[comp.simulation] SIMULATION DIGEST V21 N8

simulation@uflorida.cis.ufl.edu (Moderator: Paul Fishwick) (05/09/91)

Volume: 21, Issue: 8, Wed May  8 16:45:46 EDT 1991

+----------------+
| TODAY'S TOPICS |
+----------------+

(1) RE: Pendulum Problem
(2) WANTED: Network Modelling Software
(3) Network Analysis
(4) Qualitative and Qualitative Interfaces
(5) BOOK: The Art of Computer Systems Performance Analysis
(6) WANTED: Tools for Modeling Surface Phenomena

* Moderator: Paul Fishwick, Univ. of Florida
* Send topical mail to: simulation@bikini.cis.ufl.edu OR
  post to comp.simulation via USENET
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* Simulation Tools available by doing above and changing the
  directory to pub/simdigest/tools. 



-----------------------------------------------------------------------------

Date: Fri, 26 Apr 91 09:45:48 -0400
From: "Paul Fishwick" <fishwick@fish.cis.ufl.edu>
To: simulation@ufl.edu
Subject: Pendulum Problem

>From uflorida!caen!sdd.hp.com!cs.utexas.edu!ut-emx!emx.utexas.edu Fri Apr 26 09:45:19 EDT 1991
Article: 556 of comp.theory.dynamic-sys
Path: uflorida!caen!sdd.hp.com!cs.utexas.edu!ut-emx!emx.utexas.edu
From: hasan@emx.utexas.edu (David A. Hasan)
Newsgroups: comp.theory.dynamic-sys
Subject: double pendulum
Date: 25 Apr 91 19:56:23 GMT
Sender: hasan@ut-emx.uucp
Organization: UTexas Center for Space Research

I have failed from within my newsreader and my mailer in
trying to send mail directly to richard.  So here is my
response to his questions about potential energy of the
double pendulum problem.  Sorry to the rest of you for its
length...



In article <puchm.672390379@cutmcvax> you write:
>
>
>                T1 = 1/2 * m1 * l1 * th1.
>                T2 = 1/2 * m2 * (l1 * th1. + l2 * th2.)
>

I think that you meant to *square* the velocity terms in these
expressions, right?

>                U1 = -m1 * g * l1 * cos(th1)
>                U2 = -m2 * g * l2 * cos(th2) * l1 * cos(th1)
>
>            Are the potentials correct ?

Except for the typo in U2 (the two l-cosine terms should be
added together instead of multiplied), this looks ok.

>            If YES, why ?
>            If NO, why and what are the correct ones?
>            The above questions should indicate a total lack of
>            understanding as to the formulation of the potentials.
>

"Potential energy" as a fundamental principal on which to base
your analysis has some difficulties if the form of the
potential is not obvious to start with.  In fact, potential
energy is another way of representing the "work" done
by so-called conservative forces.  In a uniform gravity field
(situations where the effect of gravity is usefully modeled as
a constant acceleration due to gravity -- g), the potential
has the form  

       U = mgh

where h is the distance *above* some arbitrarily selected
reference.  ("above" = "opposed to gravity")  The reasons why the
reference can be selected arbitrarily are not really important
(it is because the FORCE due to gravity is calculated by 
differentiating the potential, and in the process of
differentiating all constants drop out), but is is *crucial*
that you select ONE reference (sometimes called a "datum") and
use it for all your derivations.  Based on the expressions you
have given, the reference seems to be the "root" hinge of the
system. 

The form U=mgh is derived from basic princples as follows:

The potential energy is defined as the negative of the work
done by gravity on the mass in moving it from the datum to
its location.  Work done is a dot-product of the gravity force
and the displacement.  But the gravity force is downward and
the displacement is upward, so the dotproduct in the
definition of work gives you

    work done by gravity = (force vector) . (displ. vector)
                         = - (mg) (h)
                         = -mgh

But the potential energy is the NEGATIVE of this:

    U = -( work done by gravity )
      = -( - mgh )
      =  mgh

In your case, the masses are BELOW the reference, so h
(which is defined as the height ABOVE the reference) is a
negative quantity.  Of course, it is useful in this problem to
work with (positive) distance quantities such as
          l_1 * cos(theta_1)                       
          l_1 * cos(theta_1) + l_2 * cos(theta_2)  
which are distances of the masses BELOW the reference.  This
is where the negative sign comes in.     



