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A Case Study About Cloud Based Virtual Labs Poster presentation on 2nd International Conference on Cloud Computing and Service Sciences (CLOSER 2012). Case study about cloud based virtual labs and corresponding cost advantage in higher education.
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What Cost Us Cloud Computing?A Case Study About Cloud Based Virtual Labs
Nane Kratzke
13 14 15 16 17 18 19 20 21 22 23 24 25
Average Box UsageMaximum Box Usage in an hour
(A)Maximum and Average Box Usage
Calendar Week
Use
d S
erve
r Box
es
010
2030
4050
13 14 15 16 17 18 19 20 21 22 23 24 25
(B)Accumulated Processing Hours per Week
Calendar Week
Pro
cess
ing
Hou
rs
0500
1000
1500
2000
14 16 18 20 22 24
0.0
0.2
0.4
0.6
0.8
1.0
(C)Average Box to Maximum Box Ratio
according to Weinman
Calendar Week
Avg
to M
ax B
ox U
sage
Rat
io
Is it more economical for practical courses to pro-
vide classical dedicated educational labs or to use
IaaS/cloud based virtual labs? Try to decide for your-
self by analyzing the following table of measured real world
cost data!
Group Students Project Costs in $
A 1 5 WRSC Website 88.39$
A 2 6 WRSC Website 265.37$
A 3 4 WRSC Website 88.14$
A 4 6 WRSC Website 162.88$
B 1 6 Sailbot Tracking 41.17$
B 2 6 Sailbot Tracking 57.58$
B 3 6 Sailbot Tracking 57.46$
B 4 5 Sailbot Tracking 37.42$
B 5 5 Sailbot Tracking 48.58$
Hard – isn’t it? We have answered this question at the Lu-
beck University of Applied Sciences for several lectures of
computer science study programs.
The analyzed use case was a college lecture on web techno-
logies for computer science students in summer 2011.
24x7
Training Development phase P M
13 - 15 16 - 23 24 25
Calendar weeks
In the corresponding practical courses of this lecture students
formed groups of 5 or 6 persons to develop a website for a
scientific conference on robotic sailing (project 1) or deve-
lop a google map based automatic sailbot tracking service
(project 2) for the same conference. All groups were assigned
cloud service provider accounts from Amazon Web Services.
According to the presented figures we can identify different
phases being more cloud compatible than others from an
economical point of view. Training and development pha-
ses show very peaky usage characteristics of resources which
advantages cloud computing. Other phases with less peaky
usage characteristics disadvantage cloud computing.
According to Weinmans proof of the “Inevitability of Cloud
Computing” we used the following maximum variable cost
formula as decision criteria.
cMAX :=dAT F(p)
at p(TStart,TEnd,uc)(1)
This decision criteria can be applied according the following
developed four step decision model.
Step 1: Determine your atp ratio
In our analyzed timeframe 7612 hours of instance usage were
generated. So the following average amount of servers would
be necessary to provide 7612 processing hours within a 26
week timeframe.
avg26w =7612h
26 ·7 ·24h≈ 1.74 (2)
Our maximum server usage within 1 hour was 49 servers in
parallel. So we got the following average to peak ratio for a
26 week timeframe.
at p26w =avg26w
max=
1.7449
≈ 0.035 (3)
Step 2: Determine your dedicated costs
At the Lubeck University of Applied Sciences the procure-
ment office could purchase the smallest possible server version
(approximately 4 ECU in the AWS universe) for about 3055$.
So our dedicated costs per atomic timeframe (1h) would be
(regarding a 5 year amortization):
d5year(3055$) =3055$
5 ·365 ·24h≈ 0.0697
$h
(4)
Step 3: Determine your maximal cloud costs
Equation 1 told us to calculate our cMAX costs in the following
way:
c26wMAX =
d5year(3055$)at p26w
=0.06970.035
$h≈ 1.99
$h
(5)
Step 4: Check appropriate cloud resources
The following table shows that AWS provides several compa-
rable instance types with pricings below our maximal costs.
AWS Instance Type ECU Price/h Comparable
Micro < 1 0.025$ -
Small (Standard) 1 0.095$ -
Large (Standard) 4 0.38$ o
XL (Standard) 8 0.76$ +
XL (High Memory) 6.5 0.57$ +
Medium (High CPU) 5 0.19$ o
Conclusions
So due to our peaky usage characteristics virtual labs are
more economical for the analyzed lecture (web technologies)
than classical dedicated educational labs.
It turned out that virtual labs provide a more than 25 times cost advantage (1/at p26w ≈ 28.73). In average each student ”cost” us 17.27 USD.
CW 13 CW 14–17 CW 18–21 CW 22–25
(A)Costs per Month (aligned to Weeks)
Cos
ts in
US
D
0100
200
300
400
500
instancehour (62%)
datastorage (34%)
adressing (3%)datatransfer (0%)
(B)Main Cost Drivers
GM 1 (5%)
GM 2 (7%)
GM 3 (7%)GM 4 (4%)GM 5 (6%)
WRSC 1 (10%)
WRSC 2 (31%)
WRSC 3 (10%)
WRSC 4 (19%)
(C)Costresponsibilty of Groups
(D) Histogram of Costs per Group
Cost Ranges in USD
# G
roup
s
0 50 100 150 200 250 300
01
23
4
Acknowledgements. Thanks to Amazon Web Services for supporting our ongoing research with several research as well as educational grants. Thanks to our students and Michael Breuker for using cloud
computing in practical education. Let me thank Alexander Schlaefer and Uwe Krohn for organizing the 4th World Robotic Sailing Championship 2011 (WRSC 2011) and their confidence in our students.
