1

Mor Harchol-BalterCarnegie Mellon University

Joint work with Bianca Schroeder

2

“size” = service requirement

load < 1

jobs SRPT

jobs

jobs PS

FCFS

Q: Which minimizes mean response time?

3

“size” = service requirement

jobs SRPT

jobs

load < 1

jobs PS

FCFS

Q: Which best represents scheduling in web servers ?

4

IDEAHow about using SRPT instead of PS in web servers?

Linux 0.S.

WEBSERVER(Apache)

client 1

client 2

client 3

“Get File 1”

“Get File 2”

“Get File 3”

Internet

5

Many servers receive mostly static web requests.

“GET FILE”

For static web requests, know file size

Approx. know service requirement of request.

Immediate Objections 1) Can’t assume known job size

2) But the big jobs will starve ...

6

Outline of Talk

1) “Analysis of SRPT Scheduling: Investigating Unfairness”

2) “Size-based Scheduling to Improve Web Performance”

3) “Web servers under overload: How scheduling can help”

THEORY

IMPLEMENT

www.cs.cmu.edu/~harchol/

7

THEORY SRPT has a long history ...

1966 Schrage & Miller derive M/G/1/SRPT response time:

1968 Schrage proves optimality

1979 Pechinkin & Solovyev & Yashkov generalize

1990 Schassberger derives distribution on queue length

BUT WHAT DOES IT ALL MEAN?

8

THEORYSRPT has a long history (cont.)1990 - 97 7-year long study at Univ. of Aachen under Schreiber SRPT WINS BIG ON MEAN!

1998, 1999 Slowdown for SRPT under adversary: Rajmohan, Gehrke, Muthukrishnan, Rajaraman, Shaheen, Bender, Chakrabarti, etc. SRPT STARVES BIG JOBS!

Various o.s. books: Silberschatz, Stallings, Tannenbaum: Warn about starvation of big jobs ...

Kleinrock’s Conservation Law: “Preferential treatment given to one class of customers is afforded at the expense of other customers.”

9

Unfairness Question

SRPT

PS?

?

Let =0.9. Let G: Bounded Pareto(= 1.1, max=1010)

Question: Which queue does biggest job prefer?

10

THEORYOur Analytical Results (M/G/1):

SRPT

PS

All-Can-Win Theorem:Under workloads with heavy-tailed (HT) property,ALL jobs, including the verybiggest, prefer SRPT to PS,provided load not too close to 1.

Almost-All-Win-Big Theorem:Under workloads with HT property, 99% of all jobs perform orders of magnitude better under SRPT.

I SRPT

Counter-intuitive!

11Berkeley Unix process CPU lifetimes [HD96]

Fraction of jobs with CPU duration > x

Duration (x secs)

log-log plot

Pr{Life > x} = 1x

What’s Heavy-Tail?

12

What’s the Heavy-Tailproperty?

20 , ~ } { Pr xxXDefn: heavy-tailed distribution:

Many real-world workloads well-modeled by truncated HT distribution.

Key property: HT Property:

“Largest 1% of jobs comprise half the load.”

13

THEORYOur Analytical Results (M/G/1):

SRPT

PS

All-Can-Win Theorem:Under workloads with heavy-tailed (HT) property,ALL jobs, including the verybiggest, prefer SRPT to PS,provided load not too close to 1.

Almost-All-Win-Big Theorem:Under workloads with HT property, 99% of all jobs perform orders of magnitude better under SRPT.

I SRPT

Counter-intuitive!

14

THEORYOur Analytical Results (M/G/1):

All-distributions-win-thm:If load < .5, for every job size distribution,ALL jobs prefer SRPT to PS.

Bounding-the-damage Theorem:For any load, for every job size distribution, for every size x,

PSSRPT xTExTE )]([1)]([

15

What does SRPT mean within a Web server?

• Many devices: Where to do the scheduling?

• No longer one job at a time.

IMPLEMENT From theory to practice:

16

Server’s Performance BottleneckIMPLEMENT

5

Linux 0.S.

WEBSERVER(Apache)

client 1

client 2

client 3

“Get File 1”

“Get File 2”

“Get File 3”

Rest ofInternet ISP

Site buyslimited fractionof ISP’s bandwidth

We model bottleneck by limiting bandwidth on server’s uplink.

17

Network/O.S. insides of traditional Web server

Sockets take turnsdraining --- FAIR = PS.

WebServer

Socket 1

Socket 3

Socket 2Network Card

Client1

Client3

Client2BOTTLENECK

IMPLEMENT

18

Network/O.S. insides of our improved Web server

Socket corresponding to filewith smallest remaining datagets to feed first.