Now, the question you ask about "how to derive the potential
energy" is actually more involved than this in general.  I
don't know exactly what directions your work will take you,
but if your simulations are going to handle more complex
systems, you might be required to go beyond the discussion
above.  Ultimately, it all boils down to understanding what
forces are acting on the system and representing as many of
them as possible by a potential energy.  (By the way, this is
not always possible, for example if the pendulum is suspended
in a fluid, you'll have to deal with the fluid forces using
work principles directly.)

In my work, I'm dealing with flexible vehicles in orbit.  The
flexibility intoduces internal stresses which do work and can
be modelled by a potential energy.  And the gravitational
forces can also be modelled as a potential energy.  However,
these potential energies have a different form than the
(simple) U=mgh discussed above.  The differences are due
primarily to the fact that the forces themselves act in a
significantly more complicated manner than the force due to
gravity in a uniform gravity field.

If all you need to do in model point masses and rigid bodies
near the surface of the earth, then the U=mgh stuff will get
you quite far.  Just be warned, however, that the fundamental
principles are somewhate "hidden" by the notion of potential
energy.



Finally, beware that there are some people out there who
discuss "potential functions".  The field of celestial
mechanics is full of these.  It is an unfortunate and often
confusing fact that potential functions and energies differ in
their definitions by a minus sign.  So if you go beyond U=mgh
in your efforts, pay attention to the small print.

 -- 
 |   David A. Hasan
 |   hasan@emx.utexas.edu 





------------------------------

Date: Tue, 30 Apr 91 15:35:10 EDT
From: rgirard@ncs.dnd.ca (R. Girard)
To: fishwick@bikini.cis.ufl.edu
Subject: LOOKING FOR NETWORK MODELLING SOFTWARE

   I am looking for a network simulator or simply a set of C routines
I could use to build to a rough model of a packet switching network
toward optimization of performance and reliability?

   I was told that there is at least one such modelling tool in the public domain.  It is called XSIM and is supposed to model a tcp/ip network. I have left posted Thanks!


<address this by e-mail to fishwick@uflorida.cis.ufl.edu>



------------------------------

Return-Path: <samuels@starbase.mitre.org>
Date: Wed, 1 May 91 07:55:19 EDT
From: samuels@starbase.MITRE.ORG (Mike Samuels)
To: simulation@bikini.cis.ufl.edu
Subject: Network Analysis help request


I'm working on a scenario generator for an automated highway
simulation.  My marching orders are to provide a list of vehicles with
start times, origin and destination, and the optimal path to get from
origin to destination.  The path should be optimized for shortest
delay within the capacity constraints of the network.

	The shortest delay is straightforward.  Floyd developed an
algorithm awhile back that solves the shortest path problem from any
source and any sink; i.e., a node can be both a source and sink at the
same time.  The literature calls this the "multiterminal shortest
chain problem".  The problem is when you add capacity constraints, the
problem seems to get a lot more complex.  The out-of-kilter algorithm
solves the problem if you have 1 source and 1 sink, or perhaps a set
of sources and a separate set of sinks, but it doesn't extend Floyd's
multiterminal chain solution to include capacities.  The only
algorithm we've run across that comes close is from Kleinrock, Volume
2, p. 340 ff.; he calls it the "Flow Assignment" algorithm.  It is a
gradient analysis solution, supposedly inching its way towards a
solution without getting too close to the capacity - at that point, it
will blow up.  The algorithm uses Floyd as part of its solution, so it
looks promising.  However, Kleinrock's description is a little terse -
nothing like the depth provided in a network analysis book (e.g.,
"Fundamentals of Network Analysis" by Phillips & Diaz-Garcia).  I've
printed out each step of the algorithm, and the results look terrible.

Does anyone know of a better algorithm?  All the network analysis
literature I've seen discusses numerous variations on the shortest
path algorithm, an equivalent number on maximal flow, and then a few
variations of the out-of-kilter generalized solution.  Noone seems to
cover an extension of the Floyd algorithm to include capacity
constraints.

Thanks for any help you can provide.


