Commonly used Approaches to Real Time Scheduling

Commonly used Approaches to real
time scheduling
-Shrey Dahal
-Bipin karki
-Shekhar Koirala
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Contents
• Clock Driven Approach
• Weighted Round Robin Approach
• Priority Driven Approach
• Dynamic vs Static System
• Effective Release Time And Deadline
• Optimality and Non-eptimality of EDF and LST algorithm
• Anomalous Behavior of Priority-Driven System
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Clock Driven Approach
• Also called time-driven approach . Decisions about what jobs execute are chosen
before the system begins execution.
• Parameters of the real-time jobs are fixed and known.
• Schedule of the jobs is computed off-line and is stored for use at runtime.
• Cannot handle aperiodic and sporadic task since such task cannot be predicted.
• Example: the helicopter example with an interrupt every 1/180thof a second
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Weighted Round Robin
• It is Commonly used for scheduling the time shared applications.
• Jobs Join FIFO queue when becomes ready for execution.
• Each job in the queue executes for one time slice.
• If there are n jobs, then each job gets 1/n share of processor.
• Example : Jobs communicating using Unix pipes
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Priority Driven
• It refers to large class of scheduling algorithm that never leave any resource idle intentionally.
• Jobs are placed in one or more queues ;at each event the ready job with highest priority is
executed.
• Also called event-driven approach.
• Computation is done online without knowing the knowledge of job that will be released in
future.
• Algorithm used in non-real time system:
– Priority driven, FIFO:-assign priority based on release time
– Shortest Execution Time First , Longest Execution Time First:-assign priority based on
execution time
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Priority Driven
• Algorithm used in Real Time System:
–Earliest deadline first
–Least slack time first
• Assign priority based on deadline or some timing constriants.
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EDF AND LST
• Earliest deadline first Least Slack time
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• Assign priority to jobs based on
deadline
• Earlier the deadline, higher the priority
• the schedulability test for EDF is:
where the ei are the worst-case
computation-times of the n processes and
the Pi are their respective inter-arrival
periods.
• Assign priority to jobs based on slack time(tslack)
• Calculate Slack:
t_rem = exe_time - (time – relese_time)
t_slack = deadline - time - trem
• Smaller the slack time, the higher the priority

Example:EDF
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(r1, d1, e1) = (0, 10, 3), (r2, d2, e2) = (2, 14, 6), (r3, d3, e3) = (4, 12, 4).

Static vs Dynamic System
Static System
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• S Dynamic System
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• Jobs are partitioned into subsystems, and
each subsystem is bound statically to a
processor.
• Jobs can be moved among system.
• Jobs are scheduled on multiple processors,
and a job can be dispatched from the
priority run queue to any of the processors.
• Jobs is migratable.

Optimality and Non-optimality of EDF and LST
algorithm
• OPTIMALITY:
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• they will always produce a feasible schedule if one exists.
• Constraints: on a single processor, as long as preemption is allowed and jobs do not contend for resources.
• THEOREM:
• When preemption is allowed and jobs do not contend for resources, the EDF and LST algorithms can
produce a feasible schedule of a set J of jobs with arbitrary release times and deadlines on a processor if
and only if J has feasible schedules.

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Proof:
To show the optimality of EDF, we have to require to show any feasible schedule can be transformed into
another EDF schedule.
If J i is scheduled to execute before J k, but J i’s deadline is later than J k’s such that there exist two
conditions:
– The release time of J k is after the J i completes that means they’re already in EDF order.
– The release time of J k is before the end of the interval in which J i executes.
This is always possible to swap J i and J k since J i’s deadline is later than J k’s such that

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We can move any jobs following idle periods forward into the idle period then
the result is an EDF schedule
When deadline of J i’s is earlier than J k’s there is no possibility to generate the other feasible
schedule and EDF failed to produce a feasible schedule. Hence the optimality of EDF is
verified .

Non-Optimality
• Neither algorithm is optimal if jobs are non- preemptable or if
there is more than one processor
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Non-optimality of EDF and LST
• EDF and LST algorithms are not optimal if preemption is not allowed or
there is more than one processor. consider j1(0,3,10),j2(2,6,14),j3(4,4,12).
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Consider we have two processors and three jobs J1, J2, J3, with execution
times 1, 1, 5 and deadlines 1, 2, 5 respectively. All with release time 0.

Effective Release Time and Deadline
• Effective release time:-
-The effective release time of a job with predecessor is equal to the maximum value
among its given release time and the effective release times of all of its predecessors.
• Effective Deadline:-
- The effective deadline of a job with successors is equal to the minimum value
among its given deadline and the effective deadline of all of its successors.
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Validating Priority-Driven Scheduling
• Priority-driven scheduling has many advantages over clock-driven scheduling:
• Scheduling anomalies can occur for multiprocessor or non-preemptable systems,
or those which share resources.
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• Easy to implement.
• Often have simple priority assignment rule,due to which run-time overhead of maintaining
queue can be small.
• Does not require information about deadline and release times in advance so it is uited to
application with varing time and resource requirement.

Anomalous Behavior of Priority-Driven Systems
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Commonly used Approaches to Real Time Scheduling

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