Methodology for Choosing Datacenter for Cloud Providers in West Africa

Region

ByAhmed Alharthi

Bachelor of Science in Computer Science FBSU, Saudi Arabia2009

A ProjectSubmitted to the Graduate School Faculty of Graduate School of the

University of Colorado at Colorado SpringsIn Partial Fulfillment of the Requirements

For the Degree of Master of ScienceDepartment of Computer Science

Spring 2014

This project for the Master of Science degree byAhmed Alharthi

Has been approved for theDepartment of Computer Science

By

________________________________________________________________Advisor: Dr. C. Edward Chow

________________________________________________________________Dr. Jia Rao

________________________________________________________________Dr. Kristen Walcott-Justice

_________________________________________

Date

List of Content Chapter 1 Introduction................................................................................................... 1.1 Aim and significant of the research............................................................ 1.2 Problem description................................................................................... 1.3 Targeted Audience…………………………………………………..…….. 1.4 Related Work: ............................................................................................ Chapter 2 Why Africa............................................................................................ ...... 3.1. Submarine cables………………………………………………………..3.2Geographical Characteristics on the region............................................. 3.3 Politic Systems on the region.................................................................. 3.4 Economic status in the region................................................................. Chapter 3The proposed methodology......................................................................... 3.1 Decision criteria....................................................................................... 3.2 intensive measurements for the potential location .................................. 3.3 Date center costs …………………………………………………………..Chapter 4 Discussion4.1 Nigeria is the Ultimate location..................................................................................4. 1 Attractive business atmosphere......................................................... 4.3 Net work capabilities are strong................................................................. 4.4The coast of operations..................................................... ………Chapter 5Google map web-based applicationChapter 7 Lessons Learned .................................................................................................. Chapter 8 Future work ....................................................................................................... Chapter 9 Conclusion ......................................................................................................... Bibliography……………………………….

1. Introduction This project report gives a description of the research and process for which will be undertaken in delivering a report to the requirements of selecting the best location to build dData centers for cloud providers in West Africa. We Studying study and analyzeing different factors when considering the best location for the Ca cloud providerompany to base choose its newa data center away from its regular locationsin a region [1]. This project mainly analyzes countries in West Africa as a potential choice for hosting the data center within which the most Companies do not have a single data centerserves the region.

There are many studies, reports and expert demonstrations on what are the most important elements in deciding the best location to build a data center for a cloud provider. There are different factors to be considered. Among them, the most important factors are when answering this question including network capabilityfacilities , the efficiency of operations of the center and cost of setting up a data center. factor which among the three is the most important element and whichThey are is the most critical business decision for building and maintaining the infrastructure required. IT businesses, small and large are similar in the way they make decisions. In order to make the best decision for their company, researchers and management require sufficient information before arriving at a decision and thus the purpose of these this project. In this project, we attempt to go through the decision criteria and options available for IT businesses which are looking to build their data centers in West Africa. This project attempted to produce a detailed list of the most important factors [2, ], [3, ], [4]. The decision for criteria are Cost of data center includes

[a.] The decision criteria are Cost of data center includes

Buildings.

Electricity

Landscape ( per square foot)

a.[b.] Data center distance from submarine cable

b.[c.] Network capability includes

Network latency (RTT)

Throughput

Average Typical Packet Loss

c.[d.] Environmental factors

d.[e.] Economic stability.

e.[f.] Politics System.

f.[g.] Ease of can access to the suggested location.

The criteria for selecting a data center for a cloud provider could include choosing a country with lowest cost for setting up a data center, a city with the best network capabilities, a country with stable economic and political system/climate, and so on.

This project, discusses the various risk factors that may impact data centers especially the geography in Africa. Similarly we also consider the probabilities of natural disasters such as floods, tornados and hurricanes. cases, such asFor example, many companies choose Colorado for hosting their data centers because the geographic advantage of choosing Colorado with low threat from those natural disaster. for the Company’s data center operations will be analyzed by studying probabilities of natural disasters such as floods, tornados and hurricanes. There are other issues that should be considered in this project, such as the political situation in these countries. All these factors will be considered during this research and more issues may be uncounted as the research progresses.

