In many self-organising systems the ability to extract necessary resources from the external environment is essential for growth and survival.In many self-organising systems the ability to extract necessary resources from the external environment is essential for growth and survival. E.g., extracting sunlight and nutrients in organic plants, monetary income in business organisations and mobile robots in intelligent swarms. When operating within competitive, changing environments, such systems must distribute their assets wisely, to improve and adapt their ability to extract available resources. As the system size increases, the asset-distribution process often gets organised around a multi-scale control topology. This topology may be static (fixed) or dynamic (enabling growth and structural adaptation) depending on the system's constraints and adaptive mechanisms. In this paper we expand on a plant-inspired asset-distribution model and study the impact that the topology of the multi-scale control process has upon the system's ability to self-adapt asset distribution when resource availability changes within the environment. Results show how different topological characteristics and different competition levels between system branches impact overall system profitability, adaptation delays and disturbances when environmental changes occur. These findings provide a basis for system designers to select the most suitable topology and configuration for their particular application and execution environment.
|Titel||3rd IEEE International Conference on Autonomic Computing and Self-Organizing Systems|
|Status||Udgivet - 2022|