Preliminary Contributions
Towards Auto-Resilience
Vincenzo De Florio, PATS research group

http://win.uantwerpen.be/~vince...
What is it all about?
• A number of questions; some reflections;
some ideas and conjectures
• Questions:
• What is resilie...
Q1: What is resilience?
• Resilience = ability to retain one’s identity
• From Aristotle’s concept of entelechy
• Being-at...
Q2: What makes an essence resilient?
• Several different abilities co-existing within a
same essence
• Optimal co-existenc...
Resilience prerequisites: perception
• Ability to timely register the state of some
portion of the context
• Sub-divided i...
Perception :: sensors
• Primary interface with physical world
• Reflect a subset of the world’s “raw facts”
• Problems:
• ...
Perception :: quale
•
•
•
•

C = computer world, U = physical world
C-representations of U raw facts
A morphism qualia : U...
Perception :: memory
• Quale persistence layer
• Storage and retrieval of quale
• «Apri la mente a quel ch'io ti paleso
e ...
Powers of representation
• A measure of the quality of perception
[Leibniz]
• A metric to compare the perception of
essenc...
Powers of representation
• Note: PoR are dynamic systems
• PoR: metrics to compare essences and
ambients
• E.g. say a is d...
Powers of representation
• Predicate amb(x) = “x is an ambient”
• Predicate esn(x) = “x is an essence”
PoR(b)
PoR(a)

4 Oc...
Powers of representation

PoR(b)

• esn(a) ᴧ amb(b) 
• a perceives a subset of
b’s context : some changes
in b won’t be p...
Apperception
• Apperception defines how the reflected quale
are accrued, correlated with past perception,
and used to crea...
Apperception
• Behaviour may be used to rank an essence’s
apperception [re: Rosenblueth; Boulding]
• Apperception is a tra...
Entelechism
• The quality and characteristics of the
mechanisms responsible for planning and
controlling the robust emerge...
Entelechism :: Meta-apperception
• Apperception of an essence’s Planning
essence
• Say a is an essence and a.p is its plan...
Entelechism :: Multiplicity and
organisation of Planners
• Second important factor towards resilience:
• presence of a sin...
Entelechism :: Multiplicity of
Planners
• Individual vs social context: choices are made
in isolation or otherwise
• E.g. ...
Entelechism :: Organisation of
Planners
• The way collective resilient planning
is carried out
• Centralised, hierarchical...
Q3: How can we use resilience
classes to design resilient essences?
• Conjecture:
- decomposing resilience into sub-proper...
Example: resilience handshake
• An admission control mechanism constraining
the deployment of an essence in a target
ambie...
Example: resilience handshake
• Classic scenario: miner and canary
• Two very different essences each
characterized by pec...
Example: resilience handshake
• Classic solution: the miner brings along a
canary
• Now PoR(miner+canary) > PoR(miner)
• “...
Conclusions
• Nature made us, nature shows us the way
• Symbiosis, mutualistic relationships, biological
collaborative int...
Conclusions
• Computer systems have a double option:
1. They can evolve themselves towards
resilience – much faster than p...
Conclusions
• Future work: try and define design principles
for auto-resilience
• Dynamic composition of essences and
plan...
Thank you very much
for your attention
vincenzo.deflorio@uantwerpen.be
4 October 2013

SERENE 2013
References
•

Sachs, J.: Aristotle’s Physics: A Guided Study. Rutgers (1995)

•

Nilsson, T.: How neural branching solved ...
29 August 2011
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'Preliminary Contributions towards Auto-resilience' is a presentation for the SERENE 2013 workshop. An abstract follows:
The variability in the conditions of deployment environments introduces new challenges for the resilience of our computer systems. As a response to said challenges, novel approaches must be devised so
that identity robustness be guaranteed autonomously and with minimal overhead. This presentation (and accompanying paper) provide the elements of one such approach. First, building on top of previous results, we formulate a metric framework to compare specific aspects of the resilience of systems and environments. Such framework is then put to use by sketching the elements of a hand-shake mechanism between systems declaring their resilience figures and environments stating their minimal resilience requirements. Despite its simple formulation it is shown how said mechanism enables scenarios in which resilience can be autonomously enhanced, e.g., through forms of social collaboration. This paves the way to future “auto-resilient” systems, namely systems able to reason and revise their own architectures
and organisations so as to optimally guarantee identity persistence."
For discussing about this and other papers, follow me on twitter https://twitter.com/EnzoDeFlorio