1.1 Aim and significant of the research Aim

To develop a methodology to suggest the best location forof setting up data center in West Africa region based network capability and the costs of space, power, and cooling for the datacenter.

Significance of the Research

This research is important in the current age of technological advancement. Currently globally,

IT is a major factor that boosts the economy of most countries. The demand for fast and reliable

internet connectivity is growing. This demand helps in connecting various countries and making

the world to be a global village.

West Africa is a growing IT hub and it is no exception for it to be connected to the rest of the

world. Currently data providers are limited in this region. For this reason, the economy is

boosted mostly by agriculture and industries. This therefore creates a good environment for

setting up a new data center. This is because the Nnew data centers are assured ofassure a major

market share in the region for their users because they improve delivering services for customers.

This in turn will help to create more IT related businesses. At the same time the rolling out of

new internet connectivity will help dispense information [5].

This will help to boost other related sectors of the economy also. Education will be greatly

improved as stakeholders will be able to carry out more innovative ideas. The information and

technology sector, mostly media houses, will be able to improve. They will be able to create

more digital content and at the same time create more job opportunities [6]

Cloud providers can therefore look at the wide vast opportunitiesy to invest and expand their

presence. At the same time, they it will be able to create more revenue and profits. Many At the

end, this research will enable the economy to grow. bBusinesses that depend on data centers. The

availability of data centers are many and this will surely affect everybody in the region. For this

reason West Africa will be the new investment hub that investors won’t ignore [7].

1.2 Problem description There is lack of sufficient research and information about Africa regarding possible best

locations in which data centers can be put set up to aid in the globalization movement that has

leadingd to ease of doing business and world trade. For this reason, this research paper will focus

on West Africa region by and analyzinge and evaluatinge one of the following countries with an

aim of proposing the best location for Amazon EC 2 or google as an examplesany company to

base its data center within these geographical regions:

Senegal, Guinea, Liberia, Ghana, Togo, Benin, Sierra Leone, Nigeria, Cameron, Cote

d'ivoire, Congo, Angola, Democratic Republic of the Congo and Namibia.

These countries have been chosen since they lie next to the large water bodies and these oceans

and seas are serviced by marine cables such as fiber optic which are part of a major internet and

communication infrastructure [8]. Furthermore, cloud providers are looking an in- depth

evaluation of these countries since it they plans on having a data center in these parts of the

world to help the company with its service delivery and expansion plans into new markets and

regions.

1.3 The targeted audienceThe targeted audience for this research is any one conducting research in cloud computing

and the related facility location problem, in particular to those cloud providers interesteding in

setting up data centers in West Africa. For example, Amazon EC2 are planning to expand their

operations into new regions and based on their current market presence as shown in Figure 1

Amazon EC2’s global infrastructure.

Figure 1.1 Amazon EC2 global infrastructures [1]

Amazon EC2 currently does not have data centers in Africa. Any one intends to do that

needs a critical evaluation of geographical, risk mitigation, natural disaster factors and man-made

situation factors within the listed countries in order to determine the best location for their new

data center. Although the result of this project gives a clear and precise location of the most

suitable location based on

for this research is any one conducting research in cloud computing and the related facility

location problem, in particular to those cloud providers interesting in set up data centers in West

Africa. For example, Amazon EC2 are planning to expand their operations into new regions and

based on their current market presence as shown in Figure 1 Amazon EC2’s global

infrastructure. The Amazon EC2 currently does not have data centers in Africa. Any one intends

to do that needs a critical evaluation of geographical, risk mitigation, natural disaster factors and

man-made situation factors within the listed countries in order to determine the best location for

their new data center. Although the paper will give a clear and precise location of the most

suitable location based on the proposed metrics, the final decision on where the data center will

be located will depend on other factors such as demands and financial situations.

1.4 Related workOn related work, the paperIn this section we will analyze the presence of any previous work

undertaken concerning the suitability of locating data centers. For example, John Rath has

presented a work that attempt to breaks down the decision criteria and options available to

companies who are looking to build data center. His work presents an exhaustive list of potential

factors to be weighed when doing site selection analysis. [2].

