Optimizing Scheduling Policies for M/G/k Systems Under Various Load Conditions

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Explore the effectiveness of different scheduling policies, such as SRPT and SEK, in minimizing response times in M/G/k systems under moderate and heavy traffic loads. Learn about the benefits and limitations of these policies and discover new lower bounds for optimal performance.


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  1. Bounds on M/G/k Scheduling Under Moderate Load Izzy Grosof (Isaac) (they/she) CMU Georgia Tech UIUC Northwestern IEMS Ziyuan Wang (Northwestern IEMS) Ziyuan Wang 1 MAMA 2024 - June 14

  2. M/G/k Scheduling Load ? = ??[?] < 1 Job duration ~ ?, i.i.d. Scheduling w/ known sizes 1/k ? Poisson(?) 1/k Response time ? Shortest Remaining Processing Time? Q: What scheduling policy minimizes ?[?]? 2 MAMA 2024 - June 14

  3. SRPT: Optimal? SRPT-k SRPT-k: k jobs with least remaining size. SRPT-1 is always optimal [Schrage 68]. What about SRPT-k? 0 1 Load ? Heavy Traffic: ? 1 SRPT-k is asymptotically optimal! [GSH 18] No arrivals: SRPT-k is optimal! [McNaughton 59] + [Conway et al. 67] Medium load: ?????? 3 MAMA 2024 - June 14

  4. Questions of This Talk Q: Is SRPT-? optimal at medium load? A: No! We do better! SRPT-Except-? + 1! Q: How much better is possible? A: We give new lower bounds: WINE formula + Increasing Speed Queue (ISQ) 4 MAMA 2024 - June 14

  5. SRPT-Except-? + 1 (SEK) SRPT-k SEK(5) 3 3 10 4 10 4 SEK: If ? jobs or > ? + 1, same as SRPT-?. Remaining case: ? + 1 jobs SEK parameterized by size threshold ?. Example: ? = 5. If ? jobs with size ? and one job with size > ?, then SEK serves largest, leaves out second-largest. Otherwise, same as SRPT-?. 5 MAMA 2024 - June 14

  6. SEK Intuition SRPT-k SEK(5) 3 3 10 4 10 4 13 10 7 3 0 10 Time 4 3 0 4 Time 10 4 3 Servers 3 Servers Total response time, no arrivals: SRPT: 3 + 4 + 13 = 20. SEK: 3 + 7 + 10 = 20 Time of first wasted capacity: SRPT: 4. SEK: 7. SEK: Same response time, might as well waste less . 6 MAMA 2024 - June 14

  7. Further SEK Intuition SRPT-k SEK(5) 3 3 10 4 10 4 13 10 7 3 0 10 Time 4 3 0 4 Time 10 4 3 Servers 3 Servers SRPT-?: Better if arrival before time 4: Progress on size 4 job more valuable than progress on size 10 job. SEK: Better if arrival between times 4 and 13: Less wasted capacity. Empirically, latter is more important. 7 MAMA 2024 - June 14

  8. SEK Plot: Improvement over SRPT-? ? ???? ? ????? Setting: M/M/2, size Exp(1). Improvement ratio: 1 ? 0.996 simulated 8 MAMA 2024 - June 14

  9. SEK Proof: Open Want to show: For all size distributions ?, exists ?,? such that E ????< ?[?????] Idea: Use a Nudge-type proof. Very small ? should make for a cleaner proof, might need 2 jobs < ??????, 1 job > ??????. Interested in discussion and/or collaboration! 9 MAMA 2024 - June 14

  10. Lower bounds on M/G/k scheduling: Prior Prior work: Simple bounds. Resource-pooled SRPT-1, service time. Resource pooling bound: Thm: ? ?,? ?? ? ?[????? 1] Service time bound: Thm: ? ?,? ?? ? ?? ? 10 MAMA 2024 - June 14

  11. Lower Bounds: Prior - Drawbacks Resource pooling: ? ?,? ?? ? ?[????? 1] Tight as ? 1! Drawback: Doesn t scale with number of servers ?. Service time: ? ?,? ?? ? ?? ? Tight as ? 0! Drawback: Doesn t scale with load ?. Need new lower bounds if we want tight at moderate load! 11 MAMA 2024 - June 14

  12. WINE for Lower Bounds Work Integral Number Equality (WINE): [SGH 21] ? ? =? ? ? ? ?? ? =1 ?? ?2 ? ?=0 Relevant work ??: Total remaining size of jobs with remaining size ?. Idea: Lower bound relevant work ?[??], lower bound response time ? ? Resource pooled bound: ? ?? ? ? min ?,?2 2 1 ?? Service time bound: ? ?? ?? 2? min ?,?2 Combine using WINE! 12 MAMA 2024 - June 14

