Functional Parameter & Scheduling Hierarchy | Real Time System
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This document discusses functional parameters and scheduling hierarchy for real-time systems. It describes key parameters like preemptivity and criticality of jobs, optional executions, and laxity types. It also discusses parameters of resources like preemptivity and the resource graph. The scheduling hierarchy involves a task graph, resource graph, and scheduling algorithms. The scheduler implements algorithms to schedule jobs and allocate resources according to precedence, timing, and resource constraints to produce a valid schedule if the job set is feasible. Performance is measured by metrics like lateness and miss rates.
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Real Time Systems
1. Real-time systems are systems where the correctness depends on both the logical result and the time at which the results are produced.
2. Real-time systems have performance deadlines where computations and actions must be completed. Deadlines can be time-driven or event-driven.
3. Real-time systems are classified as hard, firm, or soft depending on how critical meeting deadlines are. They are used in applications like medical equipment, automotive systems, and avionics.
Reference model of real time system
This document provides an overview of a reference model for real-time systems. It describes the key components of the model including the workload model (tasks and jobs), resource model (processors and resources), and scheduling algorithms. It defines temporal parameters for jobs, periodic and sporadic task models, and different types of dependencies. It also covers functional parameters, resource requirements, and defines concepts like feasibility and optimality for schedules. The goal is to characterize real-time systems and provide a framework for analyzing scheduling and resource allocation algorithms.
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Real time system
Real time systems must produce correct responses within defined time limits. Failure to do so can result in system degradation or malfunction. Real time systems are categorized based on their deadline requirements as hard, firm, or soft. Hard systems must meet deadlines or fail, while soft systems can tolerate missed deadlines with degraded performance. Real time systems are used in critical applications like aircraft control systems, medical equipment, traffic control and more. They interact with the physical world through sensors and actuators and require real time operating systems to ensure timing constraints are met.
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The document provides an overview of the Software Engineering course for the second semester of the second year (B.Tech IT/II Sem-II). It includes details about the term, text books, unit syllabus, index of topics, and slides covering introductions to software engineering, the changing nature of software, software myths, generic views of process, the Capability Maturity Model Integration and personal and team software processes.
Sara Afshar: Scheduling and Resource Sharing in Multiprocessor Real-Time Systems
PhD Candidate,
Department of Computer science
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Time: Tuesday, Dec. 30, 2014, 11:30 a.m.
Location: Computer Engineering Department, Urmia University
Abstract:
The processor is the brain of a computer system. Usually, one or more programs run on a processor where each program is typically responsible for performing a particular task or function of the system. The performance of all the tasks together results in the system functionality. In many computer systems, it is not only enough that all tasks deliver correct output, but it is also crucial that these activities are delivered in a proper time. This type of systems that have timing requirements are known as real-time systems. A scheduler is responsible for scheduling all tasks on the processor, i.e., it dictates which task to run and when to run to ensure that all tasks are carried out on time. Typically, such tasks/programs need to use the computer system’s hardware and software resources to perform their calculation. Examples of such type of resources that are shared among programs are I/O devices, buffers and memories. Technology that is used for the management of shared resources is known as resource sharing synchronization protocol.
In recent years, a shift from single-processor platforms to multiprocessor platforms has become inevitable due to availability of processor chips and requirements on increased performance. Scheduling and resource sharing protocols have been well studied for uniprocessor systems. However, in the context of multiprocessors, still such techniques are not fully mature. The shift towards multi-core technology has revealed the demand for real-time scheduling algorithms along with synchronization protocols to support real-time applications on multiprocessors, both with and without dependencies.
In this talk, we first have an introduction to real-time embedded systems. Next, we look at scheduling and resource sharing policies in uniprocessor platforms. Further, we discuss the extension of scheduling and resource sharing policies for multiprocessor platforms and present the recent challenges arisen in this context.
