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Resource Management for Real-Time Environments Instructor: Dr. Subra Ganesan Presented by: Pooja Mehta Date: 10/16/06.

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Presentation on theme: "Resource Management for Real-Time Environments Instructor: Dr. Subra Ganesan Presented by: Pooja Mehta Date: 10/16/06."— Presentation transcript:

1 Resource Management for Real-Time Environments Instructor: Dr. Subra Ganesan Presented by: Pooja Mehta Date: 10/16/06

2 Presentation outline Motivation Problem illustrations of Radar systems –Basic Radar model –Tasks with Harmonic Periods –Offline Template Generation –Schedule construction on Hyperperiod Some Proposed Solutions –Feasible Intervals –Online Template Generation –Finite Horizon Scheduling Conclusions

3 Motivation The traditional notion of real-time systems 0T1T1 2T 1 3T 1 0T2T2 2T 2 3T 2 4T 2 TASK 1 TASK 2 Periodic tasksKnown periodsKnown execution timesKnown deadlines However, many important applications lack this simple structure However, many important applications lack this simple structure Complexity arises because of Complexity arises because of –Stringent task requirements –Scale of systems

4 Presentation outline Motivation Problem illustrations of Radar systems –Basic Radar model –Tasks with Harmonic Periods –Offline Template Generation –Schedule construction on Hyperperiod Some Proposed Solutions –Feasible Intervals –Online Template Generation –Finite Horizon Scheduling Conclusions

5 Basic Radar Model A i : Transmit Power t xi : Transmit pulse width t wi : Wait time t ri : Receive time Radar System Model

6 Processing requirements for radar tasks Signals received at the antenna need to be processed (backend computations) –At multiple stages –Within an end-to-end deadline FILTERINGCLASSIFICATION COMMAND GENERATION End-to-end deadline Execution requirements on each node

7 Radar dwell scheduling N th job (N+1) th job Illumination window Last illumination time Temporal distance Processing window

8 Radar dwell scheduling Non-preemptible Reusable Radar dwell Question: How do we schedule many such tasks? Constraints on power Dwell packing Power (kw) t P(t)

9 Template-based Schedule

10 Q-RAM & Scheduler Admission Control Reduce the resource utilization bounds Changes at irregular intervals

11 Offline Template Generation

12 task types were restricted to a finite set appropriate templates were chosen during online operation Resource managers could only pick task types from the finite set.

13 Presentation outline Motivation Problem illustrations of Radar systems –Basic Radar model –Tasks with Harmonic Periods –Offline Template Generation –Schedule construction on Hyperperiod Some Proposed Solutions –Feasible Intervals –Online Template Generation –Finite Horizon Scheduling Conclusions

14 Dynamic Q-RAM Optimization

15 Online Template Generation Arbitrary tasks can be interleaved or nested on-the-fly.

16 Online Template Generation arbitrary task types can be combined on-the-fly to produce a template; provides greater freedom to a resource manager. The resource manager can tune the parameters of each task with finer granularity. Online template generation is carried out using a fast heuristic based on task characteristics.

17

18 Resource management framework

19 Radar dwell scheduling – issues Non-preemptible Constraints on power Dwell packing Temporal distance constraints

20 Dwell scheduling – solutions Fixed length templates for packing dwells Heuristics for building templates Template length divides the smallest period Temporal distance Synthetic period Feasible intervals

21 Modular Schedule Updates Without modular schedule update With modular schedule update

22 Constraints Temporal Constraints When new tasks are admitted, the schedule changes only within the templates in which new jobs are inserted. Energy Constraints Since a job is inserted into a template only if it will not cause the energy level to exceed ETH, and since job insertions assume that the energy level at the start of a template is ETH, job insertions are guaranteed to be safe in terms of the energy constraint. Since a job is inserted into a template only if it will not cause the energy level to exceed ETH, and since job insertions assume that the energy level at the start of a template is ETH, job insertions are guaranteed to be safe in terms of the energy constraint.

23 Dealing with the energy constraint Cooldown time E TH Cool-down duration for Dwell A Cool-down duration for Dwell B L

24 Finite horizon scheduling AAAAA T T+H Task B arrives; is rejected Task A departs Feasible intervals for Task B Task B need not have been rejected horizon

25 Scheduling overhead

26 Reduced task rejection rates

27 Utilization improvement Maximum achievable with energy bound

28 Presentation outline Motivation Problem illustrations of Radar systems –Basic Radar model –Tasks with Harmonic Periods –Offline Template Generation –Schedule construction on Hyperperiod Some Proposed Solutions –Feasible Intervals –Online Template Generation –Finite Horizon Scheduling Conclusions

29 Conclusions All Real time systems doesn’t follow Ideal model Determination of Schedulability Regions Knowing the Schedule not just the schedulability Systems should be able to handle unseen tasks, without violating the Temporal and Energy constraints

30 References [1] C.-S. Shih, S. Gopalakrishnan, P. Ganti, M. Caccamo, L. Sha: “Template- based real-time dwell scheduling with energy constraint,” IEEE Real-Time Technology and Applications Symposium, Washington D.C., USA, May 2003. [2] C.-S. Shih, S. Gopalakrishnan, P. Ganti, M. Caccamo, L.Sha: “Scheduling real-time dwells using tasks withsynthetic periods,” IEEE Real-Time Systems Symposium, Cancun, Mexico, December 2003. [3] C.-G. Lee, P.-S. Kang, C.-S. Shih, L. Sha: “Radar dwell scheduling considering physical characteristics of phased array antenna,” IEEE Real- Time Systems Symposium,Cancun, Mexico, December 2003. [4] J. Hansen, S. Ghosh, R. Rajkumar, J. Lehoczky: “Resource management of highly configurable tasks,” Workshop on Parallel and Distributed Real-Time Systems, Santa Fe, USA, April 2004.

31 References Contd.. [5] MURI on QoS in Surveillance and Control Radar Dwell Scheduling for Phased-Array Radars PIs Lui Sha Marco Caccamo Chang-Gun Lee [6] GOPALAKRISHNAN, S. Resource Management for Real-Time Environments. PhD thesis, University of Illinois, Urbana, Illinois, Dec. 2005. [7] GOPALAKRISHNAN, S., CACCAMO, M., SHIH, C.-S., SHA, L., AND LEE, C.-G. Finite horizon scheduling of radar dwells with online template construction. Real-Time Systems (2006).

32 Thank you !!!!

33 Questions and Answers


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