Analysis of a Time-driven Chain of Dependent Components

April 19, 2023 Alina Weffers-Albu, [email protected]

TU/e Computer Science, System Architecture and NetworkingPhilips Research Laboratories Eindhoven

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Analysis of a Time-driven Chain of Dependent Components

M.A. Weffers-Albu, J.J. Lukkien, P.D.V. v.d. Stok



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Contents

• Goal & Approach

• Analyzed Systems

• Characterization of behavior

• QoS Requirement. First solution

• Stable Phase Theory

• Practical Applications

• Future work



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Goal & Approach

The goal of our work is the prediction and optimization of performance parameters to provide guaranteed and optimized Quality of Service (QoS) for real-time streaming applications.

Approach: provide a characterization of streaming applications execution to determine performance parameters and provide insight into best design practices for optimising these attributes.

Performance parameters: • Response Time of tasks and chain (RT), • Resource utilization (RU) for CPU, memory.• Number of Context Switches (NCS)



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Physical Platform

…

Media Processing Applications



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Physical Platform

…




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Physical Platform

…




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Physical Platform

…


eqi?

fqi-1? fqi!

eqi-1!

Component

Processing code(ci)

Get Full Packet Put Full Packet

Put Empty Packet Get Empty Packet

eq2 eqN-1

fq1

eq1

fqN-1C1

C2 CN

fq2…



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Characterization of chain behaviour

Express behavior as: • traces, • time assignment (schedule) associated with each trace

schedule consistent traces

arbitrary interleavings

channel consistent traces

priority consistent traces

Impose

predicates

until

obtain

trace and schedule

that specify

the system behavior.

Unique trace ρ, eager schedule eager



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QoS Requirement

QoS Requirement – CN executes always strictly at rate TN.

First step solution - rate of production higher than rate of consumption for packets in fqN-1:

PRkN-1

. TN, k N

First step solution non-optimal, pessimistic – implies sum of max computation times of components actions must be smaller than TN.



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Stable Phase Theorem

Stable Phase Theorem - Provided that PRkN-1

. TN , k N, the pipeline system assumes a repetitive, periodic behavior after a finite initial phase.The complete behavior is characterized the unique trace:

ρ = tinit (inc(i) fqN-1? eqN? cN eqN-1! tL fqN ! d(i *TN)) ω.

tinit – trace recording the initial phase of the system execution.

tstable– stable phase: (inc(i) fqN-1? eqN? cN eqN-1! tL fqN ! d(i *TN)) ω

tL – subtrace recording the interleaved execution of C1..CN-1.

Execution in cascade of sub-chain

- all backward queues empty.

…C1 CN



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Stable Phase Theorem

Stable Phase Theorem - Provided that PRkN-1

. TN , k N, the pipeline system assumes a repetitive, periodic behavior after a finite initial phase.The complete behavior is characterized the unique trace:

ρ = tinit (inc(i) fqN-1? eqN? cN eqN-1! tL fqN ! d(i *TN)) ω.

tinit – trace recording the initial phase of the system execution.

tstable– stable phase: (inc(i) fqN-1? eqN? cN eqN-1! tL fqN ! d(i *TN)) ω

tL – subtrace recording the interleaved execution of C1..CN-1.

…

tinit

idle time idle time idle time

TN



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Practical applications

Given the computation times of components actions, ρ and eager can be calculated at design time.

• Hence NCS, task and chain RT, RU for CPU and memory can also be calculated.

• Minimum Queue Capacity: 1

• Minimum NCS at Stable Phase: P(C1)<…<P(CN-1) Cap(fqi) = 2 for all i, 1 i < N−1.

• Chain RT cannot be optimized

• CN has the same influence as a minimum priority data-driven component.



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On-going work

• Optimal solution for satisfying QoS requirement

• Study chains containing a time driven component at each end (realistic surveillance application)

• Study chains that include video/audio decoding components, execution depends on input stream(realistic video/audio decoding chains).

Documents

Analysis of a Time-driven Chain of Dependent Components