Biography:
Sara Afshar is a PhD student at Mälardalen University. She has received her B.Sc. degree in Electrical Engineering from Tabriz University, Iran in 2002. She worked at different engineering companies until 2009. In the year 2010 she started her M.Sc. in Embedded Systems at Mälardalen University. She obtained her Master degree in 2012 and at the same year she started her PhD studies in Mälardalen University. Currently she is working on the topic of resource sharing in multiprocessor systems. She is part of the Complex Real-Time Embedded Systems group at Mälardalen University.
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Real Time Systems
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2. Real-time systems have performance deadlines where computations and actions must be completed. Deadlines can be time-driven or event-driven.
3. Real-time systems are classified as hard, firm, or soft depending on how critical meeting deadlines are. They are used in applications like medical equipment, automotive systems, and avionics.
Reference model of real time system
This document provides an overview of a reference model for real-time systems. It describes the key components of the model including the workload model (tasks and jobs), resource model (processors and resources), and scheduling algorithms. It defines temporal parameters for jobs, periodic and sporadic task models, and different types of dependencies. It also covers functional parameters, resource requirements, and defines concepts like feasibility and optimality for schedules. The goal is to characterize real-time systems and provide a framework for analyzing scheduling and resource allocation algorithms.
Clock driven scheduling
The document discusses clock-driven scheduling for real-time systems. It covers key concepts like static schedules, cyclic executives, frame size constraints, job slicing, and algorithms for constructing static schedules. Notations are introduced to represent periodic tasks, and assumptions made for clock-driven scheduling are explained. Methods to improve the average response time of aperiodic jobs through slack stealing are also summarized.
Real time system
Real time systems must produce correct responses within defined time limits. Failure to do so can result in system degradation or malfunction. Real time systems are categorized based on their deadline requirements as hard, firm, or soft. Hard systems must meet deadlines or fail, while soft systems can tolerate missed deadlines with degraded performance. Real time systems are used in critical applications like aircraft control systems, medical equipment, traffic control and more. They interact with the physical world through sensors and actuators and require real time operating systems to ensure timing constraints are met.
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The document provides an overview of the Software Engineering course for the second semester of the second year (B.Tech IT/II Sem-II). It includes details about the term, text books, unit syllabus, index of topics, and slides covering introductions to software engineering, the changing nature of software, software myths, generic views of process, the Capability Maturity Model Integration and personal and team software processes.
Sara Afshar: Scheduling and Resource Sharing in Multiprocessor Real-Time Systems
PhD Candidate,
Department of Computer science
Mälardalen University
Time: Tuesday, Dec. 30, 2014, 11:30 a.m.
Location: Computer Engineering Department, Urmia University
Abstract:
The processor is the brain of a computer system. Usually, one or more programs run on a processor where each program is typically responsible for performing a particular task or function of the system. The performance of all the tasks together results in the system functionality. In many computer systems, it is not only enough that all tasks deliver correct output, but it is also crucial that these activities are delivered in a proper time. This type of systems that have timing requirements are known as real-time systems. A scheduler is responsible for scheduling all tasks on the processor, i.e., it dictates which task to run and when to run to ensure that all tasks are carried out on time. Typically, such tasks/programs need to use the computer system’s hardware and software resources to perform their calculation. Examples of such type of resources that are shared among programs are I/O devices, buffers and memories. Technology that is used for the management of shared resources is known as resource sharing synchronization protocol.
In recent years, a shift from single-processor platforms to multiprocessor platforms has become inevitable due to availability of processor chips and requirements on increased performance. Scheduling and resource sharing protocols have been well studied for uniprocessor systems. However, in the context of multiprocessors, still such techniques are not fully mature. The shift towards multi-core technology has revealed the demand for real-time scheduling algorithms along with synchronization protocols to support real-time applications on multiprocessors, both with and without dependencies.
