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   Stable Cooperating Systems (WAS RE: XML for Online Games)

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  • From: "Bullard, Claude L (Len)" <clbullar@ingr.com>
  • To: Joshua Allen <joshuaa@microsoft.com>, Sam Hunting <sam_hunting@yahoo.com>,xml-dev@lists.xml.org
  • Date: Wed, 01 Nov 2000 10:15:44 -0600

<warning>Going long.</warning>

Right.  Thank you, Joshua. I'll take a look at the URL.  
Meanwhile, here are some aging thoughts on trust and 
the maintenance of stable cooperating systems.


Encapsulation of view means that updates are 
only occuring in the locale of interest.  There are 
several techniques for achieving this well-described 
in the virtual reality literature.  Proximate or 
scoped addressing is part of that, there is a lot 
of literature on clustering, applying imaginary 
numbers, etc.  One can go pretty far over the edge 
with this one, but the essential is the view dimension 
as described in complex systems theory that enables 
level of detail based on distance to viewed object.
A wrapped string is a point until viewed closely, 
a ball then, and closer than that, a wrapped cylinder, 
and so forth.  Map paths have the same characteristics 
, eg interstates down to local roads, to finite addresses, 
so what we are describing is granularity of address 
resolution and why in Hytime, they expended so much 
effort on identifying address types independent of 
system and the concept of location ladders which 
can chain these.  All of these come under resolution. 
People spent a lot of time looking at fractals but 
really, fractals are a kind of illusion, a path 
produced by feedback looping and thumping a control. 
Fractal dimensions and view dimensions are the same, 
but note that in process design, it is just a GUI.

As to trust, this issue has been debated again and 
again over the years as former F2F processes became 
automated and distributed.  HTML scared the hell out
of some of us not because it was bad, but because 
as a primitive tag stacker, the essentials of validation 
were left behind and knowing that it was gencoding, 
the first stage of markup system evolution, there 
was the terrifying sense of abandoning hard learned 
lessons with regards to "trust but validate".  I considered 
it a bad precedent: colonization at the cost of the 
health of the information being encoded.   Then 
came the XMLIsOnlyWellFormed nonsense, and the panic 
became palpable.  Finding out that what was really 
in the works was replacing DTDs with instance syntax 
was a kind of relief but also a warning to take any 
signals from the W3C about futures with more than 
a grain of salt.  That is why we are shaking out 
the Semantic Web concepts like a dog with a sock in 
his teeth.   The XML development process tore apart 
the fabric of trust in some parts of the community 
and we have been a while getting that back. 
Creating XML was necessary but we would be remiss 
if we did not look at the process and ask if we 
can do better.  I think the results of lessons learned 
are in Jon Bosak's exemplary process design for OASIS.

It comes down to process, testing process, scoping 
control, and predictable behavior.  In Beyond The 
Book Metaphor, I took up the issues of trust, cooperation, 
and system-destabilization in some detail.  It is 
obvious that distributed systems and destabilization 
are issues we have to pay attention to given the nature 
of the web as an amplifier, and therefore, the 
nasty potentials of cascades due to feedback.  SGMLers 
recognized the problems of semantics long ago, experimented with 
the semantic nets and came back to document flow as 
the best level for coordinating distributed processes 
particularly, the human levels.  Policy, protocol, 
and precise definitions of the documents plus a discipline 
with respect to the execution of process enables 
humans to identify emerging discontinuities.  It builds 
a kind of intuition into the practice very similar 
to the damping of chaotic systems (operate close 
to the edge where the processes are hot, and lightly 
thump the control to prevent systems from settling 
into local non-optimum minima - see annealing).

There is no magic mantra for trust.  The best systems 
use tit-for-tat strategies.  This strategy is simple 
and tends over time to converge on optimum solutions.  

System destabilization is not a complex notion.  Humans always 
must be enabled to "pull the plug" in response to 
unknown-unknowns which trigger actions with potentially  
catastrophic results (See NORAD - 1960 Thule incident and 
October 19 1987 stock crash).  

Still, while we are here, let's talk about your hacker 
problems as a destabilization issue.  The goal of destabilization 
is to exhaust the energy budget of a system and deprive it 
of the capacity to meet mission goals.  One can say a 
destabilized system exhibits a "higher temperature", thus, 
an increase in energy expenditure without a resultant 
increase in organization, until it reaches entropy.  Direct 
attack is one means (eg, a worm), but more subtle approaches 
are possible.  Some working definitions:

o  Instability - the sensitivity of a system element to 
   variance.  The number of sensitive elements and the degree 
   of sensitivity determine the overall system vulnerability.

o  Destabilization - the process of increasing the entropic 
   value of a system by introducing false referents or relationships 
   that increase the latency of the messaging system beyond the 
   tolerance thresholds of the protocol.

A successful destabilization strategy disrupts the synergy of 
system and organization.  The more interdependent the system, 
typically, the easier it is to destabilize.  To make the 
system less vulnerable, it needs to be noise-tolerant and 
we all understand the most common techiques using redundant 
data storage, matching and verification, and encapsulation 
of components or view dimensionality to restrict propagation. 
It is necessary to be able to discriminate natural activity 
that results in decay (incompetence in functions, superstitious 
learning, etc) from an active destabilizing agent (goal seeking).
Note your own problems with detecting account 
creation and discrimination based on seeking higher levels 
of privilege.  The obvious pattern was goal seeking.

