The document summarizes topics related to real-time software engineering including embedded system design, architectural patterns for real-time software, timing analysis, and real-time operating systems. It discusses key characteristics of embedded systems like responsiveness, the need to respond to stimuli within specified time constraints, and how real-time systems are often modeled as cooperating processes controlled by a real-time executive. The document also outlines common architectural patterns for real-time systems including observe and react, environmental control, and process pipeline.
This Presentation contains all the topics in design concept of software engineering. This is much more helpful in designing new product. You have to consider some of the design concepts that are given in the ppt
This Presentation contains all the topics in design concept of software engineering. This is much more helpful in designing new product. You have to consider some of the design concepts that are given in the ppt
The difference between in-depth analysis of virtual infrastructures & monitoringBettyRManning
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Virtualization is an indispensable part of a modern data center. Frequently, the degree of virtualization is 90 percent or more. What formerly operated on a number of servers today runs on a few hosts.
PreMonR - A Reactive Platform To Monitor Reactive ApplicationKnoldus Inc.
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Applications whose foundation is laid on Reactive Manifesto accounts for being Reactive Applications. But can any monitoring pipeline ensure that its worthy enough to monitor your reactive fleet?
With years of experience in Reactive stack; Knoldus compiles all its learning into a Premonition based Reactive Monitoring and Alerting Platform i.e PremonR which is a single solution for all your enterprise monitoring needs.
Covers security and privacy issues for software product developers including attacks and defenses, encryption, authentication, authorisation and data protection
Discusses the microservices architectural style for cloud-based systems. Explains what is meant by microservices and architectural choices for microservices
Introduces some fundamentals of cloud based software and discusses architectural issues for product developers. Covers containers, databases and cloud architecture choices
Dev Dives: Train smarter, not harder â active learning and UiPath LLMs for do...UiPathCommunity
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đĨ Speed, accuracy, and scaling â discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Miningâĸ:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing â with little to no training required
Get an exclusive demo of the new family of UiPath LLMs â GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
đ¨âđĢ Andras Palfi, Senior Product Manager, UiPath
đŠâđĢ Lenka Dulovicova, Product Program Manager, UiPath
DevOps and Testing slides at DASA ConnectKari Kakkonen
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My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
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After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more âmechanicalâ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
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The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties â USA
Expansion of bot farms â how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks â Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
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Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as âpredictable inferenceâ.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
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A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
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Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
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Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
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Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
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Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But thereâs more:
In a second workflow supporting the same use case, youâll see:
Your campaign sent to target colleagues for approval
If the âApproveâ button is clicked, a Jira/Zendesk ticket is created for the marketing design team
Butâif the âRejectâ button is pushed, colleagues will be alerted via Slack message
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And...
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Charlie Greenberg, Host
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
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In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
âĸ The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
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âĸ Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
âĸ Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
2. Topics covered
ī˛ Embedded system design
ī˛ Architectural patterns for real-time software
ī˛ Timing analysis
ī˛ Real-time operating systems
04/12/2014 Chapter 21. Real-time Software Engineering 2
3. Embedded software
ī˛ Computers are used to control a wide range of systems
from simple domestic machines, through games
controllers, to entire manufacturing plants.
ī˛ Their software must react to events generated by the
hardware and, often, issue control signals in response to
these events.
ī˛ The software in these systems is embedded in system
hardware, often in read-only memory, and usually
responds, in real time, to events from the systemâs
environment.
04/12/2014 Chapter 21. Real-time Software Engineering 3
4. Responsiveness
ī˛ Responsiveness in real-time is the critical difference
between embedded systems and other software
systems, such as information systems, web-based
systems or personal software systems.
ī˛ For non-real-time systems, correctness can be defined
by specifying how system inputs map to corresponding
outputs that should be produced by the system.
ī˛ In a real-time system, the correctness depends both on
the response to an input and the time taken to generate
that response. If the system takes too long to respond,
then the required response may be ineffective.
04/12/2014 Chapter 21. Real-time Software Engineering 4
5. Definition
ī˛ A real-time system is a software system where the correct
functioning of the system depends on the results
produced by the system and the time at which these
results are produced.
ī˛ A soft real-time system is a system whose operation is
degraded if results are not produced according to the
specified timing requirements.
ī˛ A hard real-time system is a system whose operation is
incorrect if results are not produced according to the
timing specification.
04/12/2014 Chapter 21. Real-time Software Engineering 5
6. Characteristics of embedded systems
ī˛ Embedded systems generally run continuously and do
not terminate.
ī˛ Interactions with the systemâs environment are
unpredictable.