In this talk, we first have an introduction to real-time embedded systems. Next, we look at scheduling and resource sharing policies in uniprocessor platforms. Further, we discuss the extension of scheduling and resource sharing policies for multiprocessor platforms and present the recent challenges arisen in this context.
Biography:
Sara Afshar is a PhD student at Mälardalen University. She has received her B.Sc. degree in Electrical Engineering from Tabriz University, Iran in 2002. She worked at different engineering companies until 2009. In the year 2010 she started her M.Sc. in Embedded Systems at Mälardalen University. She obtained her Master degree in 2012 and at the same year she started her PhD studies in Mälardalen University. Currently she is working on the topic of resource sharing in multiprocessor systems. She is part of the Complex Real-Time Embedded Systems group at Mälardalen University.
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This document discusses real-time scheduling algorithms. It begins by defining real-time systems and their key properties of timeliness and predictability. It then discusses two common real-time scheduling algorithms: fixed-priority Rate Monotonic scheduling and dynamic-priority Earliest Deadline First scheduling. It covers how each algorithm prioritizes and orders tasks, and analyzes their schedulability and utilization bounds. It concludes by comparing the two approaches.
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Project managers tend to define various tasks, and project milestones and they arrange them keeping various factors in mind.
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Evaluation of results of all work product reviews
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- 1. Functional Parameter &Scheduling Hierarchy BY Aananda Bhandari Shubham Ghimire 1
- 2. Functonal Parameter • Preemptivity Of Jobs • Criticality Of Jobs • Optional Execution • Laxity Type And Laxity Function 2
- 3. Preemptivity Of Jobs • Preemptable Job :- Can be suspended and resumed from the suspention point • Example :- Computations • Non-preemptable :- Data transmission 3
- 4. Criticality Of Jobs • Criticality of job :- Positive number indicating how critical the job is. • Increases with importance of job • Don’t use the terms priority and weight 4
- 5. Optional Executions • If an optional job or optional portion completes late or is not executed at all, the system still functions satisfactorily. • Non-optional job :- Mandatory 5
- 6. Laxity Type & Laxity Functions • Laxity type:- indicates whether the job is hard or soft. • Hard RT Jobs:- “Better never than late”. • Soft RT Jobs:- Usefulness decreases gradually. 6
- 7. Resource Parameters Of Jobs & Parameters Of Job Resources • Preemptivity Of Resources • Resource Graph 7
- 8. Preemptivity Of Resources • Describing processors and resources independently of application Parameter of resources: Preemptivity. • Nonpreemptable resource: Each unit is to be used serially. 8
- 9. Resource Graph • Configuration of the resources • Vertex Ri for every processor or resource Ri in the system. • Attributes of the vertex are the parameters of the resource. • P- processors, R- for passive resources • Parameters – Type – Number of available units. 9
- 11. Scheduling Hierarchy • Task Graph – Representation of application system. – Processor time – Resource requirement – Timing constraints & dependencies of jobs • Resource Graph – Amount of available resources – Resource attributes – Usage rules • Scheduling and resource access-control algorithms used by the operating system. 11
- 12. Scheduler & Schedules • Scheduler: – implements scheduling algorithms –Schedules Jobs, –Allocates Resources. Example: Processors assignment on jobs (or vice versa). • Schedule: Assignment of all system jobs on available processors produced by the scheduler. 12
- 13. Valid Schedule • Every processor assigned to at most one job at any time • Every job is assigned at most one processor at any time. • No job is scheduled before its release-time. • Total amount of processor time = execution time • Precedence and resource usage constraints are satisfied. 13
- 14. Feasibility, Optimality & Performance Measures • valid schedule is a feasible schedule if every job completes by its deadline. • Hard RTS scheduling algorithm is optimal if (using) the algorithm (the scheduler) always produces a feasible schedule if the given set of jobs has feasible schedules. • Lateness, tardiness, miss ,loss and invalid rates. 14
- 15. Thank You 15 Reference : Real-Time Systems , Jane W. S. Liu