IBM has well explained documents in data center strategies. For example, how to meet a

growing need for more data center capacity, the IBM Canada Leadership Data Centre leverages

best practices developed in designing, building and operating data centers around the world. [9].

Other related work, Federico Larumbe and , Brunilde Sans`o have presentedin their work on

Cloud Location and Routing problem (CLRP) [10] formulated a. A mathematical problem that is

looking to compute geographical distribution on multiple regions, the location of data center,

servers and software components. Their results underline the importance of location and routing

showing that the budget and number of datacenters have critical impact on overall network

performance.

Khosrow Ebrahimi, Gerard F. Jones, and Amy S. Fleischer have presented a comprehensive

review of data center cooling technology, operations conditions and corresponding availability of

data center waste heat sources and stream.[11].

Other papers have been done to measureIn terms of Africa’s network connectivity, . For

example, M. Zennaro, E. Canessa, K.R. Sreenivasan , A.A. Rehmatullah and R.L. Cottrell have

used Ping methodology and obtained data to quantify the difference in performance between

developed and developing countries . [12].

Linda K. Nozick, Mark A. Turnquist has presented a model which forces to answer these

questions:, how many dData center should be in a place? Where should be located? Also, the p-

dispersion problem is closely related to this proposal. The p-dispersion problem seeks to locate p

facilities in an area or a graph such that the minimal distance between two facilities is maximized

[13].

There are other public researches on the about strategies of picking up data center locations for

Africa. In same time, there are reports about the most important factors for choosing data center

locations in United States for army and enterprise [2], [4]. Also, there are different electronic

journals that talk abouton different factors about for preventing specific locations [3].

Chapter 2

Why Africa2. Why AfricaData center in Africa is expanding fast. In 2011 alone, there were more than 20 date center

facilities began construction in several regions such as, Uganda, Reunion, Ghana, Benin,

Zimbabwe, Cameron, Angola , Burkina Faso and Kenya. Telecoms operators are bouncing on

the bandwagon, trying to capitalize on the possibility to lock in their corporate customers further,

without always recognizing the difficult road ahead. [14].

Few years ago, the world believed that all the hype and buzz that surrounding cloud computing

and data center had skipped Africa. However, developments indicate that the Dark Continent is

facing a huge demand in term of data services, but still not enough comparing to other

continents. For example, According to data center map, Africa has 32 datacenters and 18 of

which are located in South Africa. On the other hand, country like United States has 1242 data

center alone. Figure 2 and 3 show the number of data center in both Africa and counties around

the world [15]

Figure 2 shows the number of data centers in Africa

Figure 3 shows the number of data center around the world

Looking at the previous chartFigure 2 show that no wondering data center is growing business

in Africa. Internet penetration continues to increase across the continent fuelling data services

demand and lowering latency. Corporation and cloud providers are becoming aware of the

benefits of having datacenters in Africa. Outsourcing allows them to center on their core

activities, while worries about unreliable power and inadequate security can be assigned to a

dedicated third party that will guarantee the required uptime and data integrity. Finally, data

centre outsourcing offers cost savings, and a capacity to rapidly react to changing business needs.

2.1 Africa Submarine cables “Africa is surrounded by networks of submarine communications cable systems that will play a

major part in supporting the continent's future growth” [16]

For years specially equipped ships tasked with placing submarine communication cables for the

last five years. These ships have been navigating new routes off the both east and west of the

Dark Continent. These submarine cables provide high–speed, high capacity fiber optic to play

an integral part in promoting digital links that will be the backbone of Africa’s information

infrastructure for the future. Figure 4 and 5 show the submarine cable between 2010 -2012.

