EGR 518 Performability Performance and Dependability Analysis for Computer Systems

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EGR 518Performability (Performance and
Dependability) Analysis for Computer Systems

• Instructor Meng-Lai Yin
• Office Bldg. 9, Room 511
• Tel [phone]
• emailmyin_at_csupomona.edu

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Expectation

• A student, after take this class, is expected to
• Know the terminology and state-of-the-art
  technology in reliability, availability,
  performance, and performability
• Grasp an overall picture of the system being
  analyzed
• Recognize and determine the type of analysis
  needed for a particular task
• Construct corresponding models for the analysis
• Get familiar with provided computer-aided
  analysis tools to conduct the analysis
• Obtain quantitative as well as qualitative
  results from the models
• Validate the modeling results

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Course Outline

• Basic Concepts about Performability Modeling
• Probability Review
• Fault Tolerance Techniques
• Concepts about Modeling Approaches
• Modeling Tools
• Reliability Block Diagram
• Markov Modeling Technique
• Fault Tree Analysis
• Performance Analysis Queuing Models
• Integrate Performance and Dependability
• Case Studies, Project Presentations

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Assessment

• Homework 20
• Quizzes 20
• Midterm 20
• Final 20
• Project 20

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Text References

• Kishor S. Trivedi, Probability and Statistics
  with Reliability, Queuing and Computer Science
  Applications, second edition, John Wiley Sons,
  Inc. 2002, ISBN 0-471-33341-7.
• References
• 1 Robin A. Sahner, Kishor S. Trivedi, Antonio
  Puliafito,
• Performance and Reliability Analysis of Computer
  Systems
• An Example-Based Approach Using the SHARPE
  Software Package,
• Kluwer Academic Publishers, 1996. ISBN
  0-7923-9650-2.
• 2Martin L. Shooman, Reliability of Computer
  Systems and Networks,Fault Tolerance, Analysis,
  and Design, John Wiley Sons, Inc., 2002. ISBN
  0-471-29342-3.
• 3 http//www.crhc.uiuc.edu/PERFORM/home.html
• 4 http//www.eecs.umich.edu/jfm/
• 5 http//www.ee.duke.edu/kst/

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Ok. So, what is "Performability"?
The needs of High Performance, Fault Tolerant
Computing
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Fault-Tolerant Computing

• Fault-tolerant computing is a generic term
  describing redundant design techniques with
  duplicate components or repeated computations
  enabling uninterrupted (tolerant) operation in
  response to component failure (faults).

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Links
Performability

• http//www.crhc.uiuc.edu/PERFORM/home.html
• http//www.eecs.umich.edu/jfm/

Conferences
http//www.dsn.org http//www.rams.org
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An Example
The purpose of this example is to showthe
existences of performance degradable systems
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An email received on July 20, 2005 433PM

• We are experiencing problems with the AIX user
  account file systems. We need to take the AIX
  system off-line immediately to fix the problem.
  We expect the AIX file systems to be off line for
  approximately an hour and a half. We hope to
  have the file systems back on-line by 600PM.
• Sorry for any inconvenience.
• Sys Admin Team

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Later that day July 20, 2005 626PM

• All AIX file systems are back on-line except
  wei_snoop which is in a rebuild stage. Wei_snoop
  file system will be back on-line by 0600 tomorrow
  morning.
• Thanks,
• Sys Admin Team

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Observations

• The system is not totally failed even with the
  failed AIX file system
• The system can operate without the wei_snoop file
  system
• The system can be upgraded while operating

More and more systems become performance
degradable
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Performance Degradable Systems

• Performance degradable systems have the
  capability of continuing to operate failure-free
  in the presence of certain faults or errors by
  diminishing the level of quality of service 7.

Normal Scenario A system starts with all
components operational and performs at its
maximum capability. When a component fails, the
system will reconfigure itself and operate with
degraded performance, etc.
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Reasons for Performability Modeling

• Two separate measures in the past
• Traditional dependability analysis assumes no
  performance degraded states.
• Performance measures always are applied to fully
  operational state.
• Need an integrated, meaningful metric
• For performance degradable systems, where the
  system can operate in many different states, how
  do you address the systems performance?
• Traditional metrics (performance, reliability,
  availability. etc.) and the corresponding
  modeling techniques cannot catch the overall
  performance feature for performance degradable
  systems.

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The Beginning of Performability

• The term Performability was introduced almost
  three decades ago 4, by Prof. J. F. Meyer.

