ahmed alharthi april 25, 2014 uccs
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Methodology for Choosing Datacenter for Cloud Providers in West Africa Region. Ahmed Alharthi April 25, 2014 UCCS. Master’s Project Report. Agenda. Introduction Why Africa The proposed Methodology Selection Results Lessons Learned Future Work Conclusion. Motivation. - PowerPoint PPT PresentationTRANSCRIPT
Ahmed- Public Cloud Location in Africa
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Ahmed AlharthiApril 25, 2014
UCCSMaster’s Project Report
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Methodology for Choosing Datacenter for Cloud Providers in West Africa Region
Ahmed- Public Cloud Location in Africa
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• Introduction
• Why Africa
• The proposed Methodology
• Selection Results
• Lessons Learned
• Future Work
• Conclusion
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Agenda
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Lack of information regarding to data centers in Africa.
Demand of the services In globalizations movement, Africa was neglected Cloud provider numbers
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Motivation
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Cloud providers
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Number of data centers
Why Africa ?
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Number of Data Centers around the World
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Growing Demand from Africa
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Research the process for selecting the best locations to build data centers for cloud providers in West Africa.
Main Considerations: Network performance, Costs, Submarine cable.
Other factors : Environmental, Economical and Politics stabilities.
Research Plan
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Develop a methodology to suggest the best locations for setting up data centers for cloud providers.
Significance ◦ Connect Africa to the world in efficient way.
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Goal
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McConnell A., Parr G.P., Mc Clean S.I., Khan, K [38]
Khosrow Ebrahimi, Gerard F. Jones, and Amy S. Fleischer [11]
In terms of Africa’s network connectivity, M. Zennaro, E. Canessa, K.R. Sreenivasan , A.A. Rehmatullah and R.L. [12]
Sanjay M. Parekh, Robert B. Friedman, Neal K. Tibrewala, and Benjamin Lutch [28]
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Related Work
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Climate & topography of the continent Tornados & Hurricanes & Tsunami Earthquake Politic Systems on the region Economic Status
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Geographical & Climate Characteristics of the region
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Africa Submarine Cables
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Intel Considerations are : WAN infrastructure, availability of water for cooling, costs workforce, water, power or landscape.
HP Considerations are: quality of the landtheir size, price and geographic location, the availability of power and communication network in the region, cost of operations including electricity, water, network access, free cooling.
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How Intel/HP Select their Data Center Locations
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Methodology is mix of Intel , HP and IBM approaches
Main considerations :◦ Costs of Powering, Cooling and landscape. ◦ Communication network and their capabilities.Secondary considerations : Politics status Geographical & Climate location Submarine cables Economy
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The Proposed Methodology
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Decision Process for Selecting Countries to Host Public Cloud
Senegal, Guinea, Liberia, Ghana, Togo, Benin, Sierra Leone, Nigeria, Cameron, Cote d'ivoire, Congo, Angola, Democratic Republic of the Congo and Namibia.
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Results of Decision Process
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Latency Round Trip Time Packet loss Bandwidth
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Network measurements
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Network measurements
Amazon Linux AMI 2014.03.1 machines In Singapore, Sydney and Sao Paulo
Linux commands : Ping and Traceroute
Tool used :◦ Nmap (Network mapper)◦ Visual route
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System and Tools for Measurement
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From Colorado 128.198.49.171
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Network measurements from North America
Ghana South Africa Senegal Nigeria 0
50
100
150
200
250
300
23 27 30 27
220
265
182 182
Latecny RTT
Country Latency Round trip time
Packet loss
Number of Hops
Ghana 23 ms 220 ms 10 % 17
South Africa 27 ms 265 ms 0% 20
Senegal 30 ms 182 ms 0% 17
Nigeria 27 ms 182 ms 0% 18
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Network measurements from East Asia (Singapore)
Country Latency Round trip time
Packet loss Number of Hops
Ghana 197.253.65.36 28 ms 270 ms 0% 12South Africa 41.74.178.82 48 ms 476 ms 0% 20Senegal 41.83.255.255 24 ms 236 ms 0% 13Nigeria 41.222.211.58 27 ms 274 ms 0% 19
Ghana South Africa Senegal Nigeria 050
100150200250300350400450500
28 4824 27
270
476
236274
RTT Latency
54.255.149.162
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54.206.48.231
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Network measurements from East Asia (Sydney)
