CNS Core: Small: New Caching Paradigms for Distributed and Dynamic Networks

在过去的几十年中，内容分发网络(CDN)被用于缓存离终端用户更近的流行兴趣的数据，以便在请求时快速访问这些数据。从终端用户的角度来看，这在检索流行内容(如视频提要)时节省了大量时间。它还有助于降低对整个网络的带宽需求。这是通过开发使用基于流行度的指示符来存储内容或从高速缓冲存储器中取出内容的高效机制来实现的。然而，随着物联网(IoT)和网络物理系统等新兴技术的出现，网络的动态和需求正在发生重大变化，需要全新的缓存解决方案，这些解决方案将超越CDN的范围，扩展到无线边缘和最终用户设备。这些新网络将由大量高度移动的设备(例如移动电话)组成，这些设备具有间歇性、延迟敏感型和个性化需求，需要通过资源有限的无线信道来支持。为了应对这些新的挑战，该项目承担了缓存民主化的任务，提出了一种系统的方法，在为日益动态和不同的网络设计可证明良好的缓存策略时，将无线边缘和最终用户包括在内。该项目的动机是观察到，网络终端内和终端上的缓存必须从根本上不同于彼此，以及不同于为当今CDN优化的现有缓存策略。特别是，该项目确定并系统地研究了必须根据内存空间的位置及其接收到的需求的性质采用不同缓存原则的补充方案。在每个场景中，该项目都采用整体设计方法，以纳入发电和需求动态、无线通信能力和限制、流量和环境中的各种不确定性以及服务质量要求。这项研究是多学科的，将汇集排队、调度、异常检测、编码、学习和控制理论的元素，以设计集成的和自适应的缓存解决方案。这种跨学科研究将被纳入课程，并将帮助培训下一代工程师和院士，使他们掌握成功解决日益复杂和具有挑战性的问题所需的工具。调查人员致力于在他们的研究中招募女性和代表性不足的少数族裔学生。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Over the last few decades, Content Distribution Networks (CDNs) have been used to cache data of popular interest closer to the end-users in order to make them rapidly accessible whenever requested. This results in substantial time savings from an end-user’s perspective when retrieving popular content like video feeds. It also helps to reduce the bandwidth demands on the overall network. This is achieved by developing efficient mechanisms that employ popularity-based indicators to store or evict content from the cache memory. However, with the advent of emerging technologies such as the Internet-of-Things (IoT) and cyberphysical systems, the dynamics and requirements of networks are witnessing significant changes that call for fundamentally new caching solutions that extend beyond the purview of CDNs to the wireless edge and the end-user devices. These new networks will be composed of a large number of highly mobile devices (e.g., mobile phones) with intermittent, delay-sensitive, and personalized demand to be supported over resource-limited wireless channels. To address these new challenges, this project undertakes the task of democratizing caching by proposing a systematic methodology that encompasses the wireless edge and the end-users in the design of provably good caching strategies for increasingly dynamic and disparate networks. This project is motivated by the observation that caching within and at the endpoints of networks must differ fundamentally from each other, as well as from existing caching strategies optimized for today's CDNs. In particular, the project identifies and systematically investigates complementary scenarios that must employ different caching principles based on the position of the memory space and the nature of demand it receives. In each scenario, the project takes a holistic approach to the design to incorporate generation and demand dynamics, wireless communication capabilities and limitations, variety of uncertainties in the traffic and environment, and quality-of-service requirements. This research is multi-disciplinary and will bring together elements from queueing, scheduling, anomaly detection, coding, learning and control theories towards the design of integrated and adaptive caching solutions. This interdisciplinary research will be integrated into the curricula and will help train the next generation of engineers and academicians with the tools it takes to succeed in solving increasingly complex and challenging problems. The investigators are committed to recruit women and under-represented minority students in their research.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.