Destabilization in a system can be increased by decreasing 
the referential value of a pointer.  This 
activity seeks to increase uncertainty and decrease confidence 
or goodness in a value.  These might be called Boltzman Attacks 
based on application of the Boltzman entropy equation:

o  Uncertainty - increase the number of imprecise terms or referents 
   that result in unresolved ambiguities.  Superstitious learning is a 
   good example. (aka, FUD).

o  Exhaustion - increase the number of referents precise or otherwise 
   beyond the capacity of the system to resolve them within the budget 
   (eg time, money, any other finite resource).  Vaporware is a good 
   example as it disrupts timing. 

Disrupting timing is an excellent strategy. See Miyamoto Musashi - 
The Book of Five Rings - "You win in battle by knowing the enemy's timing, 
and thus using a timing which the enemy does not expect."  He 
goes on to describe foreground and background timing and the need 
to see both in relationship to each other.  Musicians understand 
this as syncopation and the effects of it on autonomic systems.

Some factors that affect destabilization are:

o position of destabilizing agent in hierarchy of control, that is, 
  the interdimensional effectiveness for propagating by force

o Length of time of effective destabilization, how long is the 
  error undetected and therefore, the density of the error 
  (eg, replication)

Destabilization can propagage linearly, by value, or non-linearly 
by reference.

To destabilize:  

o  Identify a mission critical component and its importance in 
   the event stream

o Introduce the destabilizing agent with sufficient resources 
  to execute a change needed to redefine a component or critical 
  element of a component.  Reclassification is an excellent 
  strategy here.  AKA, labeling.  This is why authority is so 
  problematic when creating semantic nets.  Note carefully, 
  the principle of rationality is weak for organizing human 
  systems (see Prisoner's Dilemma).  No system can be predicated 
  on self-sacrifice that leads to extinction.  Trust in an organizaton  
  is in direct proportion to the relationship to self-preservation.  
  If it helps, it is supported.  If it extinguishes, it is attacked.

o Redirect resources so that stabilizing controls are decreased, 
  eg, distraction.  For example, a change of focus can be used 
  to mask destabilizing activities.  When the hacker better understands 
  your resources and how you apply them, he can create other activities 
  to deny visibility of his real mission.  Coordinated attacks are 
  hard to defend against if such knowledge is available.

o Protect the agent until the energy budget collapses such that 
  effective mission closure cannot be achieved by redirection.  
  Deny the capacity to remediate.

The notion of focus involves temporal elements of concurrency. 
What can be known, when and with what degree of certainty grows 
or diminishes in relation to the available referents and the 
capacity of the system to resolve them.  

To counter instability:

o  Identify the noise background.  Difficult if the hacker 
   can hide in the noise.

o  Regulate and test any interdimensional relationship or 
   signal.  Precisely identify extra-domain relationships.

o  Design such that system uses the smallest number of terms.  
   As Dr Goldfarb says, conserve nouns, and I say, test verbs.

o  Ensure terms with a large referent set are carefully monitored 
   when applied.  Rigorously QA broadcast deliverables by policy.

o  Structure terms into strongly bound classes

o  Collect performance data to identify emerging instabilities.  Compare 
   local events and environment continuously (use current maps and 
   keep them current).

o  Isolate inherently unstable components or processes from 
   the network.  Unstable processes are often useful particularly 
   as they operate near the edge of onset of chaos, and therefore, 
   are engines of evolution. "...crazy but we need the eggs."

o  Design system to maximize opportunism and cooperation among 
   dependent subsystems.  If a system is becoming baroque, it 
   is in need of redesign.  If the slightest deviation is a cause 
   of controversy, you probably have a system that is overly sensitive.
   Note this is an issue for many object-oriented systems that use 

o  Avoid intrigue as a means to administer policy.  The thing to
   know about Machiavelli is, he was fired.  Do not make an employee 
   bet their badge as the price of innovation.  Don't white pig.  If 
   the price of innovation is to watch others get the reward for it, the
   behavior will be extinguished.

As some extra reading, the Taguchi Model for process evolution and 
Deming's TQA work are worthy.  As in all things, over applied, they 
are also a good way to exhaust an organization.  Beware the problem 
of top-heavy control systems.  In most business transactions, if 
the customer is satisfied, you are done.  They'll call you if they 
need you.  Make sure they know you will respond when they call.


Ekam sat.h, Vipraah bahudhaa vadanti.
Daamyata. Datta. Dayadhvam.h

-----Original Message-----
From: Joshua Allen [mailto:joshuaa@microsoft.com]

To me, the trust issue is the one with which we have the least experience as
an industry.  This is also going to be the most important cahllenge for us
to solve long-term.  One interesting project is at

P.S. We tolerate inconsistencies in the real world all the time.  To quote
from a favorite play by Pirandello, "Oh sir, you know well that life is full
of infinite absurdities, which, strangely enough, do not even need to appear
plausible, since they are true."


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