一句话：提出用因果场编程分布式调度，替代固定时钟，实现可平衡反应性与开销的时间流体式场协调。
CPS、IoT 与边缘计算需要开放、自适应、异构且部署无关的协调。基于场的协调以 field 的时空演化声明式编程系统行为，但通常假设各设备由平台级公平且不同步的固定时钟驱动。本文挑战该假设，提出用 causality fields 将调度与场协调一并编程：因果场表达分布式计算“原因”，即为何与何时本地计算某 field 及其时空变化。因果场可从底层平台触发器组织为多层，直至应用级集体计算的时间抽象，形成“时间流体”协调，能细粒度选择响应触发器，自适应平衡系统反应性与资源开销。作者在 field calculus 中形式化该框架，在 aggregate computing 中实现并多案例仿真评估。
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.
@article{paperbot1262,
title = {Time-Fluid Field-Based Coordination through Programmable Distributed Schedulers},
author = {Danilo Pianini and Roberto Casadei and Mirko Viroli and Stefano Mariani and Franco Zambonelli},
journal = {Logical Methods in Computer Science},
volume = {Volume 17, Issue 4},
year = {2021},
doi = {10.46298/lmcs-17(4:13)2021}
}