ī˛ There may be physical limitations that affect the design
of a system.
ī˛ Direct hardware interaction may be necessary.
ī˛ Issues of safety and reliability may dominate the system
design.
04/12/2014 Chapter 21. Real-time Software Engineering 6
8. Embedded system design
ī˛ The design process for embedded systems is a systems
engineering process that has to consider, in detail, the
design and performance of the system hardware.
ī˛ Part of the design process may involve deciding which
system capabilities are to be implemented in software
and which in hardware.
ī˛ Low-level decisions on hardware, support software and
system timing must be considered early in the process.
ī˛ These may mean that additional software functionality,
such as battery and power management, has to be
included in the system.
04/12/2014 Chapter 21. Real-time Software Engineering 8
9. Reactive systems
ī˛ Real-time systems are often considered to be reactive
systems. Given a stimulus, the system must produce a
reaction or response within a specified time.
ī˛ Periodic stimuli. Stimuli which occur at
predictable time intervals
ī§ For example, a temperature sensor may be polled 10 times per
second.
ī˛ Aperiodic stimuli. Stimuli which occur at
unpredictable times
ī§ For example, a system power failure may trigger an
interrupt which must be processed by the system.
04/12/2014 Chapter 21. Real-time Software Engineering 9
10. Stimuli and responses for a burglar alarm
system
Stimulus Response
Clear alarms Switch off all active alarms; switch off all lights that have
been switched on.
Console panic button positive Initiate alarm; turn on lights around console; call police.
Power supply failure Call service technician.
Sensor failure Call service technician.
Single sensor positive Initiate alarm; turn on lights around site of positive
sensor.
Two or more sensors positive Initiate alarm; turn on lights around sites of positive
sensors; call police with location of suspected break-in.
Voltage drop of between 10%
and 20%
Switch to battery backup; run power supply test.
Voltage drop of more than 20% Switch to battery backup; initiate alarm; call police; run
power supply test.
04/12/2014 Chapter 21. Real-time Software Engineering 10
11. Types of stimuli
ī˛ Stimuli come from sensors in the systems environment
and from actuators controlled by the system
ī§ Periodic stimuli These occur at predictable time intervals.
ī§ For example, the system may examine a sensor every 50
milliseconds and take action (respond) depending on that sensor
value (the stimulus).
ī§ Aperiodic stimuli These occur irregularly and unpredictably and
are may be signalled using the computerâs interrupt mechanism.
ī§ An example of such a stimulus would be an interrupt indicating
that an I/O transfer was complete and that data was available in
a buffer.
04/12/2014 Chapter 21. Real-time Software Engineering 11
12. A general model of an embedded real-time
system
04/12/2014 Chapter 21. Real-time Software Engineering 12
13. Architectural considerations
ī˛ Because of the need to respond to timing demands
made by different stimuli/responses, the system
architecture must allow for fast switching between
stimulus handlers.
ī˛ Timing demands of different stimuli are different so a
simple sequential loop is not usually adequate.
ī˛ Real-time systems are therefore usually designed as
cooperating processes with a real-time executive
controlling these processes.
04/12/2014 Chapter 21. Real-time Software Engineering 13
15. System elements
ī˛ Sensor control processes
ī§ Collect information from sensors. May buffer information
collected in response to a sensor stimulus.
ī˛ Data processor
ī§ Carries out processing of collected information and computes
the system response.
ī˛ Actuator control processes
ī§ Generates control signals for the actuators.
04/12/2014 Chapter 21. Real-time Software Engineering 15
16. Design process activities
ī˛ Platform selection
ī˛ Stimuli/response identification
ī˛ Timing analysis
ī˛ Process design
ī˛ Algorithm design
ī˛ Data design
ī˛ Process scheduling
04/12/2014 Chapter 21. Real-time Software Engineering 16
17. Process coordination
ī˛ Processes in a real-time system have to be coordinated
and share information.
ī˛ Process coordination mechanisms ensure mutual
exclusion to shared resources.
ī˛ When one process is modifying a shared resource, other
processes should not be able to change that resource.
ī˛ When designing the information exchange between
processes, you have to take into account the fact that
these processes may be running at different speeds.
04/12/2014 Chapter 21. Real-time Software Engineering 17
18. Mutual exclusion
ī˛ Producer processes collect data and add it to
the buffer. Consumer processes take data from the
buffer and make elements available.
ī˛ Producer and consumer processes must be
mutually excluded from accessing the same
element.
ī˛ The buffer must stop producer processes
adding information to a full buffer and consumer
processes trying to take information from an empty
buffer.
