Space-Fluid and Time-Fluid Programming

This chapter addresses coordination challenges in emerging application scenarios, such as cyber-physical systems (CPSs), the Internet of Things (IoT), and edge computing, through a Fluidware-based approach to field-based coordination, showing how data structures distributed in space and time (fields) can be extended towards fluidity. In time, we challenge the traditional assumption of fixed clocks regulating local activities and propose “causality fields” for scheduling in coordination with field-based methods. This innovative approach enables “time-fluid” coordination, balancing system reactivity and resource usage. We formalise the scheduling framework in the field calculus, provide a reference implementation, and assess its effectiveness through simulations across diverse case studies. In space, we explore managing spatially varying signals in coordinated systems, employing decentralised and situated computing for collaborative adaptive sampling. Our algorithm dynamically partitions space into regions that adapt, creating a “fluid” virtualised space responsive to pressure from the underlying phenomenon under observation. Proven self-stabilising and locally optimal, our adaptive sampling algorithm enables spatially adaptive computations with a tuneable trade-off between accuracy and efficiency.