Figure 4 shows Submarine cables 2010

Figure 5 shows submarine cables in 2012The previous two charts figures show how fast counties and corporation in Africa to connect to

the global network. In two years the western coast of Africa jump from having two submarine

cables to five cables with capacity from 340 gigabits to 5120 gigabits. By the end of 2014,

combined service and cables capacities will exceed 67Tb/s on the west coast and 22Tb/s on the

east coast. These submarine cables reach different landing points, starting from Cape Town in

South Africa and crossing the west coast of Africa to UK. Although these landing points

countries have shore stations are located to gain most from begin physically linked. The goal of

these stations is to provide feed through and landlocked countries to enable these countries to

build their own networks and connect to the world. [16]

2.2 Geographical & Climate Characteristics of the regionGeographical factors are mostley overlooked in the process of deciding where is the best location

to build data center. Site selection is the key for most companies, not only because the companies

will save critical systems and platforms but also to keep their operations expenses on average.

However, West Africa region has combination of different geographical and climate patterns.

This project goes through these patterns characteristics because it has strong relationship with the

cost of operating data center. Hotter weather means increasing in the cost of cooling data center.

The following sections will provide an overview of these patterns:

a. Climate & topography of the continent

In general, West Africa has four climate zones, the Tropical, the Savanna, the Sahara and the

Sahel. That makes the weather ranges from lush tropical rainforest to arid desert, while in center

and few southern areas there is combination of savanna and rainforest climate. In fact, Africa

considers being the hottest continent on earth [17]. Figure 6 shows the different patterns in the

weather where it is wetter in the south and drier at north.

Figure 6. Shows wWeather patterns on Africa

b. Tornados & Hurricanes:

Hurricanes and tornadoes are both stormy atmospheric systems that have the potential of causing destruction. They are caused due to instability in atmospheric conditions. According to the region and severity of stormy conditions, these storms may be referred to as typhoons or tropical cyclones. Tornado and Hurricanes can create stress and dramatic issue for data center. For example, what happened in hurricane Katrina 2005 made huge impact on datacenters that are located in New Orleans. Prior to hurricane Katrina, the department of Agriculture moved its data center from New Orleans to Kansa City, Missouri [18]. Tornado do accrue where a

thunderstorm is possible, and there is history of places have been struck with tornados and Hurricanes [19]. Still hurricanes and tornedos are rare because they typically get weak at the cost line of weak Africa and travel west of the Atlantic Ocean.

C. Earthquake

Earthquakes occur every day around the world, but large ones and potential for future large quakes. These large earthquakes need to be taken into data center site location consideration. The west coast of Africa consider to be safer form these quakes comparing to other continents. There are countries in the west coast of Africa got hit by earthquakes, such as, Democratic Republic of the Congo and South Africa. In general, Africa as a continent has lower number of earthquakes comparing to other continents, South Africa is the spotlight of earthquakes in the continent follow by Egypt [19]. The following figure shows the major earthquakes in the world and clearly showing that Africa is totally out of the spot.

Figure 7 shows the major earthquakes in the world since 1900. [20]

D. Tsunami

Since this project is targeting the west coast line of Africa, which facing the Atlantic Ocean, Tsunami have to be consider as major threat to data center location. As 2004 tsunami that wreaked death and destruction in Indonesia, it had reach the east coast of Africa and struck Somalia, Kenya and reached South Africa [21]. East coast of Africa is out the scope but looking at the west side of the continent is the main goal. Since tsunami weaves has relationship with earthquakes the chance of tsunami in the west coast are lower than the east coast.

2.3 Politic Systems on the region

There are a variety of politics systems in West Africa. These politics system have copied itself

from Europe as a result of been colonist. The majority of these systems are using Republics with

a semi-presidential system of government like Ghana, Cape Verde, Democratic Republic of the

Congo, Guinea, Mauritania and Senegal. Other politics systems in West Africa like Federal

republics systems like what is rolling Nigeria. Another example, South Africa uses democratic

republic systems where the president is elected to serves both as head of state and as head of

government. The following figure shows the diversity of politics systems in Africa and the

world

Figure 8 shows the politics systems around the world.

