Distributed Systems ==========================
In our world of computing there can be many different things which are distributed.
In computing there are at least two causes to every effect. There is the cause of the underlying machine or hardware platform as we so dearly like to call it, and there is the application or program which subsists off the provider layer.
(1) The service provider or hardware layer called the Computer platform.
(2) The application or program level which harbours the immediate accessibility to the qualification and quantification of the input information stream. If the input information stream does actually contain information then the computer system will respond according to its parameterization crieteria. With many aspects of the Computer System being distributed, the questions we ask are many and the possible model emerges like a giant standing ten foot tall, eddying, above the rubble!
(1) The provider is distributed.
(2) There are proximity distributions.
(2a) Delta-t distrubution or dt distributions.
(2b) Delta-s distributions or ds distributions.
(2c) Delta-e distributions or de distibutions.
(3)
Data is distributed.
(3a) Security.
(1a1) Hierarchial accessability.
(1a2) Auditing trails.
(1a3) One stop thievery.
(3b) Bottlenecks.
(3b1) Speed.
(3b2) Size.
(3b3) Other restrictions.
(3c) Safety.
(3c1) Fire.
(3c2) Terrorism.
(3c3) Natural weather systems.
(3d) Necessity.
(3d1) Natural locations.
(3d2) Hardware tresholds.
(3e)
(4) Information is distributed.
(5) Users are distributed.
(6) Equipement and apparatus are distributed.
(7) Memory is distributed.
(8) Instructions are distributed.
Practical Distributions.
We will take a practical look at distribution through a real-world example using high proximity distributions located and denoted by :
(a) LA. (b) Chicago. (c) Denver. (d) New York. (e) Miami. (f) Toronto. (g) Montreal. (h) Kingston. (i) Georgetown.
Examples of how the proximity grouping is obtained will be subsequently derived. High distribution centres like India, China, the African continent, Russia and the European Union will be examined as a context derivitive of the underlying distribution philosophy.
Distribution Philosophy
(1) Truth.
(2) Integrity.
(3) Gain.
(4) Input.
(5) Loss.
(6) Exchange.
(7) Transfer.
(7a) Objects can be readied but must wait on an incoming token or transition transfer to preserve sequencing.
(7b) Objects readied but are semantic entities which operate on their own with their own signalling and synchronous mechanisms and their codes of conduct are self-embedded.
(7c) Transition.
(7d) .
(8) Output.
(9) Query.
(10) Wait.
(11) Entropy.
(12) Result interpretation.
(13) Result corroboration.
(14) The Distribution Map
(a) dt away
(b) G(idt) where i is finite.
(c) Action Object.
(d) Fill in parameters.
(e) Response Form to set parameters.
(f) The Solution set. Example:
User(i) = Many links to system.
User(k) = Closest to system which is a link-0.
User(l) = Two links away from system. User(x) = Wants to link to system.
(f1) Each user has a j-parameter solution.
(f2) S(j) is the solution set for the j-parameters.
(f3) tR(j) is the Trace Relation of j which can accomodate the philosophy of distribution.
(f4) zR(j) or Z(j) is the Zero or Vaccuum solution for j.
(f5) iZ(j) corresponds to the many Z-solutions for j.
General Notes.
(1) Stack local changes.
(2) Transfer global parameters.
(3) Local Ghosts.
(4) Multiple distributions.
(5) Hard changes derived through an exchange.
(6) Soft changes arising from voluntary information or derived knowledge.
(7) State Predictions.
(8) Transition functions.
(8a) The cause-effect deterministic paradyne. f(x) which corresponds to cause has a parametric provider-system solution set S(j) where j is the j-parameter solution set. In this particular instant S() can be Newtonian, Gr, Quantum.
(9)