04/12/2014 Chapter 21. Real-time Software Engineering 18
20. Real-time system modelling
ī˛ The effect of a stimulus in a real-time system may
trigger a transition from one state to another.
ī˛ State models are therefore often used to describe
embedded real-time systems.
ī˛ UML state diagrams may be used to show the states
and state transitions in a real-time system.
04/12/2014 Chapter 21. Real-time Software Engineering 20
21. State machine model of a petrol (gas) pump
04/12/2014 Chapter 21. Real-time Software Engineering 21
22. Sequence of actions in real-time pump control
system
ī˛ The buyer inserts a credit card into a card reader built
into the pump.
ī˛ Removal of the card triggers a transition to a Validating
state where the card is validated.
ī˛ If the card is valid, the system initializes the pump and,
when the fuel hose is removed from its holster,
transitions to the Delivering state.
ī˛ After the fuel delivery is complete and the hose replaced
in its holster, the system moves to a Paying state.
ī˛ After payment, the pump software returns to the Waiting
state
04/12/2014 Chapter 21. Real-time Software Engineering 22
23. Real-time programming
ī˛ Programming languages for real-time systems
development have to include facilities to access system
hardware, and it should be possible to predict the timing
of particular operations in these languages.
ī˛ Systems-level languages, such as C, which allow
efficient code to be generated are widely used in
preference to languages such as Java.
ī˛ There is a performance overhead in object-oriented
systems because extra code is required to mediate
access to attributes and handle calls to operations. The
loss of performance may make it impossible to meet
real-time deadlines.
04/12/2014 Chapter 21. Real-time Software Engineering 23
25. Architectural patterns for embedded systems
ī˛ Characteristic system architectures for embedded
systems
ī§ Observe and React This pattern is used when a set of sensors
are routinely monitored and displayed.
ī§ Environmental Control This pattern is used when a system
includes sensors, which provide information about the
environment and actuators that can change the environment
ī§ Process Pipeline This pattern is used when data has to be
transformed from one representation to another before it can be
processed.
04/12/2014 Chapter 21. Real-time Software Engineering 25
26. The Observe and React pattern
Name Observe and React
Description The input values of a set of sensors of the same types are
collected and analyzed. These values are displayed in some way. If
the sensor values indicate that some exceptional condition has
arisen, then actions are initiated to draw the operatorâs attention to
that value and, in certain cases, to take actions in response to the
exceptional value.
Stimuli Values from sensors attached to the system.
Responses Outputs to display, alarm triggers, signals to reacting systems.
Processes Observer, Analysis, Display, Alarm, Reactor.
Used in Monitoring systems, alarm systems.
04/12/2014 Chapter 21. Real-time Software Engineering 26
27. Observe and React process structure
04/12/2014 Chapter 21. Real-time Software Engineering 27
28. Alarm system description
A software system is to be implemented as part of a burglar alarm
system for commercial buildings. This uses several different types of
sensor. These include movement detectors in individual rooms, door
sensors that detect corridor doors opening, and window sensors on
ground-floor windows that detect when a window has been opened.
When a sensor detects the presence of an intruder, the system
automatically calls the local police and, using a voice synthesizer,
reports the location of the alarm. It switches on lights in the rooms
around the active sensor and sets off an audible alarm. The sensor
system is normally powered by mains power but is equipped with a
battery backup. Power loss is detected using a separate power circuit
monitor that monitors the mains voltage. If a voltage drop is detected,
the system assumes that intruders have interrupted the power supply
so an alarm is raised.
04/12/2014 Chapter 21. Real-time Software Engineering 28
29. Process structure for a burglar alarm system
04/12/2014 Chapter 21. Real-time Software Engineering 29
30. The Environmental Control pattern
Name Environmental Control
Description The system analyzes information from a set of sensors that collect data from
the systemâs environment. Further information may also be collected on the
state of the actuators that are connected to the system. Based on the data
from the sensors and actuators, control signals are sent to the actuators that
then cause changes to the systemâs environment. Information about the
sensor values and the state of the actuators may be displayed.
Stimuli Values from sensors attached to the system and the state of the system
actuators.
Responses Control signals to actuators, display information.
Processes Monitor, Control, Display, Actuator Driver, Actuator monitor.
Used in Control systems.
04/12/2014 Chapter 21. Real-time Software Engineering 30
32. Control system architecture for an anti-skid
braking system
04/12/2014 Chapter 21. Real-time Software Engineering 32
33. The Process Pipeline pattern
Name Process Pipeline
Description A pipeline of processes is set up with data moving in
sequence from one end of the pipeline to another. The
processes are often linked by synchronized buffers to
allow the producer and consumer processes to run at
different speeds. The culmination of a pipeline may be
display or data storage or the pipeline may terminate in
an actuator.