  13. WINE Lower Bound: Plot Resource pooled SRPT-1 Service time WINE combination Big improvement! WINE SRPT-1 Service M/M/2, ? ? = 1 13 MAMA 2024 - June 14

  14. Increasing Speed Queue (ISQ) (? = 2.4,? = 1/2) Single-server queue. State: Amount of work, server speed ?,? . Lower bound on work in the M/G/k. At the beginning of the busy period, system starts at speed 1/?, for some integer ?. Same speed as M/G/k at start of busy period. 14 MAMA 2024 - June 14

  15. Increasing Speed Queue (ISQ) (? = 1.9,? = 1/2) Single-server queue. State: Amount of work, server speed ?,? . Lower bound on work in the M/G/k. At the beginning of the busy period, system starts at speed 1/?, for some integer ?. Same speed as M/G/k at start of busy period. When another job arrives, speed increases to 2/?, 3/?, up to 1. 15 MAMA 2024 - June 14

  16. Increasing Speed Queue (ISQ) (? = 4.2,? = 1) Single-server queue. State: Amount of work, server speed ?,? . Lower bound on work in the M/G/k. At the beginning of the busy period, system starts at speed 1/?, for some integer ?. Same speed as M/G/k at start of busy period. When another job arrives, speed increases to 2/?, 3/?, up to 1. Stays at speed 1 until end of busy period. 16 MAMA 2024 - June 14

  17. ISQ: Drift-based Analysis Idea from tutorial: Find a test function with linear drift. Here, goal is linear in work ?. Test function ?(?,?): ? 0,0 = 0 ? ?,1 = ?2 ? ?,1 2 If ? > 0, ? = 1 or , ? ? ?,? = ?? ?2+ 2?( 1 + ?) ? 1 ? 2?? = ?2+? 2?2 17 MAMA 2024 - June 14

  18. ISQ: Mean Work If ? > 0, ? = 1 or , ? ? ?,? = ?? ?2+ 2?( 1 + ?) Thm: +? ? 1 ? 2? /2? 3 ? 2? ?? ?2 2 1 ? ? ? = Exact characterization of mean work! Similar results for ISQ-?. Lower bound on total work in M/G/k 18 MAMA 2024 - June 14

  19. ISQ: Relevant Work Bounds More effort to use ISQ to lower bound relevant work, because of recycled jobs. ? From the perspective of relevant work ?, size ? jobs appear in the system. recycle 19 MAMA 2024 - June 14

  20. ISQ: Relevant Work Bounds More effort to use ISQ to lower bound relevant work, because of recycled jobs. ? =x From the perspective of relevant work ?, size ? jobs appear in the system. recycle Simple ISQ-based bound: Use size distribution ??= [?1 ? ? ], and ? jobs recycle on separate servers. Fancier ISQ-based bound: Worst-case jump in test function ?(?,?). 20 MAMA 2024 - June 14

  21. ISQ: Detailed relevant work bounds Definitions: ??= ???? ,??= ? S ? , ??= ??? ?? ,? ?= ??[min ?,? ] Separate-servers ISQ: ISQ ? ?? 1 ??2?? 2?? Recycling 2 ??? ?? 2 1 ?? + ? ???2 ? ?? + 3 ??2?? ISQ Worst-case jump (recycling) ISQ: ? ?? 1 Recycling ??2?? 2?? 2 ? ???2 2 1 ?? ??? ?? 2 1 ?? 1 ? ? 1 ?? ? ?? + + 3 ??2?? 21 MAMA 2024 - June 14

  22. Stronger response time lower bounds Red: Simple ISQ bound. Purple: Combine all 3 with WINE. Improvement of WINE 3 over WINE 2. WINE 4: Add in fancy ISQ bound. 22 MAMA 2024 - June 14

  23. Future Directions Prove for all size dists. ?, exists load ? and threshold ? such that ? ????< ? ?????? Use lower bounding framework to prove optimality in some medium load setting? Generalize ISQ relevant work lower bounds to all ?. 23 MAMA 2024 - June 14

  24. Conclusion SRPT-k SEK(5) 3 3 10 4 10 4 24 MAMA 2024 - June 14

  25. Bonus: Lower bound comparison to SRPT-k M/M/10 25 MAMA 2024 - June 14

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