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Serene'13

  1. 1. Preliminary Contributions Towards Auto-Resilience Vincenzo De Florio, PATS research group http://win.uantwerpen.be/~vincenz/
  2. 2. What is it all about? • A number of questions; some reflections; some ideas and conjectures • Questions: • What is resilience? • What makes an individual or collective essence resilient? • How can we use this knowledge to design resilient essences? • Autonomic management of resilience 4 October 2013 SERENE 2013
  3. 3. Q1: What is resilience? • Resilience = ability to retain one’s identity • From Aristotle’s concept of entelechy • Being-at-work staying-the-same [Sachs] • Being-at-work: adapt to changing circumstances • Staying-the-same: without compromising one’s “definition” – one’s essence 4 October 2013 SERENE 2013
  4. 4. Q2: What makes an essence resilient? • Several different abilities co-existing within a same essence • Optimal co-existence = tough design problem! • Design trade-offs are necessary due to physical or practical limitations • Many examples in nature [Nilsson] • Three major abilities: perception, apperception, entelechy 4 October 2013 SERENE 2013
  5. 5. Resilience prerequisites: perception • Ability to timely register the state of some portion of the context • Sub-divided into three layers: sensors, quale, memory 4 October 2013 SERENE 2013
  6. 6. Perception :: sensors • Primary interface with physical world • Reflect a subset of the world’s “raw facts” • Problems: • Proper subset (incomplete view) • « Facile credo plures esse Naturas invisibiles quam visibiles in rerum universitate. Sed horum omnium familiam quis nobis enarrabit ? Et gradus et cognationes et discrimina et singulorum munera?» T. Burnet • Imperfect reflection • External dependences (resource depletion…) • Aging 4 October 2013 SERENE 2013
  7. 7. Perception :: quale • • • • C = computer world, U = physical world C-representations of U raw facts A morphism qualia : U  C Important aspects w.r.t. resilience: • Qualia manifestation latency • Time b/w U event e occurs and qualia(e) appears in C • Reflective throughput • Amount of raw facts that may be reliably encoded as quale per time unit 4 October 2013 SERENE 2013
  8. 8. Perception :: memory • Quale persistence layer • Storage and retrieval of quale • «Apri la mente a quel ch'io ti paleso e fermalvi entro; ché non fa scïenza, sanza lo ritenere, avere inteso» (Dante, Paradiso, V, 40-42) • Important aspects w.r.t. resilience: • Qualia access time • How quickly the “control layer” may access stored quale 4 October 2013 SERENE 2013
  9. 9. Powers of representation • A measure of the quality of perception [Leibniz] • A metric to compare the perception of essences PoR(b) PoR(a) PoR(∞) 4 October 2013 • PoR(a) < PoR(∞) • PoR(b) < PoR(∞) • PoR(a) ≠ PoR(b) SERENE 2013
  10. 10. Powers of representation • Note: PoR are dynamic systems • PoR: metrics to compare essences and ambients • E.g. say a is deployed in b • Picture says: • a perceives only a PoR(b) PoR(a) subset of b’s context • a perceives changes that won’t occur in b 4 October 2013 SERENE 2013
  11. 11. Powers of representation • Predicate amb(x) = “x is an ambient” • Predicate esn(x) = “x is an essence” PoR(b) PoR(a) 4 October 2013 • esn(a) ᴧ esn(b)  PoR(a) < PoR(b) • amb(a) ᴧ esn(b)  • b perceives all of a’s context • b is designed to perceive changes that won’t occur in a SERENE 2013
  12. 12. Powers of representation PoR(b) • esn(a) ᴧ amb(b)  • a perceives a subset of b’s context : some changes in b won’t be perceived by a PoR(a) 4 October 2013 SERENE 2013
  13. 13. Apperception • Apperception defines how the reflected quale are accrued, correlated with past perception, and used to create dynamic models of the “self” and of the “world” (deployment ambient) • “The most merciful thing in the world, I think, is the inability of the human mind to correlate all its contents” [H.P.Lovecraft, Call of Cthulhu] 4 October 2013 SERENE 2013
  14. 14. Apperception • Behaviour may be used to rank an essence’s apperception [re: Rosenblueth; Boulding] • Apperception is a trait characterising • Teleological behaviour essences • 0-order predictive behaviour essences • N-order predictive behaviour essences • The above order may be used to define an apperception metric to compare essences with one another (in what follows: ord(e)) 4 October 2013 SERENE 2013
  15. 15. Entelechism • The quality and characteristics of the mechanisms responsible for planning and controlling the robust emergence of resilience • In a resilient MAPE-K loop essence, the Planner • Planner is an essence in itself; thus its apperception may be ranked 4 October 2013 SERENE 2013