Michael Samuels                         The MITRE Corporation
samuels@mitre.org                       Mailstop W448
(703) 883-7828                          7525 Colshire Drive
FAX: (703) 883-6435                     McLean, VA 22102    



------------------------------

Date: Thu, 2 May 1991 18:07:26 +0200
X400-Originator: guasch@esaii.upc.es
X400-Mts-Identifier: [/PRMD=iris/ADMD= /C=es/;910502180726]
X400-Content-Type: P2-1984 (2)
Content-Identifier: 42
Conversion: Prohibited
From: Antoni Guasch <guasch@esaii.upc.es>
To: simulation@ufl.edu (Receipt Notification Requested) (Non Receipt Notification Requested)
Subject: Quantitative & Qualit. interfaces



We are the Simulation Group of the Computing and Control Engineering
Department at the Politechnical University of Catalonia, Barcelona
(Spain). We are currently starting a research project in Qualitative Simulation 
in general and the interface between quantitative and qualitative modeling
in particular.  

We are very interested on any work (papers, ongoing project, research
groups) related to the interface between both modeling methodologies.
 
We will forward the received information to the list.

Alvaro de Albornoz
Departament ESAII
Universitat Politecnica de Catalunya
Diagonal 647 - 2 planta
08028 Barcelona

e-mail: ALBORNOZ@ESAII.UPC.ES   


------------------------------

To: comp-simulation@Decwrl.dec.com
Path: nntpd.lkg.dec.com!manage.enet.dec.com!jain
From: jain@manage.enet.dec.com (Raj Jain, DEC, 550 King st, Littleton, MA, 01460, 508-486-7642, Fax:486-5279)
Newsgroups: comp.simulation
Subject: New Book Announcement: The Art of Computer Systems Performance Analysis
Date: 5 May 91 14:19:34 GMT
Sender: newsdaemon@shlump.nac.dec.com
Organization: Digital Equipment Corporation



              The Art of Computer Systems Performance Analysis:
  Techniques for Experimental Design, Measurement, Simulation, and Modeling
                                 By Raj Jain

    John Wiley & Sons, New York, ISBN 0471-50336-3, 720 pages, April 1991.

This book emphasizes simple-to-use techniques that can be applied by computer
system designers, managers, marketing professionals, buyers, analysts, and
others who need to compare alternative systems (computers, processors,
devices, networks, databases, operating systems, languages, algorithms, or
applications) or manage such projects.

The 720-page volume covers virtually every aspect of systems evaluation from
performance specification, capacity planning, and monitoring systems in use,
to summarizing measured data, designing experiments, simulating future
designs, and modeling the effect of proposed changes.

The book reveals how to avoid common mistakes, and shows how to protect
oneself from misleading analyses presented by others.  Given a set of
performance data on two or more systems, it is sometimes possible to
manipulate the data, benchmarks, analysis, metrics, or data presentation such
that either system can be shown to outperform the other!

More than 150 examples and case studies cover topics such as evaluation of
microprocessors, RISC processors, remote procedure calls, the UNIX operating
system, garbage collection algorithms, interconnection networks, local area
networks, text-formatting programs, cache and scheduler design issues and
more.

It has been selected as the *main* selection by the NewBridge Library of
Computer and Information Sciences (LCIS) bookclub.

                             EXPERTS' OPINIONS...

"At last, a welcome and needed text for computer professionals who require
practical, ready-to-apply techniques for performance analysis.  Highly
recommended!"
            --- Professor Leonard Kleinrock, Univ of California at Los Angeles

"The Art of Computer Systems Performance Analysis is an extraordinary book.
It has a practical, problem-oriented style which appeals immediately to
engineers engaged in real-world design and analysis."
                                          --- Vint Cerf, Chairman, ACM SIGCOMM

"An entirely refreshing text which has just the right mixture of theory and
real world practice.  The book is ideal for both classroom instruction and
self study."
    --- Professor Raymond L. Pickholtz, President, IEEE Communications Society

"An extraordinarily comprehensive treatment of both theoretical and practical
issues."
            --- Dr. Jeffrey P. Buzen, Internationally known performance expert

"It is the most thorough book available to date."
                  --- Professor Erol Gelenbe, Universite Rene Descartes, Paris