WebServer

Socket 1

Socket 3

Socket 2Network Card

Client1

Client3

Client2

priorityqueues.

1st

2nd3rd

S

M

L

BOTTLENECK

IMPLEMENT

19

Experimental Setup

Implementation SRPT-based scheduling: 1) Modifications to Linux O.S.: 6 priority Levels 2) Modifications to Apache Web server 3) Priority algorithm design.

Linux 0.S.

123

APACHEWEB

SERVER

Linux

123

200

Linux

123

200

Linux

123

200

switch

WAN

EM

UW

AN E

MU

WAN

EM

U

20

Experimental Setup

APACHEWEB

SERVER

Linux 0.S.

123

Linux

123

200

Linux

123

200

Linux

123

200

switch

WAN

EM

UW

AN E

MU

WAN

EM

U

Trace-based workload: Number requests made: 1,000,000Size of file requested: 41B -- 2 MBDistribution of file sizes requested has HT property.

FlashApache

WAN EMUGeographically-dispersed clients

10Mbps uplink100Mbps uplinkSurgeTrace-basedOpen systemPartly-open

Load < 1Transient overload

+ Other effects: initial RTO; user abort/reload; persistent connections, etc.

21

Preliminary Comments

• Job throughput, byte throughput, and bandwidth utilization were same under SRPT and FAIR scheduling.

• Same set of requests complete.

• No additional CPU overhead under SRPT scheduling. Network was bottleneck in all experiments.

APACHEWEB

SERVER

Linux 0.S.

123

Linux

123

200

Linux

123

200

Linux

123

200

switch

WAN

EM

UW

AN E

MU

WAN

EM

U

22

Load

FAIR

SRPTMea

n R

espo

nse

Tim

e (s

ec)

Results: Mean Response Time

.

.

.

.

.

.

23

FAIR

SRPT

Load

Mea

n Sl

owdo

wn

Results: Mean Slowdown

24

Percentile of Request Size

Mea

n R

espo

nse

time

(s)

FAIR

SRPT

Load =0.8

Mean Response Time vs. Size Percentile

25

• SRPT scheduling yields significant improvements in Mean Response Time at the server.

• Negligible starvation.

• No CPU overhead.

• No drop in throughput.

Summary so far ...

26

More questions …

• So far only showed LAN results. Are the effects of SRPT in a WAN as strong?

• So far only showed load < 1. What happens under SRPT vs. FAIR when the server runs under transient overload? -> new analysis -> implementation study

27

WAN EMU resultsPropagation delay has additive effect.Reduces improvement factor.

FAIR

SRPT

28

WAN EMU resultsLoss has quadratic effect.Reduces improvement factor a lot.

FAIR

SRPT

29

WAN results Geographically-dispersed clients

Load 0.9

Load 0.7

30

Zzzzzzzzzz...

Personunder

overload

Overload – 5 minute overview

31

Q: What happens under overload?A: Buildup in number of connections.

FAIR

SRPT

Q: What happens to response time?

32

Web server under overload

Clients

SYN-queueWhen reach SYN-queue limit, server drops all connection requests.

Server

SYN-queue ACK-queue Apache-processes

33

Transient Overload

34

Transient Overload - Baseline

Mean response time SRPTFAIR

35

Transient overloadResponse time as function of job

size

small jobswin big!

big jobsaren’t hurt!

FAIR

SRPT

WHY?

36

Baseline CaseWAN propagation delays

WAN loss

Persistent ConnectionsInitial RTO valueSYN CookiesUser Abort/ReloadPacket LengthRealistic Scenario

WAN loss + delay

RTT: 0 – 150 ms

Loss: 0 – 15%

Loss: 0 – 15%RTT: 0 – 150 ms,

0 – 10 requests/conn.

RTO = 0.5 sec – 3 secON/OFF

Abort after 3 – 15 sec, with 2,4,6,8 retries.

Packet length = 536 – 1500 Bytes

RTT = 100 ms; Loss = 5%; 5 requests/conn.,RTO = 3 sec; pkt len = 1500B; User abortsAfter 7 sec and retries up to 3 times.

FACTORS

37

Transient Overload - Realistic

Mean response timeFAIR SRPT

38

SRPT scheduling is a promising solution for reducing mean response time seen by clients, particularly when

the load at server bottleneck is high.

SRPT results in negligible or zero unfairness to large requests.

SRPT is easy to implement.

Results corroborated via implementation and analysis.

Conclusion