Why we care about politic systems in deciding the location of datacenter

In recent decades politics systems have been collapsed and other begin taking over the rule. Changing

politics systems could change different polices that might affect somehow datacenter operations. It

could affect the cost of powering these datacenters or may affect who can use them. Also, it may affect

the privacy of these datacenter like what happened in Saudi Arabia in 2010. In 2010, Saudi Arabia

government forced RIM (Research In Motion), Blackberry service provider, to place their servers within

the country, putting them under the jurisdiction of local security force. RIM claims it does not provide any

private data to the government and their cryptographic keys are strong enough. These claims probably

true, but if a server is within a country region that’s mean it will be subject for local laws.

Another example, what called these days “Arabic Spring” which has expanded to reach other counties in

different continent, such as, Venezuela in South America. However, customers won’t host their own

sensitive data in a country has unstable systems. These politic systems add number of risk factors have

to be weighted when considering the next location for building data center facilities.

2.4 Economic status in the regionAccording to the Economic Community of West African States (ECOWAS), the economy of

West Africa region experiencing growth rate of seven per cent in 2013 compared to 6.6 per cent

in 2012 [22]. Also, this rate expected to continue its rapid growth rates to 7.4% in 2014. The

economy on west coast of Africa is driven by oil industry, mineral sector, agriculture and

services. In same time, the economy of southern Africa grows around 4% in 2013 and it continue

accelerating to reach 4.6% in 2014. Few countries are still struggling to improve their GDP such

as Angola. Meanwhile South Africa is taking over the southern region and keep growing but not

as much as Nigeria in west side.

In May 7th 2014, the world proved that Africa’s remarkable growth is projected to stay above 5

per cent in 2014 with West Africa, the fastest growing region in the continent [22]. Now Nigeria

is taking over South Africa and ranked as the biggest economy in the continent. That will make

companies look with real interest to west side of Africa considering the huge information

technology market that need to grow side by side with the economy. The following chart shows

GDP of Nigeria taking it above South Africa in the ranking of the continent’s economies by size.

Chart 9 shows the GDP Africa countries [22]

Why we care about economy in data center site location

Growing economy for data center means arability of electricity. Data center use a large amount

of electricity to run equipment. That’s why selecting location with strong and stable economy

reflect the stability of the provided services to the datacenter. Another reason is labor

availability. Strong economy means the chance of attracting more labor to the region is bigger.

The quality of these labors also might increase as reflection to the growth of the region.

Moreover, any time a company consider a capital investment projects in growing country, the

country mostly try to reduce the costs of these projects and operation costs, that have an

advantage when it comes to big projects such as building data centers.

Chapter 3The proposed Methodology

The methodology of this project is unique and has combination of different factors for different

datacenter’s owners around the global. For example, Intel has a range of factors to consider when

choosing data cementer site [24]. Their factors are related to the physical capacity of the data

center, such as, WAN infrastructure and availability of water for cooling the facility. Also they

consider other factors related to the business operations for data center, such as, costs that are

related to workforce, water power or landscape.

HP is other example of data center owner [25]. HP has its own approach when it comes to

choosing data center site location. For example, HP considers the size, price and geological

quality of the land as first matter, the availability of power and communication network in the

region. Also, the cost of these operations is matter such as, electricity, water, networking access

costs and the amount of the provided power and the chances to increase it. Also, HP considers

free cooling is considerable factor which will help to reduce the cost of operations.

Data center has to be in safe location out of any kind natural disaster or any type of threats. What

happened in Louisiana’s datacenter was a shock for information technology community. In the

same way, customers want their data to be in safe place and out of any kind of privacy

obligations like what happening in Saudi Arabia. However, since this project is dealing with

continent has lack information about technology and communications this project has to come up

with a methodology to choose a new location for data center using other datacenter‘s owners

experiences.

3.1 Decision criteria of this projectIn this project we are going to study different factors and look for location has most of these

factors. We are basically look for the following:

Environmental conditions: Is the selected location environment conditions are would

meet the minimum requirements for data center as section 2.2 explained.

Submarine cables: Does the selected location has access to 3 or more fiber optical

submarine cables as section 2.1 shows.

Power: Does the selected locations has enough and stable power to satisfy and feed the

requirements of data center. Also, is the power costs affordable?

Politically stable: Does the selected location have stable political atmosphere. Section 2.3

Network capabilities: Does the selected locations have reasonable network infrastructure.