"This is an unusual object, a textbook that one wants to sit down and peruse.
The prose is clear and fluent, but more important, it is witty."
                                             --- Allison Mankin, in Simulation

"The frequent use of case studies was effective and sometimes entertaining."
                    --- Craig Partridge, Editor, Computer Communication Review

"It is extremely comprehensive -- I am hard pressed to think of a performance
evaluation technique that isn't discussed here.  The emphasis is on practical
techniques that could be used without a great deal of mathematical
sophistication."
                      ---Professor David Finkel, Performance Evaluation Review

"I found that the pace of the material was very even, which makes it a
particularly suitable text from which to teach."
  --- Professor Jon Crowcroft, Univ College London, in Computer Communications

                  A LIST OF INTERESTING "DON'T MISS" TOPICS

o  How to show a better performance for your system without any changes
   (Beware of ratio games played by your competitors)
   (Performance games people play) [p 130-131, 146, 165-174]
o  Four rat holes to avoid in performance presentations
   (Four easy ways to stall anybody's performance presentation) [p 162]
o  Twenty six ways to stall your competitor's presentation
   (How to kill your competitors' performance presentations) [p 161-162]
o  Six mistakes to avoid in preparing charts for presentations [p 144-146]
o  Six tricks to watch out for in your competitors' presentation graphics [p
   146-150]
o  Twenty two mistakes to avoid in your performance analyses [p 14-22]
o  Ten problems in computer systems capacity planning [p 125-127]
o  Twelve common mistakes in benchmarking computer systems [p 127-130]
o  Seven benchmarking games to watchout [p 130-131]
o  Thirty four ways to improve your programs' performance [p 114-116]
o  Twenty six guidelines for good graphics in your presentations [p 141-143]
o  Eleven mistakes to avoid in empirical modeling [p 266-269]
o  Six common mistakes in experimental design [p 278-279]
o  Eight mistakes that may lead to incorrect simulation results [p 394-395]
o  Seven reasons why most simulations fail [p 395-397]
o  Six guidelines for selecting seeds for random number generators [p 453-455]
o  Six myths about random-number generators [p 455-458]
o  Thirteen system behaviors that are difficult to analyze using queueing
   models [p 620-622]

                            OTHER TOPICS DISCUSSED

I  AN OVERVIEW OF PERFORMANCE EVALUATION
o  When to measure, simulate, or model?
o  How to select the right performance criteria?
o  How to specify performance requirements?

II MEASUREMENT TECHNIQUES AND TOOLS
o  Which benchmarks are commonly used in the industry?
o  How to design the right workload for your system?
o  How to monitor your distributed systems?
o  How to use accounting logs to determine the workload of your system?
o  How to plan and manage capacity required for your computer installation?

III PROBABILITY THEORY AND STATISTICS
o  How to summarize measurements with a single number?
o  How to report variability?
o  How much confidence can you put on data with a large variability?
o  How many measurements do you need to compare two systems?
o  How to compare systems using multiple benchmarks?

IV EXPERIMENTAL DESIGN AND ANALYSIS
o  How many experiments do you really need?
o  How to get the most information with the minimum number of experiments?
o  Is one system really better than another?  Or is it the effect of very
   different benchmarks?
o  How to isolate measurement errors?
o  How to check if a model is adequate?

Part V:  SIMULATION
o  What language should you use for a simulation?
o  How to verify and validate a simulation model?
o  How long to run a simulation?
o  How to generate random numbers and how to select seeds?
o  What probability distributions should you use?

Part VI:  QUEUEING MODELS
o  How to use simple queueing models to quickly answer common questions?
o  How to obtain response time, queue lengths, and device utilizations?
o  How to obtain bounds, variance, and other statistics on system performance?
o  How to subdivide a large queueing network model and solve it?

                         FOR INSTRUCTORS AND STUDENTS

Designed to be the main textbook for a first course on performance evaluation,
it provides a comprehensive treatment of all aspects of performance analysis.
You no longer need separate books for measurement, statistics, experimental
design, simulation, and queueing theory.  If you teach a course on computer
systems such as architecture, engineering, networks, or databases, you can use
it as a supporting textbook to cover performance issues.

