基于可编程分布式调度器的时间流体场协调
Time-Fluid Field-Based Coordination through Programmable Distributed Schedulers
AI总结：
本研究提出基于因果场和可编程分布式调度器的时间流体场协调方法，重新定义场计算中的时间调度，以平衡系统响应性与资源成本，并在场演算和聚合计算框架中实现与仿真验证。
摘要：
新兴应用场景，如信息物理系统（CPS）、物联网（IoT）和边缘计算，要求协调方法能够应对开放性、自适应性、异构性和部署无关性。场协调是其中一种方法，它提倡从全局视角以声明式方式编程系统协调，通过对称为场的分布式数据结构在“空间和时间”中的功能操作与演化来实现。更具体地关于时间，在场协调中（如同许多其他分布式协调方法一样），假设每个设备中的本地活动由平台层面运行的公平且非同步的固定时钟调节。在本工作中，我们挑战这一假设，并提出一种替代方法，其中调度以自然方式（与通常的场协调一起）通过因果场进行编程，每个因果场实施一种可编程的分布式计算“原因”概念（即场计算为何以及何时应在本地计算），以及它应如何随时间和空间变化。从低层平台触发器出发，此类因果场可组织成多个层次，直至高层、集体计算的时间抽象，供应用层使用。这种将时间重新解释为明确的因果关系的方式，使我们能够表达所谓的“时间流体”协调，其中调度可被精细调整以选择要响应的触发器，通常允许自适应地平衡计算的性能（系统响应性）和成本（资源使用）。我们在场演算的背景下形式化了所提出的场协调调度框架，讨论了在聚合计算框架中的实现，并最终通过多个案例研究的仿真评估了该方法。
英文摘要：
Emerging application scenarios, such as cyber-physical systems (CPSs), the Internet of Things (IoT), and edge computing, call for coordination approaches addressing openness, self-adaptation, heterogeneity, and deployment agnosticism. Field-based coordination is one such approach, promoting the idea of programming system coordination declaratively from a global perspective, in terms of functional manipulation and evolution in "space and time" of distributed data structures called fields. More specifically regarding time, in field-based coordination (as in many other distributed approaches to coordination) it is assumed that local activities in each device are regulated by a fair and unsynchronised fixed clock working at the platform level. In this work, we challenge this assumption, and propose an alternative approach where scheduling is programmed in a natural way (along with usual field-based coordination) in terms of causality fields, each enacting a programmable distributed notion of a computation "cause" (why and when a field computation has to be locally computed) and how it should change across time and space. Starting from low-level platform triggers, such causality fields can be organised into multiple layers, up to high-level, collectively-computed time abstractions, to be used at the application level. This reinterpretation of time in terms of articulated causality relations allows us to express what we call "time-fluid" coordination, where scheduling can be finely tuned so as to select the triggers to react to, generally allowing to adaptively balance performance (system reactivity) and cost (resource usage) of computations. We formalise the proposed scheduling framework for field-based coordination in the context of the field calculus, discuss an implementation in the aggregate computing framework, and finally evaluate the approach via simulation on several case studies.
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