Simulation Evaluation of Hybrid SRPT Policies

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Simulation Evaluationof Hybrid SRPT Policies

• Mingwei Gong and Carey Williamson
• Department of Computer Science
• University of Calgary
• April 19, 2004

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Introduction

• Web large-scale, client-server system
• WWW World Wide Wait!
• User-perceived Web response time involves
• Transmission time, propagation delay in network
• Queueing delays at busy routers in the Internet
• Delays caused by TCP protocol effects
  (e.g., handshake, slow start, packet loss,
  retransmits)
• Queueing delays at the Web server itself, which
  may be servicing 100s or 1000s of concurrent
  requests
• Our focus in this work Web request scheduling

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Example Scheduling Policies

• FCFS First Come First Serve
• typical policy for single shared resource
  (unfair)
• e.g., drive-thru restaurant playoff tickets
• PS Processor Sharing
• time-sharing a resource amongst J jobs
• each job gets 1/J of the resources (equal,
  fair)
• e.g., CPU VM multi-tasking Apache Web server
• SRPT Shortest Remaining Processing Time
• pre-emptive version of Shortest Job First (SJF)
• give full resources to job that will complete
  quickest
• e.g., ??? (express lanes in grocery
  store)(almost)

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Research Methodology

• Trace-driven simulation
• Input workload is empirical/synthetic trace
• Web server simulator
• Empirical trace (1 million requests, World Cup
  1998)
• Synthetic traces (WebTraff)
• Probe-based sampling methodology
• Based on PASTA Poisson Arrivals See Time
  Averages
• Any scheduling policy, any arrival process, any
  service time distribution.

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Simulation Assumptions

• User requests are for static Web content
• Server knows response size in advance
• Network bandwidth is the bottleneck
• All clients are in the same LAN environment
• Ignores variations in network bandwidth and
  propagation delay
• Fluid flow approximation service time response
  size
• Ignores packetization issues
• Ignores TCP protocol effects
• Ignores network effects
• (These are consistent with SRPT literature)

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Performance Metrics

• Slowdown
• The slowdown of a job is its observed response
  time divided by the ideal response time if it
  were the only job in the system
• Lower is better
• We consider mean slowdown as well as the variance
  of slowdown (complete distribution)

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Empirical Web Server Workload
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Probe-based Sampling Algorithm

• The algorithm is based on PASTA (Poisson Arrivals
  See Time Average) principle.

Slowdown (1 sample)
Repeat N times
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Probe-based Sampling Algorithm

• For scheduling policy S (PS, SRPT, FCFS, LRPT,
  ) do
• For load level U (0.50, 0.80, 0.95) do
• For probe job size J (1B, 1KB, 10KB,
  1MB...) do
• For trial I (1,2,3 N) do
• Insert probe job at randomly chosen
  point
• Simulate Web server scheduling policy
• Compute and record slowdown value
  observed
• end of I
• Plot marginal distribution of slowdown
  results
• end of J
• end of U
• end of S

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Slowdown Profile Plot
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PS
Slowdown
SRPT
1
0
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Job Size
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Notation Details

• Number of jobs in the system J
• Number of threads for a single server K
• Number of servers in the system M
• Probe jobs 1KB, 10KB, 100KB, 1MB...
• Number of probes 3000
• All simulation results are for 95 load

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Single Server Scenario (M 1)

• PS Processor Sharing
• SRPT Shortest Remaining Processing Time
• FSP Fair Sojourn Protocol
• FSP computes the times at which jobs would
  complete under PS and then orders the jobs in
  terms of earliest PS completion times. FSP then
  devotes full service to the uncompleted job with
  the earliest PS completion time.
• FSP response time dominates PS (i.e., is never
  worse)

E. Friedman and S. Henderson Fairness and
Efficiency in Web Server Protocols, Proc. ACM
SIGMETRICS 2003.
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Mean Slowdown (M 1)
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Variance of Slowdown (M 1)
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A Hybrid SRPT/PS Policyfor a Single Server (M
1)

• Threshold-based policy, with threshold T
• T-SRPT
• Determining whether the system is "busy" or not
  depends on number of jobs (J) in the system.
• If J lt T
• Then use PS
• Else use SRPT
• Special cases T 0 is SRPT, T is PS

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Mean Slowdown for T-SRPT
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Variance of Slowdown for T-SRPT
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A Generalized SRPT Policy for aMulti-threaded
Single Server

• K-SRPT
• Multi-threaded version of SRPT that allows up to
  K jobs (the K smallest RPT ones) to be in service
  concurrently (like PS), though with the same
  fixed aggregate service rate. Additional jobs (if
  any) in the system wait in the queue. Also
  preemptive, like SRPT.
• Let s min (J, K)
• If J lt K
• Then J jobs each receive 1/s
• Else K jobs each receive 1/s (while J-K wait)
• Special cases K 1 is SRPT, K is PS

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Mean Slowdown for K-SRPT
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Variance of Slowdown for K-SRPT
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Multi-Server Scenario

• M-SRPT
• Let s M
• If J lt M
• Then J jobs each receive 1/s (M-J idle servers)
• Else M jobs each receive 1/s (while J-M wait)

• M-PS
• Let s max(M, J)
• Each job receives a service rate of 1/s

• M-FSP
• Let s M
• If J lt M
• Then J jobs (under PS) each receive 1/s
• Else M jobs (under PS) each receive 1/s

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Mean Slowdown for M-SRPT
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Variance of Slowdown for M-SRPT
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Mean Slowdown for M-PS
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Variance of Slowdown for M-PS
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Mean Slowdown for M-FSP
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Variance of Slowdown for M-FSP
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Summary

• Slowdown profile plots for several policies
• For the largest jobs, FSP better than SRPT and PS
• For small jobs, FSP is sometimes worse than SRPT
• Multi-threaded server results
• T-SRPT and K-SRPT provide a smooth transition
  between SRPT and PS, implying smoother tradeoff
  in fairness between small jobs and large jobs
• Multi-server results
• With more servers, mean slowdown worsens, but
  variance of slowdown often improves
• FSP does not response time dominate PS for M gt 1

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Thank You!Questions?
For more information Email gongm,carey_at_cpsc.uca
lgary.ca