Difference between revisions of "Group 2"
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** The state of other self-organizing systems cannot be modeled, they exhibit chaotic behavior, which makes it impossible to predict future states. | ** The state of other self-organizing systems cannot be modeled, they exhibit chaotic behavior, which makes it impossible to predict future states. | ||
| − | * '''Robustness issues'' | + | * '''Robustness issues''' |
** Malicious nodes, faults, defects | ** Malicious nodes, faults, defects | ||
Revision as of 11:24, 12 July 2010
Contents
Group members
- Christian Bettstetter
- Hermann de Meer
- Johannes Klinglmayr
- Martina Umlauft
Challenges
- Design of emergence:
- How to design local rules achieving the desired global properties?
- Non-trivial but approaches exist.
- Design of the communication / interaction protocol:
- Degrees of freedom and adaptability
- Simple versus chaotic behavior: Can we describe the system state?
- The state of some self-organizing systems can be easily modeled (firefly sync)
- The state of other self-organizing systems cannot be modeled, they exhibit chaotic behavior, which makes it impossible to predict future states.
- Robustness issues
- Malicious nodes, faults, defects
- Testing:
- It can be very difficult to test a proposed self-organizing system with respect to a given goal (many entities, large operational range, chaotic behavior)
- Rare events may lead to major global effects.
- Repeatability of results
- User aspects
- To what extend can today’s systems be replaced or complemented by self-organizing systems, taking into account
- constraints and acceptance of the technology and
- risks for users?
- To what extend can today’s systems be replaced or complemented by self-organizing systems, taking into account
Ideas
- "Immune system" as an umbrella around self-organizing system
- Optimize probability to end up in desired state
Side note
- Heylighen: "interaction pattern are not specified"