Stimuli Input values from the environment or some other process
Responses Output values to the environment or a shared buffer
Processes Producer, Buffer, Consumer
Used in Data acquisition systems, multimedia systems
04/12/2014 Chapter 21. Real-time Software Engineering 33
37. Timing analysis
ī˛ The correctness of a real-time system depends not just
on the correctness of its outputs but also on the time at
which these outputs were produced.
ī˛ In a timing analysis, you calculate how often each
process in the system must be executed to ensure that
all inputs are processed and all system responses
produced in a timely way.
ī˛ The results of the timing analysis are used to decide how
frequently each process should execute and how these
processes should be scheduled by the real-time
operating system.
04/12/2014 Chapter 21. Real-time Software Engineering 37
38. Factors in timing analysis
ī˛ Deadlines
ī§ The times by which stimuli must be processed and some
response produced by the system.
ī˛ Frequency
ī§ The number of times per second that a process must execute so
that you are confident that it can always meet its deadlines.
ī˛ Execution time
ī§ The time required to process a stimulus and produce a
response.
04/12/2014 Chapter 21. Real-time Software Engineering 38
40. Power failure timings
ī˛ It takes 50 milliseconds (ms) for the supplied voltage to
drop to a level where the equipment may be damaged.
The battery backup must therefore be activated and in
operation within 50ms.
ī˛ It takes 16ms from starting the backup power supply to
the supply being fully operational.
ī˛ There is a checking process that is scheduled to run 250
times per second i.e. every 4ms.
ī§ This process assumes that there is a power supply problem if
there is a significant drop in voltage between readings and this is
sustained for 3 readings.
04/12/2014 Chapter 21. Real-time Software Engineering 40
41. Power failure timings
ī˛ Assume the power fails immediately after a reading has
been taken. Therefore reading R1 is the start reading for
the power fail check. The voltage continues to drop for
readings R2âR4, so a power failure is assumed. This is
the worst possible case.
ī˛ At this stage, the process to switch to the battery backup
is started. Because the battery backup takes 16ms to
become operational, this means that the worst-case
execution time for this process is 8ms.
04/12/2014 Chapter 21. Real-time Software Engineering 41
42. Timing requirements for the burglar alarm
system
Stimulus/Response Timing requirements
Audible alarm The audible alarm should be switched on within half a second of an
alarm being raised by a sensor.
Communications The call to the police should be started within 2 seconds of an alarm
being raised by a sensor.
Door alarm Each door alarm should be polled twice per second.
Lights switch The lights should be switched on within half a second of an alarm being
raised by a sensor.
Movement detector Each movement detector should be polled twice per second.
Power failure The switch to backup power must be completed within a deadline of 50
ms.
Voice synthesizer A synthesized message should be available within 2 seconds of an
alarm being raised by a sensor.
Window alarm Each window alarm should be polled twice per second.
04/12/2014 Chapter 21. Real-time Software Engineering 42
44. Stimuli to be processed
ī˛ Power failure is detected by observing a voltage drop of
more than 20%.
ī§ The required response is to switch the circuit to backup power by
signalling an electronic power-switching device that switches the
mains power to battery backup.
ī˛ Intruder alarm is a stimulus generated by one of the
system sensors.
ī§ The response to this stimulus is to compute the room number of
the active sensor, set up a call to the police, initiate the voice
synthesizer to manage the call, and switch on the audible
intruder alarm and building lights in the area.
04/12/2014 Chapter 21. Real-time Software Engineering 44
45. Frequency and execution time
ī˛ The deadline for detecting a change of state is 0.25
seconds, which means that each sensor has to be
checked 4 times per second. If you examine 1 sensor
during each process execution, then if there are N
sensors of a particular type, you must schedule the
process 4N times per second to ensure that all sensors
are checked within the deadline.
ī˛ If you examine 4 sensors, say, during each process
execution, then the execution time is increased to about
4 ms, but you need only run the process N times/second
to meet the timing requirement.
04/12/2014 Chapter 21. Real-time Software Engineering 45
47. Real-time operating systems
ī˛ Real-time operating systems are specialised operating
systems which manage the processes in the RTS.
ī˛ Responsible for process management and
resource (processor and memory) allocation.
ī˛ May be based on a standard kernel which
is used unchanged or modified for a particular
application.
ī˛ Do not normally include facilities such as file
management.
04/12/2014 Chapter 21. Real-time Software Engineering 47
48. Operating system components
ī˛ Real-time clock
ī§ Provides information for process scheduling.
