CSR: Small: Collaborative Research: Multi-tier Service Architecture in IoT-Edge-Cloud-Paradigms

边缘计算是一种新兴的范式，在这种范式中，计算和存储被放置在端点物联网（IoT）设备和云之间的多个位置。这被视为物联网解决方案下一波进步背后的驱动力。边缘服务预计将成为下一个数十亿美元的技术市场，并颠覆当前基于云计算的行业。边缘计算的全行业开发和标准化工作正在积极进行，以定义相关架构。在此背景下，本项目设计并实现了一个系统架构，以优化跨物联网设备、边缘服务器和云的多层服务编排。与典型的每个应用程序优化方法不同，这个项目对多个应用程序的联合并发优化采取了独特的观点。这种架构鼓励开发新的分布式算法来分解物联网应用程序的处理语义。此外，该项目还为行业标准化工作提供了技术和参考模型。利用边缘功能来改变物联网服务格局需要新颖的分布式算法和系统架构。这远远超出了为单个应用程序划分应用程序代码和卸载计算的现有方法。为此，该项目旨在构建一个系统运行时，该系统运行时在自动化优化应用程序处理的同时抽象掉基础设施的复杂性。在计算路径上，该项目强调了新的相关计算类型，其中相应的输入和输出相似但不相同。消除这一点是同时优化计算延迟和结果质量的关键。进一步开发的技术为重构这些应用程序的处理管道提供了原语。在控制路径上，项目在单个客户机-服务器层中抛弃了现有的以服务器为中心的控制，而是在嵌套的服务器模型中提出以客户为中心的控制，以利用多层计算能力。最后，将上述技术集成到系统运行时中，从而进一步提供简单的api（应用程序编程接口）和诸如调度之类的通用系统级支持。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Edge computing is an emerging paradigm in which computing and storage are placed at multiple locations between the endpoint Internet of Things (IoT) devices and the cloud. This is seen as a driving force behind the next wave of advances in IoT solutions. Edge services are predicted to become the next multi-billion dollar technology market and disrupt the current cloud computing based industry. Active industry-wide development and standardization efforts for edge computing are under way to define related architectures. Against this backdrop, this project designs and implements a system architecture to optimize multi-tier service orchestration across IoT devices, edge servers, and the cloud. In contrast to the typical per-application optimization approach, this project takes a unique view of joint, concurrent optimization of multiple applications. This architecture encourages the development of new distributed algorithms for decomposing the processing semantics of IoT applications. Further, the project contributes techniques and reference models to industry standardization efforts.Harnessing edge capabilities to transform the IoT service landscape requires novel distributed algorithms and system architectures. This goes far beyond existing approaches for application code partitioning and computation offloading for individual applications. To that end, this project aims to build a system runtime that abstracts away the infrastructure complexity while automating the optimization of application processing. On the compute path, the project highlights new types of correlated computation, where the corresponding input and output are similar but not identical. Eliminating this holds the key to simultaneously optimizing for the computation latency and results quality. The techniques developed further provide primitives to restructure the processing pipelines of these applications. On the control path, the project departs from the existing server-centric control in a single client-server tier, and instead proposes client-centric control in a nested server model to leverage multiple tiers of computing capabilities. Finally, the above techniques are integrated into a system runtime, which further provides simple APIs (application programming interface) and generic system level support such as scheduling.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.