Real Time Systems (Uniprocessor, Parallel,

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Real Time Systems(Uniprocessor, Parallel,
Distributed)

• Johnnie W. Baker

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Introduction

• What is a Real-Time System?
• Correctness of the system depends not only on the
  logical results, but also on the time in which
  the results are produced.
• Works in a reactive and time-constrained
  environment
• Examples
• Real-time temperature control of a chemical
  reactor
• Space mission control system
• Nuclear power generator system
• Many safety-critical systems

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Introduction (Cont)

• What is an Embedded System?
• A combination of hardware software (a
  computational engine) to perform a specific
  function
• Is part of a larger system, say a real-time
  system, that may not be a computer
• Works in a reactive and time-constrained
  environment
• Example
• Pacemaker Defibrillator
• Smart card reader
• Elevator
• Weather/GPS satellite

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Key Properties

• Real-time systems
• Timeliness Concurrency
• Reliability
• Reactivity
• QoS
• Embedded systems
• Timeliness Concurrency
• Dedicated (not general purpose)
• Liveness (Non-terminating programs)
• Reliability
• QoS

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Specific Examples of Real Time Embedded Systems

• Cars
• Anti-lock Brake System (ABS)
• Air Traffic Control
• Evolution of Real-Time Embedded Systems
• Wireless Sensor Network
• Smart Sensor Networks Applications

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Cars

• Todays high-end automobile may have 100
  microprocessors
• 4-bit microcontroller checks seat belt
• Microcontrollers run dashboard devices
• 16/32-bit microprocessor controls engine

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Anti-lock Brake System (ABS)

• Pumps brake to reduce skidding
• Provides real-time safety

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Air Traffic Control
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Evolution of Real-Time Embedded Systems
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Wireless Sensor Network (WSN)

• Smart Sensor Processor Sensor Wireless
  Interface
• Miniature devices manufactured economically in
  large numbers
• Embedded in environments for distributed sensing
  and control

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Smart Sensor Networks Applications
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Other Real-Time Embedded Systems

• PDAs
• Printers
• IPODs
• Television
• Household appliances
• Wrist watches
• Game consoles
• Mars rovers
• Power grid management systems
• Air Traffic Control (??)
• Observation gt95 of all microprocessors are
  used for real-time embedded systems.

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Whats Special About Embedded Systems

• Must worry about non-functional constraints
• Real Time
• For systems to function correctly, their timing
  constraints must be satisfied.
• Memory footprint
• Power
• Reliability
• Safety
• Cost
• Just functionally working is NOT ENOUGH

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Taxonomy of Real-Time Systems
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Taxonomy of Real-Time Systems
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Taxonomy of Real-Time Systems
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Taxonomy Static

• Task arrival times can be predicted
• Static (compile-time) analysis possible
• Allows good resource usage (low idle time for
  processors).

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Taxonomy Dynamic

• Arrival times unpredictable
• Static (compile-time) analysis possible only for
  simple cases.
• Processor utilization decreases dramatically.
• In many real systems, this is very difficult to
  handle.
• Must avoid over-simplifying assumptions
• e.g., assuming that all tasks are independent,
  when this is unlikely.

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Taxonomy Soft Real-Time

• Allows more slack in the implementation
• Timings may be suboptimal without being
  incorrect.
• Problem formulation can be much more complicated
  than hard real-time
• Two common and an uncommon way of handling
  non-trivial soft real-time system requirements
• Set somewhat loose hard timing constraints
• Informal design and testing
• Formulate as an optimization problem

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Taxonomy Hard Real-Time

• Creates difficult problems.
• Some timing constraints are inflexible
• Simplifies problem formulation.

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Taxonomy Periodic

• Each task (or group of tasks) executes repeatedly
  with a particular period.
• Allows some static analysis techniques to be
  used.
• Matches characteristics of many real problems
• Not closely related to situations involving tasks
  that designers pretend are periodic.
• It is possible to have tasks with deadlines
  smaller, equal to, or greater than their period.
• The later are difficult to handle (i.e., multiple
  concurrent task instances occur).