  16. 16. Entelechism :: Meta-apperception • Apperception of an essence’s Planning essence • Say a is an essence and a.p is its planning essence; in general ord(a) ≠ ord(a.p) • E.g. a may be 1-order predictive while a.p may be 0-order (teleological) [De Florio, ‘13] 4 October 2013 SERENE 2013
  17. 17. Entelechism :: Multiplicity and organisation of Planners • Second important factor towards resilience: • presence of a single or multiple concurrent Planners • Latter case: - individual vs. social nature of the interactions between Planners - organisation of control among the Planners 4 October 2013 SERENE 2013
  18. 18. Entelechism :: Multiplicity of Planners • Individual vs social context: choices are made in isolation or otherwise • E.g. Bacillus subtilis • when subjected to a stressful environment B.subtilis use quorum sensing and choose between cooperative and selfish strategies depending on an estimation of the choices made by fellows 4 October 2013 SERENE 2013
  19. 19. Entelechism :: Organisation of Planners • The way collective resilient planning is carried out • Centralised, hierarchical, heterarchical, distributed organisation, … • Latter case: bionic organisations, holarchies, and fractal organisations • a hierarchical composition of autonomous planners 4 October 2013 SERENE 2013
  20. 20. Q3: How can we use resilience classes to design resilient essences? • Conjecture: - decomposing resilience into sub-properties; - classifying essences and ambients accordingly; makes it easier: • to reason about essence-ambient fits; • to resiliently self-adapt an essence w.r.t. a reference ambient  Auto-resilience 4 October 2013 SERENE 2013
  21. 21. Example: resilience handshake • An admission control mechanism constraining the deployment of an essence in a target ambient • Aim: Allowing an essence’s resilience figures to be matched with the expected minimal resilience requirements of a deployment ambient • “Resilience contract” to be matched with an “environment policy” 4 October 2013 SERENE 2013
  22. 22. Example: resilience handshake • Classic scenario: miner and canary • Two very different essences each characterized by peculiar resilience figures • At first sight, miner is a superior essence • Extended perception, apperception, entelechism • But miner is deployed in an unfavourable ambient (mine) • PoR(Miner) < PoR(Mine) • carbon monoxide, carbon dioxide, methane… 4 October 2013 SERENE 2013
  23. 23. Example: resilience handshake • Classic solution: the miner brings along a canary • Now PoR(miner+canary) > PoR(miner) • “+” here implies constant monitoring • If perception of toxic gases is here, Miner+canary will be able to react 4 October 2013 PoR(Mine) PoR(M+c) PoR(M) SERENE 2013
  24. 24. Conclusions • Nature made us, nature shows us the way • Symbiosis, mutualistic relationships, biological collaborative interactions are nature’s way to augment our individual features • Only through this we can match changing environments before the changes make us extinct 4 October 2013 SERENE 2013
  25. 25. Conclusions • Computer systems have a double option: 1. They can evolve themselves towards resilience – much faster than physical essences 2. They can use mutualistic approaches to give raise to complex collective resilient systems • Auto-resilience = ability to manage autonomously the complex trade-offs necessary to manage 1. and 2. 4 October 2013 SERENE 2013
  26. 26. Conclusions • Future work: try and define design principles for auto-resilience • Dynamic composition of essences and planners via Transformer [GD12] • Collective resilience strategies via Fractal Social Organizations and their social overlay networks [DF12, DF13a, DF13b] 4 October 2013 SERENE 2013
  27. 27. Thank you very much for your attention vincenzo.deflorio@uantwerpen.be 4 October 2013 SERENE 2013
  28. 28. References • Sachs, J.: Aristotle’s Physics: A Guided Study. Rutgers (1995) • Nilsson, T.: How neural branching solved an information bottleneck opening the way to smart life. In: Proc. of the 10th Int.l Conf. on Cognitive and Neural Systems, Boston Univ., MA (2008) • Strickland, L.H.: The shorter Leibniz texts: a collection of new translations • Rosenblueth, A., Wiener, N., Bigelow, J.: Behavior, purpose and teleology. Philosophy of Science 10(1) (1943) 18–24 • Boulding, K.: General systems theory—the skeleton of science. Management Science 2(3) (1956) • De Florio, V.: On the constituent attributes of software and organizational resilience. Interdisciplinary Science Reviews 38(2) (2013) [DF13a] • De Florio, V. et al.: Models and Concepts for Socio-technical Complex Systems: Towards Fractal Social Organizations, to appear in Systems Research and Behavioral Science (2012) [DF12] • De Florio, V.: Fractal Social Organizations on YouTube [DF13b] 4 October 2013 SERENE 2013
  29. 29. 29 August 2011

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