Difference between revisions of "Design Patterns for engineering SOS"
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* Control Theory -> Feedback | * Control Theory -> Feedback | ||
* Coupling between local interactions and global behaviour | * Coupling between local interactions and global behaviour | ||
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== Related Work on Design Patterns == | == Related Work on Design Patterns == |
Revision as of 11:40, 13 July 2010
Design Patterns for SOS?
- The idea of reuse existing, proven solutions seems to be interesting...
- Focus on mechanisms that cause systems to be SOS
- Use a pattern at design time, so that a SOS runtime behaviour shows up
- The usage of design patterns depends on the nature of the desired system
- Kategorize types of SOS and assign possible design patterns, which are useful for which type
- Checklist seems currently to be more appropriate, we know what is necessary to get SOS
- Checklist for basic properties of SOS: Adaptivity, Emergence, Autonomy, Decentralisation, Cognition, Feedback, Multiple intercations
- Runtime effects to show up: spatial temporal structures, multiple stability, parameter bifurcation
Design Patterns
- Achitectural patterns
- Observer-Controller Architecture (Organic Computing)
- MAPE (Monitor, Analyze, Process, Execute) Cycle (IBM Autonomic Computing)
- Patterns for (interaction) mechanisms
- Artificial Hormone System (moving/placing resources/load balancing)
- Ant foraging (reliably find shortest routes)
- Pulse-coupled oscillators
- Plain diffusion, replication, chemotaxis, and stigmergy, …
- Patterns of coordination
- Stigmergy
- Combine positive/negative Feedback w. Balance
- Control Theory -> Feedback
- Coupling between local interactions and global behaviour
Related Work on Design Patterns
In software engineering: a design pattern is a general reusable solution to a commonly occurring problem in software design. A design pattern is not a finished design that can be transformed directly into code. It is a description or template for how to solve a problem that can be used in many different situations [1]
- Design Patterns for Self-organising Systems, Gardelli et al.
- Design Patterns from Biology for Distributed Computing, Babaoglu et al.
- Design patterns for decentralised coordination in self-organising, De Wolf et al.