Prof. Daniel A. Menascé Department of Computer Science George Mason University
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1 Pro. Daniel. Menascé Deartment o Comuter Science George Mason University D.. Menascé. ll Rights Reserved. 1 Most o the igures in this set o slides come rom the book Perormance by Design: comuter caacity lanning by examle, by Menascé, lmeida, and Dowdy, Prentice Hall, It is strictly orbidden to coy, ost on a Web site, or distribute electronically, in art or entirely, any o the slides in this ile D.. Menascé. ll Rights Reserved. 2
2 Online auction site. One Web Server, one lication Server, and one Database Server. Each server has one CPU and one disk. Services oered by the site: Create and broker auctions Search or auctions based on categories and keywords Monitor existing bids on oen auctions Place bids on oen auctions. Login 2004 D.. Menascé. ll Rights Reserved. 3 Manages web ages and handles direct interactions with customers. Imlements core business logic o the site. Stores ersistent data about auctions, bids, registered customers D.. Menascé. ll Rights Reserved. 4
3 2004 D.. Menascé. ll Rights Reserved. 5 Entry (e Home (h Search (s iew ids (v Create Login (g uction (c Place id (b Exit (x Entry (e Home (h Search (s iew ids (v Login (g Create uction (c Place id (b Exit (x D.. Menascé. ll Rights Reserved. 6
4 Entry (e Home (h Search (s iew ids (v Login (g Create uction (c Place id (b Exit (x Entry y( (e Home (h Search (s iew ids (v Login (g Create uction (c Place id (b Exit (x D.. Menascé. ll Rights Reserved. 7 e h s v g = 1 = = = e h s = h = c g eh hs sv hg gb = 1 s s ss sg v vg 2004 D.. Menascé. ll Rights Reserved. 8
5 Tye session have higher number o visits to most states e h s v g c b D.. Menascé. ll Rights Reserved ions Nume eber o ucti / / / / / / / / / / / / / / / /31 Time slot = 1 day Number o uctions /16 10/17 10/18 10/19 10/20 10/21 10/22 10/23 10/24 10/25 10/26 10/27 10/28 10/29 10/30 10/ D.. Menascé. ll Rights Reserved. Time slot = 1 hour on each day. 10
6 10000 umber o u uctions N Sum o no. auctions er hour on all days. 0:0 00 verage arrival rate during eak hour is 11 times the average or the rest o the day. 2:0 00 4:0 00 6:0 00 8: : :0 00 Time o Day 14: : : : : D.. Menascé. ll Rights Reserved. 11 Nu umber o id ds umber o ids N /2 26 M /26 10/ /27 10/ 10/ /26 PM 10/2 27 M 10/ /27 PM /28 10/ /29 10/ 10/2 28 M 10/ /28 PM 10/2 29 M 10/ /29 PM 10/3 30 M /30 10/ /31 10/ 10/ /30 PM 10/3 31 M 10/ /31 PM 11/0 01 M 1/1 1 /01 PM 11/ Time slot = 1 day Time slot = 1 hour on each day D.. Menascé. ll Rights Reserved. 12
7 2000 Numbe er o i ds :00 0 2:00 0 4:00 0 6:00 0 8: : : : : : : :00 0 Total Human Proxy 2004 D.. Menascé. ll Rights Reserved. 13 surge in the number o auctions created and bids laced was observed between 8.m. and 11.m. What is the resonse time o the various tyes o requests (home age hits, search executions, bid viewings, logins, auction creations, and bid lacements? The resonse time SL or create auctions and bid lacement is 4 seconds D.. Menascé. ll Rights Reserved. 14
8 To solve this model the arameters needed are 1 arrival rates o requests er To solve this model, the arameters needed are 1 arrival rates o requests er class, and 2 service demands er request er class at each device. Multiclass Oen Queuing Network Model 2004 D.. Menascé. ll Rights Reserved. 15 g γ: total rate at which sessions are started. ( ( home h h = = γ γ ( ( view search v v s s = = γ γ ( login g g = γ ( ( bid create b b c c = = γ γ ( bid b b γ 2004 D.. Menascé. ll Rights Reserved. 16
9 Total Session rrival Rate (sessions/sec Percent o Tye Sessions 0.25 Percent o Tye Sessions 0.75 rrival o requests (requests/sec Home (h Search (s iew bids (v Login (g Create uction (c Place ids (b Cha8-CMG.XLS 17 Record and relay scrits that submit a single tye o request by using load testing tools [2]. Service demand or a request o tye r can be obtained by submitting a large no. N o requests o that tye to the site during a eriod o time τ. τ Utilization U i o each device i o the site is measured during that eriod. Service demand D i,r o class r requests at device i: Ui Dir, = ( N / τ 18
