On Static WCET Analysis Vs. Runtime Monitoring of Execution Time

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On Static WCET Analysis Vs. Run-time Monitoring
of Execution Time

• Charles D. Cavanaugh, Ph.D.
• The Center for Advanced Computer Studies
• University of Louisiana at Lafayette

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Introduction

• Safety critical and mission critical software
• Input, process, output
• Ex. Air-traffic control
• Workload varies dynamically
• Can allocate resource for maximum expected input
  size
• Questions regarding resource allocation
• How to process more tracks than anticipated?
• How to get better utilization?

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Example

• Air traffic control display subsystem
• R-T display of radar, correlated data

Displays
DANGER
F100 07 250 180
F100 07 250 180
747 29 400 270
747 29 400 270
S80 07 200 000
S80 07 200 000
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Overview

• Model and approach
• Diagnosis algorithm
• Conclusions and future work

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System Model and Approach

• Path d.a.g. of connected programs, Pi
• Computational subpath executing program ai,j,k
• Communication subpath connection between two
  programs (ai,j,k, ai,j1,k)

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System Model and Approach

• Observed time path or subpaths operating time
  ?OBS(Pi, c)
• Required time specified bound on time ?REQ(Pi)
• Profiled time mean execution or communication
  time with no other apps running or communicating
• CPROF(ai,j,k, Pi.DS(ai,j,k, c), HOST(ai,j,k))
• CMPROF(ai,j,k, ai,j1,k, Pi.DS(ai,j,k, ai,j1,k,
  c), COMMPATH(ai,j,k, ai,j1,k))
• May vary dynamically with workload

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System Model and Approach

• Poor health path or subpaths operating time
  exceeding specified bounds
• ?OBS(Pi, c) exceeds ?REQ(Pi) because subpath
  latencies ?OBS(ai,j,k, c) and ?OBS(ai,j,k,
  ai,j1,k, c) sum to more than ?REQ(Pi)
• Quality of service operating time falling
  within specified bounds

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System Model and Approach

• Workload amount of data a path or subpath
  processes
• Queueing delay or contention time delay caused
  by other programs executing or communicating
• Difference between observed time and profiled
  time without contention

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Diagnosis Algorithm

• Monitors computational and communication subpaths
• Identifies unhealthy subpaths
• Distinguishes the cause of poor health
• Recommends actions to improve health

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Example

• Table 2. Example latency, profiled time, queuing
  delay

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Example
Table 3. Example latency, profiled time, queuing
delay
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Conclusions and Future Work

• System model
• Observed time
• Profiled time
• Contention
• Examples
• Diagnosis algorithm
• Future work
• Incorporate into ATC simulator
• Enhance profiling accuracy

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Diagnosis Algorithm

• (1) IF observed time gt required time THEN
• (2) IF paths maximum slack lt 0 THEN
• (3) LET s subpath having the least
  maximum slack.
• (4) IF s is a compuational subpath
  THEN
• (5) IF s is scalable THEN LET
  action copy s ELSE LET action move s.
• (6) IF s is a communication subpath
  THEN
• (7) LET action combine
  endpoints of s.

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Diagnosis Algorithm

• (8) ELSE IF paths queuing delay gt paths
  maximum slack THEN
• (9) LET s subpath having the least
  maximum slack or the greatest queuing delay.
• (10) IF s is a compuational subpath THEN
• (11) IF s has the greatest queuing delay THEN LET
  action move s.
• (14) IF s is a communication subpath
  THEN LET action combine endpoints of s.