，拟议的研究范围从数学建模和分析到统计测量和实验。我们的结果的影响，由于它们的交叉学科性质，将不仅限于设计多媒体网络缓存系统，而且可能导致改进计算机算法、软件工程、概率论和运筹学等相关领域的问题解决技术。

Exponentially increasing multimedia information content has become a problem at theheart of modern communication networks. This is a paradigm shift from traditional com-munication networks, where the primary function is information transmission, and wherequality of service improvements are attainable through better dimensioning of bandwidthand switching resources. However, in networks where information storage plays a centralrole, major improvements in quality of service can not be successful without the help ofcaching, prefetching and/or mirroring of information. It can be argued that even if anunlimited amount of free bandwidth were available, the concentration of information on asmall number of servers would cause server overloads, resulting in unacceptable downloadlatencies. This general problem has created the explosion of research studies that are to be foundin the network systems engineering literature on Web caching. Although this work hascontributed important engineering solutions, much of it is ad hoc and informal. Indeed, inthe large literature on caching research, it is rare to find papers dealing with mathematicalfoundations, especially those underpinning stochastic models. Also, one rarely finds proofs ina rigorous setting of nontrivial stochastic or average-case properties of caching structures andalgorithms. It is our thesis here that more systematic approaches are needed. This proposaldescribes a project to meet this need; more generally, we outline a systematic treatmentthat focuses on fundamental design issues, one that, in dealing with these issues, integratesexperimentation, analysis and statistical measurements. Network cache design objectives are reductions in access latency, traffic congestion, andserver loads. These objectives can be attained only through a thoughtful design that ad-dresses many important and challenging research topics. Some of the fundamental questionsthat remain without definitive answers include: dynamic caching and caching with expirationtimes; design and analysis of easily implemented heuristic algorithms; impact of locality inrequest sequences on caching performance; caching and prefetching in low bandwidth accessenvironments, with a special emphasis on wireless Web accesses; cache allocation and sizingproblems; and Web-graph performance modeling. Extending the knowledge base and deep-ening our insight into these and several other equally fundamental caching system designproblems is the main theme of this proposal. The ultimate goal is to utilize this improvedknowledge base to develop an experimental testbed for achieving practically feasible andefficient network caching systems. The inherent complexity of the research topics identified here, and the network cachingproblem as a whole, necessarily call into play all available research tools. Thus, methodologi-cally, the scope of the proposed research ranges from mathematical modeling and analysis tostatistical measurements and experimentation. The impact of our results, by their interdis-ciplinary nature, will not just be limited to designing multimedia network caching systems,but will potentially lead to improved problem solving techniques in related fields of computeralgorithms, software engineering, probability theory, and operations research.