The chapters are organized so that each one can be presented in 45 minutes,
with time left over to discuss the exercises and solutions in a typical
55-minute class.  This makes the text ideally suited for a one- or
two-semester course.  Practice exercises at the end of each chapter can be
used for homework.  Solutions to the exercises appear at the end of the book.

                              TABLE OF CONTENTS

The book consists of 36 chapters divided into six parts.  The chapter titles
are listed below.

1. AN OVERVIEW OF PERFORMANCE EVALUATION:  Introduction.  Common Mistakes and
   How to Avoid Them.  Selection of Techniques and Metrics.

2. MEASUREMENT TECHNIQUES AND TOOLS:  Types of Workloads.  The Art of Workload
   Selection.  Workload Characterization Techniques.  Monitors.  Program
   Execution Monitors and Accounting Logs.  Capacity Planning and
   Benchmarking.  The Art of Data Presentation.  Ratio Games.

3. PROBABILITY THEORY AND STATISTICS:  Summarizing Measured Data.  Comparing
   Systems Using Sample Data.  Simple Linear Regression Models.  Other
   Regression Models.

4. EXPERIMENTAL DESIGN AND ANALYSIS:  Introduction to Experimental Design.
   2**k Factorial Designs.  (2**k)r Factorial Designs with Replications.
   2**(k-p) Fractional Factorial Designs.  One-Factor Experiments.  Two-Factor
   Full Factorial Design without Replications.  Two-Factor Full Factorial
   Design with Replications.  General Full Factorial Designs with k Factors.

5. SIMULATION:  Introduction to Simulation.  Analysis of Simulation Results.
   Random-Number Generation.  Testing Random-Number Generators.
   Random-Variate Generation.  Commonly Used Distributions.

6. QUEUEING MODELS:  Introduction to Queueing Theory.  Analysis of a Single
   Queue.  Queueing Networks.  Operational Laws.  Mean-Value Analysis and
   Related Techniques.  Convolution Algorithm.  Hierarchical Decomposition of
   Large Queueing Networks.

                               ABOUT THE AUTHOR

With over sixteen years of experience in the field of computer systems
performance, Raj Jain is a Senior Consulting Engineer at Digital Equipment
Corporation.  He received the Ph.D.  degree in Computer Science from Harvard
University and has taught courses on performance analysis at Massachusetts
Institute of Technology.

Author's Address:  Raj Jain, 137 Dutton Road, Sudbury, MA 01776-2804, USA.
Internet:  Jain@Erlang.enet.DEC.Com

                                 BOOK REVIEWS

o  Simulation, Vol.  56, No.  1, January 1991, p.  60.
o  Computer Communications Review, Vol.  21, No.  1, January 1991, p.  13.
o  Performance Evaluation Review, Vol.  18, No.  3, November 1990, p.  21-22.
o  ConneXions, Vol.  5, No.  2, February 1991, p.  22.
o  Computer Communications, Vol.  14, No.  4, May 1991.
o  Computer Marketing Newsletter, Vol.  XIV, No.  12, May 1991, p.  4.

The book (ISBN 0471-50336-3, LCCN:  QA76.9E94J32 1991, 720 pp., April 1991,
$52.95, Hardcover) is published by John Wiley & Sons, 1 Wiley Drive, Somerset,
NJ 08875, Phone: (908)-469-4400, (800)-225-5945 Ext 2499, Fax: (908)-302-2300.
It is available NOW at most technical bookstores in the United States.  It can
also be obtained directly from the publisher.



------------------------------

Date: Sun, 5 May 1991 14:57 +8:00
From: THUDSONDL@cc.curtin.edu.au
Subject: request for software help
To: simulation@bikini.cis.ufl.edu
X-Envelope-To: simulation@uflorida.cis.ufl.edu
X-Vms-To: IN%"simulation@uflorida.cis.ufl.edu"

To whom it may concern:

I am interested in tools that will help in the construction of models of
dynamic surface phenomena such as forest fires, oil spills, epidemic spreads,
etc.  Could anyone there direct suggest some software that has been designed
for this purpose - perhaps some relevant literature as well.

Doug Hudson
School of Computing Science
Curtin University of Technology
Perth Western Australia


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END OF SIMULATION DIGEST
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