For example, average latency and throughputs. Section 2.5

Economy: Does the selected location has stable economy? Is the economy ready to host

capital investment project such as data center? Section 2.4

All the previously mentioned factors are important in site location process. To find out which

one of West Africa counties meet the minimum requirements of these factors, we will use the

following decision criteria, figure 10, in order to eliminate undesired locations and narrow down

the possible locations. These potential locations are located in the West coast of Africa and they

are: Senegal, Guinea, Liberia, Ghana, Togo, Benin, Sierra Leone, Nigeria, Cameron, Cote

d'ivoire, Congo, Gabon, Angola, Democratic Republic of the Congo, Namibia and South Africa.

Figure 10. Shows decision criteria.

As a result for the decision criteria, there are counties have removed from begin good location to host a data center. Table 11 shows the results of decision criteria

Table 11 shows the results of decision criteria

Totally meets the requirements.

Partially meet the requirements.

It does not meet the requirements.

From the mentioned table there were countries have been eliminated because does not meet the basic requirements of hosting a data center. For example, Angola, Gabon and Cameron have

been eliminated immediately form the scope of this project because the politics status of these country are not safe to host big capital projects such as data center.

Also other counties have been removed from the scope of this project because they did not meet critical condition to host and build data center. To build a data center in any location, the location has to have average of 3 or more submarine cables to operate normally and prevent begin disconnected for any reason. So if one got disconnected, other cables should operate normally that provide stability for the provided services. For example, in the early 1990s an accident occurred at the rail yard just north of down town Sacramento, California. As a result, many other customers experienced network outage because their network provider has fiber underground and was installed along with the railroad path. The other fiber service provider was in the same trench, as result customers were also impact [24]. That show the importance of having more than one reliable fiber optical service in the selected location to grantee traffic will continue flow no matter what happen.

The results from figures 10 and 11 are the potential site locations for building a data center. The potential locations are; Senegal, Ghana, Nigeria and South Africa.

3.2 intensive Network measurement potential location As a part of this project we have to find one possible location to build datacenter in the West coast of Africa. The decision criteria in section 3.1 have left the following countries, Senegal, Ghana, Nigeria and South Africa. However, to find out this location, project will focus more on both of Network capabilities and the cost of Space, Power and cooling in these countries.

3.2.1 Network measurements The goal of network measurement is to find the performance of the countries and how they will react with global communication through fiber optical cables. Every continent has it is own performance while they communicate with the rest of the world. In this project we will measure hosts of Senegal, Ghana, Nigeria and South Africa from Linux web servers that are located in Colorado United states at North America and Singapore East Asia to find out latency, packet loss percentage and round trip time.

- Latency (delay), is an expression of how much time it takes for a packet of data to get from point to another.

- Round trip time (RTT): is an expression that measure the time that take for single packet to travel from one host to other and come back again to the sender. Also called round trip delay.

- Packet loss: is a good measure of the quality of the link for many TCP based application. It is mainly cause by congestion which in turn cause queues in routers to fill and packet to be dropped. Also it may cause by bit error in the link or in network devices.

All the previous tools are helpful when it comes to measure the performance between to hosts in a network. They help to understand where the problems are in a network and for getting details sense about the internet between hosts.

Two main utilities the project will use to measure network latency, packet loss and round trip time for the mentioned countries – the Ping and traceroute utility

- Traceroute: is a utility that record the route that packet takes through the internet between one host to other. It is also consider as debugging tool that attempt to trace the path of packet through the network.

- Ping: it is a tool to determine if a host is operating normally and its network connection are intact. It places a timestamp in packet which will send through network to practical IP address. The sender will be waiting (listing) for the return packet.

