🚀 go-pugleaf

I think that trying to define a "distributed system" is a lot trying to
define an "artifically intelligent" system.  The definitive definition
remains elusive because these terms refer more to collections of techniques
and models of problems than to actual physical properties of systems.

A "distributed system" is a system that makes good use of "distributed
programming techniqes."  Of course, defining "distributed programming
technique" is no easier, but there are various characteristic features:
 -- The technique is designed to perform well in the presence of high
    communications latency, often being optimized for this property
    at the expense of other costs that would be relatively more significant
    in a system having lower communications latencies.
 -- The technique may also be optimized for low communications bandwidth.
    This is similar to, but should not be confused with high latency.
    Even high-bandwidth fiber-optic networks don't have to be all that long
    for latency to be significantly greater than memory access time.
 -- Techniques for improving reliability and availability via replication
    are often considered to be "distributed computing techniques", both
    because distributed systems *can* be partially available due to being
    physically distributed, and because they often *are* partially available
    due to their complexity.
 -- Techniques for acheiving security with insecure communications are
    "distributed techniques", since distributed systems often have insecure
    communications.
 -- Techniques for locating services or objects given some symbolic or
    indirect "name" are often "distributed" techniques, since the fluid
    configuration of distributed systems makes indirect references necessary.

If you agree that distributedness is a matter of degree rather than a
boolean attribute, then it is clearly hopeless to firmly discriminate
between a "distributed system" and a "multiprocessor", since a system can be
built at any level of "distributedness".

Going back to the A.I analogy, I think that these complaints about there not
"really being any commercial distributed systems" are similar to the
complaints from A.I. researchers about all these expert systems companies
not doing "real A.I.".  The problem with both these fields is that once a
technique really works well, it tends to be co-opted by ordinary programmers
trying to get work done.

A.I. started with heuristic search and logical inference algorithms.
Probably distributed systems started the day that someone ran a serial line
across the room to the next machine.  Basic applications of these techniques
are not very sexy research anymore, and thus not "real" A.I. or distributed
systems to academics.  

A conflicting pressure comes from the hype factor in industry.  "Buy our
system because it's distributed."  Even ignoring the vagueness of
"distributed", this is a bogus claim, since a rational consumer should make
their choice based on how well the system solves their problem, rather than
on how the system is implemented.

Rob