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Taxonomy Periodic with Single-Rate

• One period in the system
• Simple but inflexible
• Used in implementing a lot of wireless sensor
  networks.

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Taxonomy Multirate Periodic

• Multiple periods
• Can use notion of circular time to simplify
  static (i.e., compile-time) schedule analysis.

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Taxonomy Aperiodic

• Are also called sporadic, asynchronous, or
  reactive.
• Creates a dynamic situation
• Bounded arrival time interval are easier to
  handle
• Unbounded arrival time intervals are impossible
  to handle with resource-constrained systems.

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Definitions

• Tasks and Jobs
• Processor and parallel distributed systems
• Deadline violations

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Tasks and Jobs

• Jobs are units of work that are scheduled and
  executed by the systems.
• The set of related jobs that can be solved by the
  same algorithm are called a task.
• A job is an instance of a task.

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Processor Systems

• A processor execute tasks
• May be assigned multiple concurrent tasks
• Parallel and distributed systems
• Consists of multiple processors
• The interprocessor communications has an impact
  on the systems performance.
• Communications can be difficult to evaluate,
  particularly for distributed and asynchronous
  parallel systems
• Two types of distributed systems
• Homogeneous One processor type
• Heterogeneous Multiple processor types.

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Missed Deadline Penalties

• Hard real-time systems
• Example Air Traffic Control, Medical Systems
• Firm real-time systems
• Example Banking, Production Control System
• Soft real-time systems
• Video on Demand, Inventory Management, Habitat
  Monitoring, Weather Prediction System

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Central Areas for Real-Time Study

• Allocation, assignment, and scheduling
• Operating systems and scheduling
• Parallel distributed systems and scheduling
• Observe Scheduling is central to the study of
  real-time systems

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Allocation, assignment, and scheduling

• Analyze task execution times
• Worst-case or average case (or both)
• Worst-case needed for critical, hard deadline
  systems
• Decide which processor will be used for each
  task.
• Decide how to manage allocation of resources to
  processors
• Decide the times at which all tasks will execute
• Provide guarantees when possible predictability
• Determine how deadlines will be met.

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Operating systems and scheduling

• How to best design operating systems to
• Support control over scheduling, etc. without
  increasing design error rate.
• Design operating system schedulers to support
  real time constraints
• Support predictable costs for task and OS service
  execution

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Parallel distributed systems and scheduling

• How to best control (usually dynamically)
  scheduling regarding
• Assigning tasks to processing nodes
• Scheduling execution of these tasks
• For distributed systems with processors separated
  over large distances
• Bound task deadline violations, when possible
• Minimize deadline violations, when no bound is
  possible.

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Why Parallel or Distributed Systems

• A single processor is unable to handle many
  actual real-time applications
• Can not execute the application within reasonable
  time limitations
• Value of the results obtain may degrade with the
  time required to obtain them.
• The memory is not sufficiently large to hold the
  essential data and program code for the
  application.
• Execution speed is insufficient to meet hard
  deadlines.
• A single point of failure is unacceptable for
  many applications.

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Challenging Aspects of Distributed and
Asynchronous Parallel Systems

• Shared resource management is challenging
• No global knowledge on workload
• No global knowledge on resource allocation
• Load balancing between processors is required
• Dynamic task scheduling normally used
• Almost all dynamic scheduling problems are
  NP-hard
• Must schedule execution so that all the critical
  hard deadlines are met
• Communication time is very difficult to predict
  on large applications where multiple tasks are
  assigned to each processor (i.e.,multitasking)

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Asynchronous Systems Problems (cont)

• Synchronization between different tasks and
  processors is expensive.
• A distributed database is normally required
• Must ensure data serializability and data
  integrity
• Problems unique to distributed systems
• Communication related errors
• E.g., out of order delivery of packets, packet
  loss, etc.
• No synchronized clock (or else clocks need to be
  synchronized regularly)