ī˛ Interrupt handler
ī§ Manages aperiodic requests for service.
ī˛ Scheduler
ī§ Chooses the next process to be run.
ī˛ Resource manager
ī§ Allocates memory and processor resources.
ī˛ Dispatcher
ī§ Starts process execution.
04/12/2014 Chapter 21. Real-time Software Engineering 48
49. Non-stop system components
ī˛ Configuration manager
ī§ Responsible for the dynamic reconfiguration of the system
software and hardware. Hardware modules may be replaced and
software upgraded without stopping the systems.
ī˛ Fault manager
ī§ Responsible for detecting software and hardware faults and
taking appropriate actions (e.g. switching to backup disks) to
ensure that the system continues in operation.
04/12/2014 Chapter 21. Real-time Software Engineering 49
50. Components of a real-time operating system
04/12/2014 Chapter 21. Real-time Software Engineering 50
51. Process management
ī˛ Concerned with managing the set of concurrent
processes.
ī˛ Periodic processes are executed at pre-specified time
intervals.
ī˛ The RTOS uses the real-time clock to determine when to
execute a process taking into account:
ī§ Process period - time between executions.
ī§ Process deadline - the time by which processing must be
complete.
04/12/2014 Chapter 21. Real-time Software Engineering 51
52. Process management
ī˛ The processing of some types of stimuli must
sometimes take priority.
ī˛ Interrupt level priority. Highest priority which is
allocated to processes requiring a very fast
response.
ī˛ Clock level priority. Allocated to periodic
processes.
ī˛ Within these, further levels of priority may be
assigned.
04/12/2014 Chapter 21. Real-time Software Engineering 52
53. Interrupt servicing
ī˛ Control is transferred automatically to a
pre-determined memory location.
ī˛ This location contains an instruction to jump to
an interrupt service routine.
ī˛ Further interrupts are disabled, the interrupt
serviced and control returned to the interrupted
process.
ī˛ Interrupt service routines MUST be short,
simple and fast.
04/12/2014 Chapter 21. Real-time Software Engineering 53
54. Periodic process servicing
ī˛ In most real-time systems, there will be several
classes of periodic process, each with different
periods (the time between executions),
execution times and deadlines (the time by
which processing must be completed).
ī˛ The real-time clock ticks periodically and each
tick causes an interrupt which schedules the
process manager for periodic processes.
ī˛ The process manager selects a process which
is ready for execution.
04/12/2014 Chapter 21. Real-time Software Engineering 54
55. RTOS actions required to start a process
04/12/2014 Chapter 21. Real-time Software Engineering 55
56. Process switching
ī˛ The scheduler chooses the next process to be executed
by the processor. This depends on a scheduling strategy
which may take the process priority into account.
ī˛ The resource manager allocates memory and a
processor for the process to be executed.
ī˛ The dispatcher takes the process from ready list, loads it
onto a processor and starts execution.
04/12/2014 Chapter 21. Real-time Software Engineering 56
57. Scheduling strategies
ī˛ Non pre-emptive scheduling
ī§ Once a process has been scheduled for execution, it runs to
completion or until it is blocked for some reason (e.g. waiting for
I/O).
ī˛ Pre-emptive scheduling
ī§ The execution of an executing processes may be stopped if a
higher priority process requires service.
ī˛ Scheduling algorithms
ī§ Round-robin;
ī§ Rate monotonic;
ī§ Shortest deadline first.
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58. Key points
ī˛ An embedded software system is part of a hardware/software
system that reacts to events in its environment. The software is
âembeddedâ in the hardware. Embedded systems are normally real-
time systems.
ī˛ A real-time system is a software system that must respond to events
in real time. System correctness does not just depend on the results
it produces, but also on the time when these results are produced.
ī˛ Real-time systems are usually implemented as a set of
communicating processes that react to stimuli to produce
responses.
ī˛ State models are an important design representation for embedded
real-time systems. They are used to show how the system reacts to
its environment as events trigger changes of state in the system.
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59. Key points
ī˛ There are several standard patterns that can be observed in
different types of embedded system. These include a pattern for
monitoring the systemâs environment for adverse events, a pattern
for actuator control and a data-processing pattern.
ī˛ Designers of real-time systems have to do a timing analysis, which
is driven by the deadlines for processing and responding to stimuli.
They have to decide how often each process in the system should
run and the expected and worst-case execution time for processes.
ī˛ A real-time operating system is responsible for process and
resource management. It always includes a scheduler, which is the
component responsible for deciding which process should be
scheduled for execution.
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