Exogenous coordination in multi-scale systems: How information flows and timing affect system properties

Abstract

Abstract The architecture of coordination mechanisms is central to the performance and behaviour of (self-)integrated systems across natural, socio-technical and cyber–physical domains. Multi-scale coordination schemes are prevalent in large-scale systems with bounded performance requirements and limited resource constraints. However, theories to formalise how coordination can be implemented across multi-scale systems are often domain-specific, lacking generic, reusable principles. In these systems, feedback among system entities is a key component to coordination. Building on theories of hierarchies and complexity, in previous work we formalised Multi-Scale Abstraction Feedbacks (MSAF) as a design pattern to describe the architecture of feedback across system scales, highlighting the role played by micro-entities and macro-entities, as well as their interconnections. Focusing on exogenous coordination, this paper refines the MSAF pattern, describing a feedback cycle across scales as one where information flows bottom-up and top-down through five actions: state information communication, state information abstraction, information processing, control information communication, and adaptation from control information. Abstracted state information at each scale is processed with control input from the scale above and provides control input to the scale below. Using the example of distributed task allocation through exogenous coordination, NetLogo simulations are implemented to analyse the impact that different exogenous coordination strategies, and their internal timing configurations, have on resource consumption and on convergence performance. The experimental insights and refinement of the MSAF pattern contribute to a general theory of multi-scale feedback and adaptation. This architectural pattern and associated analysis and evaluation tools are still developing, but offer a concrete basis for further expansion, improvement, and implementation, while addressing questions that are at the core of the behaviour of multi-scale systems.