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Characteristics of a RTS

• Usually large and complex
• Vary from a few hundred lines of assembler or C
  to 20 million lines of Ada estimated for the
  Space Station Freedom
• Concurrent control of separate system components
• Devices operate in parallel in the real-world
  better to model this parallelism by concurrent
  entities in the program
• Facilities to interact with special purpose
  hardware
• need to be able to program devices in a reliable
  and abstract way

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Characteristics of a RTS (cont)

• Extreme reliability and safe
• Embedded systems typically control the
  environment in which they operate failure to
  control can result in loss of life, damage to
  environment, or economic loss
• Guaranteed response times
• we need to be able to predict with confidence the
  worst case response times for systems efficiency
  is important but predictability is essential
• Sometimes, no response is worse than a poor
  response

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Some Current Research Areas

• Temporal Quality of Service (QoS)
• Schedulability
• Predictability
• Reactivity
• Fault tolerance
• Robustness
• Sustain the fast changing operating conditions
• High integrity
• Functional independence
• Accurate Time Validation Algorithms

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Future Challenges

• Numerous challenges have been discussed in
  several papers in RTS and this list does not
  cover all of them.
• Real-time precision responses reactivity
• Fault-Tolerance under strict timing requirements
• Maintainability
• Testability under competitive pressures

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High-Level Challenges

• System evolution
• Open real-time systems
• Unknown hardware characteristics
• Mixture of applications, resource and time
  requirements
• Composibility
• Software Engineering

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Basic Challenges

• Science of performance guarantees
• Reliability formal verification
• General system issues
• Real-time multimedia
• Programming languages
• Education about real-time systems

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RT Market Growth in 1996

• Approx. 25 p.a.
• Estimate annual spending 2 bn.
• Robustness
• Sustain the fast changing operating conditions
• Accurate Validation Algorithms
• Current figures?

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Goals for Spring 2006 Course Parallel
Distributed RTS

• Cover basic concepts of RTS
• Additional focus on computational challenging
  aspects of Parallel Distributed RTS
• Taught more as a seminar course, with students
  doing some of the presentation.
• Textbook and references (see next slide)
• Book by Jane W. S. Liu will probably be textbook
• Book by Stankovic will probably be a reference
  (with copy in library or specific sections
  online)
• List of research papers
• Prerequisite for course
• Graduate Student in CS

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Main References

• Peter Dinda and Robert Dick, pdf lecture slides
  on Real-Time Systems, Fall 2005, Northwestern
  University, http//www.cse.wustl.edu/lu/cs520s/52
  0.htm
• John A. Stankovic, et. al., Strategic Directions
  in Real-Time and Embedded Systems, USC Slide
  Presentation, http//sunset.usc.edu/neno/cs589_20
  03/Week5b.ppt
• G. Marimaran, Lecture Slides on Real Time
  Systems, Iowa State University,
  http//vulcan.ee.iastate.edu/gmani/cpre558.F00/in
  dex.html
• Chenyang Lu, Lecture Slides on Real-Time Systems,
  Washington University in St. Louis, Fall 2005,
  http//www.cse.wustl.edu/lu/cs520s/520.htm
• Andy Wellings, University of York Research Group,
  Lecture slides for text Concurrent and Real-Time
  Programming in Java by Wellings,
  www.cs.york.ac.uk/rts/CRTJbook/Lecture1.ppt
• Jane W. S. Liu, Real-Time Systems, Prentice Hall,
  2000, ISBN 0-13-099651-3.
• John A. Stankovic, et. al., Deadline Scheduling
  for Real-Time Systems EDF and Related
  Algorithms, Kluwer Academic Publishers (now
  Springer), ISBN 0-7923-8269-2, 1998.

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Things to Possibly Add

• Common misconceptions one set of slides has
  this, as does Stankovics book.
• Some of the computational complex problems for
  multiprocessors that I want to include in this
  course.