John F. Meyer Address 4111 EECS Phone (734)
763-0037Fax [phone] Professor Emeritus,
Electrical Engr Computer ScienceDegree Ph.D.,
U-Michigan
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A Tribute to M. D. Beaudry

• Before Dr. John F. Meyer gave the name
  performability to the world, several works
  actually had already been devoted to address the
  issue of providing appropriate metrics for
  performance degradable systems.
• In Particular, the work conducted by Danielle
  Beaudry 1 has been referenced in many places.
• In 1, she addressed the performance-related
  reliability measures for gracefully degraded
  systems (performance degradable systems ).

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Course Objectives

• At the conclusion of this course, a participant
  will be able to
• know the basic concepts about performability
• know how to
• conduct and evaluate a dependability analysis
  using Reliability Block Diagram (RBD) or Markov
  techniques
• conduct and evaluate a performance analysis using
  Queuing models
• conduct and evaluate a performability analysis
  using various modeling techniques

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Approach
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Performance Analysis

• Purpose
• To assess workload, traffic arrival rates,
  service time distributions, etc.
• To evaluate resource Contention Scheduling
• To assess the effects of Concurrency and
  Synchronization
• Measures
• Throughput
• Response time (mean dist.)
• others

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How about dependability?
So many terms have been used in this area, such
as reliability, availability, ..
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Reliability, Availability, Dependability

• They are all probabilities.
• What are the differences?

Definition of Reliability The probability of an
item to perform a required function under given
conditions for a given time interval. (without
any failure)
Definition of Availability "The probability of
an item to be in a state to perform a required
function at a given instant of time, assuming
that the external resources, if required, are
provided. (can have failures with repairs)
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Picture the Differences
time
t0
?
Reliability the probability that the item
survive theduration t0, ?)
time
t0
?
Availability the probability that the item is
working at time ?, given that the item was
working at time t0.
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Picture the Differences
1.0
Steady state availability
A typical reliability figure (without repair)
A typical availability figure (with repair)
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Calculating Reliability Availability

• Let ? be the failure rate for a component, and ?
  be the repair rate for that component.
• Assume exponential distribution for the failures
• Then reliability can be calculated as R(t) e
  -? t
• SS (Steady-State) -Availability can be assessed
  as
• or

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Dependability Umbrella term
Trustworthiness of a computer system such that
reliance can justifiably be placed on the service
it delivers
Copied from course materials provided by prof.
Trivedi
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Modeling Taxonomy
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Combinatorial Approach

• If a system consisting of n components, and every
  component is either working or failed, then we
  can simply list out of all the possible
  combinations and calculate the probability for
  each combination.

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Complexity Concerns

• How many possible combinations of the status of
  these n components?
• What can be done to manage the complexity?
• During model construction
• Need a more intelligent way to describe the
  systems failure behavior
• Series and parallel RBD (Reliability Block
  Diagram) approach
• During model solution
• Need more efficient ways of calculations, rather
  than counting individual probabilities

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Structured Combinatorial Approach

• Reliability block diagrams
• Integrate certain probability events into a
  module, which contains the info
• A probability of failure
• A failure rate
• A distribution of time to failure
• Steady-state and instantaneous unavailability
• Organize the modules in a structured way,
  according to the effects of each modules failure
• Statistical independence Assumption
• Failures independence
• Repairs independence

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Some Basic Terminology

• Redundancy Hardware (Static,Dynamic),
  information, Time, software
• Fault Types Permanent (needs repair or
  replacement), Intermittent (reboot/restart or
  replacement), Transient (retry),
• Fault, error, failure
• Fault detection, imperfect Coverage
• Maintenance scheduled (preventive), unscheduled
  (corrective)

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Terminology Continue

• Failure occurs when the delivered service no
  longer complies with the specification
• Error is that part of the system state which is
  liable to lead to subsequent failure
• Fault is adjudged or hypothesized cause of an
  error

Faults are the cause of errors that may lead to
failures
Fault
Error
Failure
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High Availability Intents

• Scott McNealy, Sun Microsystems Inc.
• "We're paying people for uptime.The only thing
  that really matters is uptime, uptime, uptime,
  uptime and uptime. I want to get it down to a
  handful of times you might want to bring a Sun
  computer down in a year. I'm spending all my time
  with employees to get this design goal
• SUN Microsystems SunUP RASCAL program for
  high-availability
• Motorola - 5NINES Initiative
• HP, Cisco, Oracle, SAP - 5nines5minutes Alliance
• IBM Cornhusker clustering technology for
  high-availability, eLiza, autonomic computing
• Microsoft Trustable computing initiative
• Microsoft Regular full page ad on 99.999
  availability in USA Today

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