Country Latency Round trip time Packet loss Number of Hops
Ghana 197.253.65.36 44 ms 440 ms 0% 17South Africa 41.74.178.82 44 ms 493 ms 0% 25Senegal 41.83.255.255 42 ms 428 ms 0% 17Nigeria 41.222.211.5 42 ms 448 ms 0% 23
Ghana South Africa Senegal Nigeria 0
100
200
300
400
500
600
44 44 42 42
440493
428 448
Latency RTT
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54.255.149.162
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Network measurements from South America (Brazil)
Country Latency Round trip time Packet loss Number of HopsGhana 197.253.65.36 30 ms 312 ms 0% 14South Africa 41.74.178.82 36 ms 343 ms 0% 16Senegal 41.83.255.255 31 ms 281 ms 0% 14Nigeria 41.222.211.58 32 ms 297 ms 0% 12
Ghana South Africa 4 Senegal Nigeria 0
50
100
150
200
250
300
350
400
30 36 31 32
312343
281 297
Latency RTT
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[aalharth@walrus cs701]$ ping -c 10 197.253.65.36 PING 197.253.65.36 (197.253.65.36) 56(84) bytes of data. 64 bytes from 197.253.65.36: icmp_seq=1 ttl=43 time=981
ms 64 bytes from 197.253.65.36: icmp_seq=2 ttl=43 time=983
ms 64 bytes from 197.253.65.36: icmp_seq=3 ttl=43 time=973
ms 64 bytes from 197.253.65.36: icmp_seq=4 ttl=43 time=968
ms 64 bytes from 197.253.65.36: icmp_seq=5 ttl=43 time=972
ms 64 bytes from 197.253.65.36: icmp_seq=6 ttl=43 time=960
ms 64 bytes from 197.253.65.36: icmp_seq=7 ttl=43 time=1003
ms 64 bytes from 197.253.65.36: icmp_seq=9 ttl=43 time=967
ms 64 bytes from 197.253.65.36: icmp_seq=10 ttl=43 time=972
ms --- 197.253.65.36 ping statistics --- 10 packets transmitted, 9 received, 10% packet loss, time
8997ms rtt min/avg/max/mdev = 960.481/975.940/1003.880/11.900
ms, pipe 2
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Detailed Stat Related to Ghana Ghana Observation
core4.LDN-London.as6453.netis the last node connecting to Ghana
Goes to WASC submarine cables operated by TATA.
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Estimating the Coast of Space, Cooling and Powering Data Center
Estimation based on HP “Cost model for planning, development and operation of a data center”
Assumptions Facility size is 30,000 sq ft 10 MW datacenter %50 occupied
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Formula for Estimating Costs
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Cost of Renting Spaces
Country Average rent (per sq ft)
Lagos, Nigeria
$6.48 – 8.00
Accra, Ghana
$5.7-10.5
Dakar, Senegal
$ 5.5 – 9.5
Cape Town, South Africa
$ 10 - 14
Lagos, Nigeria Accra, Ghana Dakar, Senegal Cape Town, SA
$36 $41
$38
$60
Space Cost / sqft
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Cost of Power
Country
Power cost KWH
Lagos, Nigeria
$ 0.20
Accra, Ghana
$ 0.31
Dakar, Senegal
$0.42
Cape Town, SA
$ 0.48
Lagos, Nigeria Accra, Ghana Dakar, Senegal Cape Town, SA
$0.07
$0.12
$0.15
$0.17
Cost of Power /sqft per unit
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Cost of Cooling
Country Rate / sqft/unit
Lagos, Nigeria
$0.065/ft
Accra, Ghana
0.0115/ft
Dakar, Senegal
0.171/ft
Cape Town, SA
0.214/ft
Lagos, Nigeria Accra, Ghana Dakar, Senegal Cape Town, SA
0.065
0.115
0.171
0.214
Cooling Cost / sqft
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Total Cost
Lagos, Nigeria Accra, Ghana Dakar, Senegal Cape Town, SA
$36.44
$41.15 $37.44
$60.22
Total Cost /sq ft
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Country Nigeria Senegal South Africa Ghana
North America
1 1 4 3
Singapore 2 1 4 3
Sydney 2 1 4 3
Brazil 2 1 4 3
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Selection ResultsRanking the countries based on RTT
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Bandwidth
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Selection Results
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Total Space, Power and Cooling costs
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Selection Results
Lagos, Nigeria Accra, Ghana Dakar, Senegal Cape Town, SA
$36.44 $41.15
$37.44
$60.22
Total Cost /sq ft
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Network capability among the best and stable
High (5) submarine cables Cheapest power price per Kwh. Lowest total cost including space, power and
cooling. #1 Economy in the region. Largest number of Internet users, 49M. Stable politic system. Center of the region geographically
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Nigeria is Optimal Location
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Collecting data◦ Learn about IT in Africa.◦ Talk to students, IBM, HP, ISP providers, realtors◦ Language barrier.◦ Gathering real estate data◦ Conflicts data
Technical Challenges◦ Understanding cables systems◦ Track packets◦ Network tools◦ Web servers◦ Locating servers
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Lessons Learned
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Collect additional relevant data to select the best location of data center for a cloud provider.
The data gathered from latency, round trip time and bandwidth should be gained from relevant data center of a cloud provider in real world.
Examine ping and trace utility data multiple times in different times.
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Future Work
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Senegal, Nigeria, Ghana and South Africa are the ideal locations to host data center for cloud provider.
Nigeria has the most suitable features to host one. Africa has a good opportunity to host datacenter for
a cloud provide. Costs of datacenter may be vary from city to other
one.
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Conclusion
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