This document discusses analyses and models of societal resilience. It identifies problems with current social organizations, such as a strict classification between active and passive members of society. This can lead to fragility as populations age. It proposes a potential solution of fractal social organization (FSO) based on self-similar service-oriented communities that cooperate across scales. Simulations show FSO outperforms traditional and perfect oracle organizations on measures like average waiting times and number of patients treated when facing crises requiring dynamic resource orchestration. FSO allows utilization of society's full potential through dynamic cooperation rather than static classification.

1. How Resilient Are Our Societies?
Analyses, Models, Preliminary Results
Vincenzo De Florio and Arianit Pajaziti
MOSAIC/Universiteit Antwerpen & MOSAIC/iMinds
vincenzo.deflorio@uantwerpen.be
UNIVERSITY OF ANTWERP
MOSAIC Research Group

2. • "We are greatly frustrated
by all our local, static organization
of an obsolete yesterday."
Richard Buckminster Fuller,
Synergetics I

3. The problem
• Regardless of its nature, any system is
affected by its design assumptions.
Our societies are no exception.
• Our societies: complex collective systems with
(often too) simple organization
– Healthcare, crisis management, [civil] defense
– Enterprises too

4. Major problems
→ Strict classification: active and passive
side of society
• A subset of the social actors serves
the whole set
• Growing population +
progressive aging⇒ shrinking
of the service providers subset
→ Fragile society unable to serve
its citizens

5. Major problems
→ Strict classification: active and passive
side of society
• A subset of the social actors serves
the whole set
• Growing population +
progressive aging⇒ shrinking
of the service providers subset
→ Fragile society unable to serve
its citizens

6. Major problems
→Absence of a referral service.
• User responsibility to identify the
service providers
(which emergency service to invoke,
which civil organization to refer to,
which hospital to call first …)
→ Incomplete view of the current state of the system
and availability of its resources

7. Major problems
→Lack of unitary responses to
complex requests
●No composite responses
to complex requests,
no automatic orchestration of
action, knowledge, and assets.

8. What can we conclude?
• Current social organizations: ineffective and fragile
• Challenge: being able to mutate our organizational
paradigms and assumptions
– Move from
“a local, static organization of an obsolete yesterday”
to
distributed, dynamic organization
of our turbulent nowadays
• New ingredients: organizational approaches that enable the
utilization of the full potential of our societies.

9. Requirements and a potential solution
• Organizations should not stigmatize actors
and should promote the participation of all
actors
• Organizations should stimulate the
cooperation among the role players
at all levels, from the citizens to the
governing institutions
• Potential solution:
Fractal Social Organization

10. Fractal Social Organization
• A building block repeated at different scales
• Each building block is called service oriented community
(SoC)

11. Reasoning & coordination
11
Member Member
Member w/
service & feature registry
Service
& feature
The SoC building block
Publish Publish
Bind
Individual &
social concerns
optimization.
Capabilities
Policies
Availability
Location…
Events
People
Devices

12. Example: Mutual Assistance Community
(single building block)
ABC Shop
Smart
devices
Informal service
provider
Commercial vender
Doctor
Community
Access
A smart house
Coordination
center
(professional)
OSGI
Gateway
Create
OWL-S
OWL-S service
publication
Service
Request
OWL-S service
publication
OWL-S service
publication
OWL-S
Matcher
OSGI
bundle
OSGI
bundle
OSGI
bundle
More info: [DeB10]

13. 13
Member Member
Service
description
FSO = fractal organization of SoC’s
Publish Publish
Bind
Local
Reasoning & coordination
Individual &
social concerns
optimization
Capabilities
Policies
Availability
Location…
Events
People
Devices MemberMember MemberMember
Exception ⇒ Event propagation
Member w/
service & feature registry
SoC’s

16. Social
Overlay
Network

17. Simulations
• iMinds project "Little Sister" http://goo.gl/PBXEgX
– Little Sister FSO: (very) limited implementation, not tested
in real life situations
• Simulations: inexpensive way to test / assess the
model
– Of course the model, not the system…
• In what follows, simulated FSO’s
– NETLogo multi agent simulation environment

18. Simulated FSO
• tba

19. First simulation

20. First simulation

21. The "rules of the game"
–Doctors, people, ambulances, medical appliances
–People become ill with probability p
–Illness: 10 classes of increasing severity: [1]...[10]
–[1]..[3] do not require ambulances
–All doctors can treat [1]..[3] and three other diseases.
–For patient’s treatment, medical appliances are needed.
For severe cases, a combination of several medical
appliances is required.
–Healthcare request should be handled within a given
threshold, otherwise the patient’s condition degrades,
resulting in death.

22. –Traditional organization
1.Limited knowledge of the other hospital’s resources and
specialties
2.Sequential “polling” of hospitals
3.No resource sharing
–Perfect Oracle
1.Perfect knowledge regarding the hospitals and services offered
2.No resource sharing
–FSO
1.Increasing knowledge acquired while climbing the hierarchy
2.Combination of roles from distinct SoCs for answering the
situation at hand (= social overlay networks)
Terms of comparison

23. • Average Querying time: average time an individual in
need of care has to wait until s/he receives the
necessary treatment.
• Number of treated patients.
• Number of patients that could not receive the treatment
within the defined threshold, and thus die.
• SON (social overlay network): number of times a solution
to the given situation is solved as a result of
inter-community cooperation (FSO only).
Measured figures

24. Average querying times for various threshold values
Evaluations
a) Threshold 150.
b) Threshold 200. c) Threshold 250.
• Waiting time & number
of treated patients
• Threshold: 150 ticks
• TO highest times,
then PO
• Least waiting times:
FSO
• No. of patients:
FSO > PO > TO

25. Average querying times for various threshold values
Evaluations
a) Threshold 150. b) Threshold 200.
c) Threshold 250.treated
• Waiting time &
treated patient
number
• Population: 60--140
• Threshold: 250 ticks
• TO: highest times,
then PO;
FSO: least waiting times.
• # treated patients:
FSO > PO > TO
60
60
60
140
140
140
TO
PO
FSO

26. Evaluations (2)
• Waiting time > threshold
• Population: 60--140
• Threshold: 150 ticks
• TO: highest times,
then PO
• FSO: least waiting times

27. Evaluations (3)
• Waiting time > threshold
• Threshold: 250 ticks
• Same results:
TO: highest times,
then PO;
FSO: least waiting
times

28. Social overlay networks
• SON = number of
times the FSO
algorithms create
a "response team"
from two or more
SoC's

29. Conclusions
• FSO: an answer to the "challenge to mutate our
organizational paradigms and assumptions"
• No stigmatization: all participants are active
– Utilization of the full potential of our societies
• Dynamic orchestration of resources is possible
– Responsibility to the "server side"!
• Our recipe to move from “a local, static organization of an
obsolete yesterday” to distributed, dynamic organization of
our turbulent nowadays
• Challenge: mutate while preserving the identity

30. Thank you very much!
vincenzo.deflorio@gmail.com