10 Device (h (s (v (g (c (b WS CPU WS disk S CPU S disk DS CPU DS disk Oen Multiclass Queuing Networks This wokbook comes with the books "Caacity Planning or Web Services" and "Scaling or E-usiness" by D.. Menascé and.. F. lmeida, Prentice Hall, 2002 and No. Queues: 6 No. o Classes: 6 Classes rrival Rates: Service Demand Matrix Classes Tye iew bids Create uction Place ids Queues (LI/D/MPn Home (h Search (s (v Login (g (c (b WS-CPU LI WS-disk LI S-CPU LI S-disk LI DS-CPU LI DS-disk LI D.. Menascé. ll Rights Reserved. Cha8-OenQN.XLS 20
11 Time (sec c verage Request Resonse lace bids SL or create auction and lace bids create auctions Session Starts/sec Home Search Login Create id iew 2004 D.. Menascé. ll Rights Reserved. 21 Oen Multiclass Queuing Networks - Residence Times This wokbook comes with the books "Caacity Planning or Web Services" and "Scaling or E-usiness" by D.. Menascé and.. F. lmeida, Prentice Hall, 2002 and Classes Queues Home (h Search (s iew bids (v Login (g Create uction (c Place ids (b WS-CPU WS-disk S-CPU S-disk DS-CPU DS-disk Resonse Time The disk at the database server is the bottleneck 2004 D.. Menascé. ll Rights Reserved. 22
12 Oen Multiclass Queuing Networks This wokbook comes with the books "Caacity Planning or Web Services" and "Scaling or E-usiness" by D.. Menascé and.. F. lmeida, Prentice Hall, 2002 and No. Queues: 7 No. o Classes: 6 Classes rrival Rates: Service Demand Matrix Classes Queues Tye (LI/D/MPn Home (h Search (s iew bids (v Login (g Create uction (c Place ids (b WS-CPU LI WS-disk LI S-CPU LI S-disk LI DS-CPU LI DS-disk1 LI DS-disk2 LI D.. Menascé. ll Rights Reserved. Cha8-OenQN-TwoDisks.XLS 23 Oen Multiclass Queuing Networks - Residence Times This wokbook comes with the books "Caacity Planning or Web Services" and "Scaling or E-usiness" by D.. Menascé and.. F. lmeida, Prentice Hall, 2002 and Classes iew bids Create uction Place ids Queues Home (h Search (s (v Login (g (c (b WS-CPU WS-disk S-CPU S-disk DS-CPU DS-disk DS-disk Resonse Time D.. Menascé. ll Rights Reserved. 24
13 Resonse Times (sec iew bids Create Place ids Home (h Search (s (v Login (g uction (c (b rrival Rates (req/sec Original Coniguration New Coniguration % Reduction 0.0% 97.9% 94.5% 97.8% 98.2% 98.5% 2004 D.. Menascé. ll Rights Reserved. 25 Generally, there are many identical servers in each tier Consider a simle case o N ws identical Web servers, and erect load balancer sending exactly 1/N ws o traic to each WS avg. arrival rate o requests at each WS = /N ws Ignore alication and database servers Consider a single class o requests 26
14 ssumtions: identical WS s and erect load balancer 2004 D.. Menascé. ll Rights Reserved. 27 Resonse time at the single equivalent server: K Di R = 1 ( / N ws D i= 1 where K is no. o devices (CPU and disk, D i (i = 1,, K is service demand o request at device i Generalization o R to multile classes: R r D = = K K ir, ir, R i= 11 Ui i= 11 ( / r Nws D r= 1 i, r where R r is average resonse time o class r requests, r is average arrival rate o requests o class r,, and U i = R / N D is utilization o device i over all R classes r = r ws i r 1 (, i D 28
15 Total Session rrival Rate (sessions/sec 11 Percent o Tye Sessions 0.25 Percent o Tye Sessions 0.75 rrival o requests (requets/sec Home (h Search (s iew bids (v Login (g Create uction (c Place ids (b Utilization o CPU at the single equivalent Web server U CPU home search view = login create bid = = 30
16 Utilization o disk at the single equivalent Web server U disk home search view = login create bid = = 31 Resonse times o each o six classes o requests at the Web server tier are: Rhome = = sec Rsearch = = sec Rview = = sec Rlog in = = sec R create = = sec R bid = = sec
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Case Study I: n E-usiness Service Pro. Daniel. Menascé Department o Computer Science George Mason University www.cs.gmu.edu/aculty/menasce.html 1 Copyright Notice Most o the igures in this set o slides
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