1. 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

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

3. S80 07 200 000 F100 07 250 180 747 29 400 270Example Air traffic control display subsystem Air traffic control display subsystem R-T display of radar, correlated data R-T display of radar, correlated data 747 29 400 270 S80 07 200 000 F100 07 250 180 747 29 400 270 S80 07 200 000 F100 07 250 180 DANGER Filtering Decision Making Radar Displays

5. Overview Model and approach Model and approach Diagnosis algorithm Diagnosis algorithm Conclusions and future work Conclusions and future work

6. System Model and Approach Path – d.a.g. of connected programs, P i Path – d.a.g. of connected programs, P i Computational subpath – executing program a i,j,k Computational subpath – executing program a i,j,k Communication subpath – connection between two programs (a i,j,k, a i,j+1,k ) Communication subpath – connection between two programs (a i,j,k, a i,j+1,k )

7. System Model and Approach Observed time – path or subpath’s operating time OBS (P i, c) Observed time – path or subpath’s operating time OBS (P i, c) Required time – specified bound on time REQ (P i ) Required time – specified bound on time REQ (P i ) Profiled time – mean execution or communication time with no other apps running or communicating Profiled time – mean execution or communication time with no other apps running or communicating –C PROF (a i,j,k, |P i.DS(a i,j,k, c)|, HOST(a i,j,k )) –CM PROF (a i,j,k, a i,j+1,k, |P i.DS(a i,j,k, a i,j+1,k, c)|, COMMPATH(a i,j,k, a i,j+1,k )) –May vary dynamically with workload

8. System Model and Approach Poor health – path or subpath’s operating time exceeding specified bounds Poor health – path or subpath’s operating time exceeding specified bounds – OBS (P i, c) exceeds REQ (P i ) because subpath latencies OBS (a i,j,k, c) and OBS (a i,j,k, a i,j+1,k, c) sum to more than REQ (P i ) Quality of service – operating time falling within specified bounds Quality of service – operating time falling within specified bounds

9. System Model and Approach Workload – amount of data a path or subpath processes Workload – amount of data a path or subpath processes Queueing delay or contention – time delay caused by other programs executing or communicating Queueing delay or contention – time delay caused by other programs executing or communicating –Difference between observed time and profiled time without contention

10. Diagnosis Algorithm Monitors computational and communication subpaths Monitors computational and communication subpaths Identifies unhealthy subpaths Identifies unhealthy subpaths Distinguishes the cause of poor health Distinguishes the cause of poor health Recommends actions to improve health Recommends actions to improve health

11. Example Component OBS C PROF |CM PROF |CCM TO T QD OBS P1.2sCCM TOT =0.8s0.4s F0.5sC PROF =0.4s0.1s (F,ED)0.5sCM PROF =0.3s0.2s ED0.2sC PROF =0.1s0.1s Table 2. Example latency, profiled time, queuing delay Sensor Filter Evaluate & Decide Sensor Device Filter Manager Comp. Subpath Comm. Subpath Sensing Path

12. Example Table 3. Example latency, profiled time, queuing delay Component OBS C PROF |CM PROF |CCM TOT QD OBS REQ  MAX P1.2sCCM TOT =1.1s0.1s1.0s–0.1s F0.4sC PROF =0.36s0.04s0.327s0.327s–0.36s=–0.033s (F,ED)0.4sCM PROF =0.38s0.02s0.3450.345s–0.38s=–0.035s ED0.4sC PROF =0.36s0.04s0.327s0.327s–0.36s=–0.033s Sensor Filter Evaluate & Decide Sensor Device Filter Manager Comp. Subpath Comm. Subpath Sensing Path

13. Conclusions and Future Work System model System model –Observed time –Profiled time –Contention Examples Examples Diagnosis algorithm Diagnosis algorithm Future work Future work –Incorporate into ATC simulator –Enhance profiling accuracy

14. Diagnosis Algorithm (1) IF observed time > required time THEN (1) IF observed time > required time THEN (2) IF path’s maximum slack < 0 THEN (2) IF path’s maximum slack < 0 THEN (3) LET s = subpath having the least maximum slack. (3) LET s = subpath having the least maximum slack. (4) IF s is a compuational subpath THEN (4) IF s is a compuational subpath THEN (5) IF s is scalable THEN LET action = copy s ELSE LET action = move s. (5) IF s is scalable THEN LET action = copy s ELSE LET action = move s. (6) IF s is a communication subpath THEN (6) IF s is a communication subpath THEN (7) LET action = combine endpoints of s. (7) LET action = combine endpoints of s.

15. Diagnosis Algorithm (8) ELSE IF path’s queuing delay > path’s maximum slack THEN (8) ELSE IF path’s queuing delay > path’s maximum slack THEN (9) LET s = subpath having the least maximum slack or the greatest queuing delay. (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.