Network measurements from North AmericaThe following command illustrates how to send 10 pings, each 1,500 bytes in size, to IP address in every country listed in the table

IP address is 128.198.49.171

Table 2 shows the result of Ping IP addresses in the countries belowCountry Round trip time Packet loss Number of

Hops

Ghana 197.253.65.36 308 ms 10 % 17

South Africa 41.74.178.82

265 ms 0% 20

Senegal 41.83.255.255 182 ms 0% 17

Nigeria 41.222.211.58 182 ms 0% 18

[aalharth@walrus ~]$ ping -c 10 -s 1500 IP address

[aalharth@walrus ~]$ traceroute IP adress

Chart 4show RTT range between the 4 countries

Network measurements from East Asia (Singapore) IP address is 54.255.149.162

Country Round trip time Packet loss Number of Hops

Ghana 197.253.65.36 1073 ms 0% Over 30

South Africa 41.74.178.82

476 ms 0% Over 30

Senegal 41.83.255.255 236 ms 0% Over 30

Nigeria 41.222.211.58 274 ms 0% 21

[root@ip-172-31-10-140 //] ping -c 10 -s 1500 IP address

[root@ip-172-31-26-86 ec2-user]# traceroute IP address

Chart 5 show RTT range between the 4 countries

Network measurements from East Asia (Sydney) IP address is 54.206.48.231

Country Round trip time Packet loss Number of Hops

Ghana 197.253.65.36 1164 ms 0% Over 30

South Africa 41.74.178.82

493 ms 0% Over 30

Senegal 41.83.255.255 428 ms 0% Over 30

Nigeria 41.222.211.58 448 ms 0% 21

[root@ip-172-31-10-140 ec2-user]# ping -c 10 -s 1500 IP address

[root@ip-172-31-10-140 ec2-user]# traceroute IP address

Chart 6 show RTT range between the 4 countries

Network measurements from South America (Brazil) IP address is 54.207.65.201

Country Round trip time Packet loss Number of Hops

Ghana 197.253.65.36 1116 ms 0% Over 30

South Africa 41.74.178.82

360 ms 0% Over 30

Senegal 41.83.255.255 282 ms 0% Over 30

Nigeria 41.222.211.58 292 ms 0% 12

[root@ip-172-31-31-251 ~]# ping -c 10 -s 1500 IP address

[root@ip-172-31-31-251 ~]# traceroute IP address

Chart 7 show RTT range between the 4 countries

Observations:

Ghana: Ghana has a major problem interacting with traffic coming different zones. The results in charts 4, 5, 6 and 7 show high rates round trip time for the packets to travel for source to the destinations. Using IP address in Ghana show same results. Also Ghana show 10% loss packet multiple times.

Nigeria & Senegal: These two counties have a good average of round trip rates from different destinations comparing to other countries. The best respond for Nigeria was with packet coming from Brazil with less number of hops begin recorded.

South Africa: Average responds with higher round trip time for the packets which place this country on the third possible

More observation will be add, Such as routing observation

3.3 Estimating the Coast of Space, Cooling and Powering Data center

With the uptake of such technology, the need for efficient and cheap data centers is inherent. It is therefore of great importance to conduct a cost analysis before setting up a data center. The fundamental costs associated with a data center are the cost of electricity (power), networking infrastructure and cooling power. However, these are not the only cost associated with a complete data center, other cost such as operational maintenance, licenses, depreciation and cost of expertise are also important. For the purposes of being discrete, this project will focus

of three different costs: cost of power, cooling and space. These are the elementary cost which are estimable and can be calculated. The general model for model for the cost of a data center can be modeled using the below equation,

Cost total =Cost space + Cost power + Cost Cooling + Cost Operations

3.3.1 Nomenclature

A area of the computer room (data center) or full property Cap capitalization rate, ratio of the net operating income (NOI) to the real estate property value. Lower cap rates reflect an appreciating real estate market.

J1 capacity utilization factor, i.e. ratio of actual data center power consumption to the maximum design (rated) power consumption

K1 burdened power delivery factor, i.e. ratio of amortization and maintenance costsof the power delivery systems to the cost of grid power

K2 burdened cooling cost factor, i.e. ratio of amortization and maintenance costs ofthe cooling equipment to the cost of grid power L1 cooling load factor, i.e. ratio of power consumed by cooling equipment to thepower consumed by compute, storage and networking hardware

NOI Net Operating Income (in $), calculated as the difference between gross operating Income and actual operating costs (not including amortization and maintenance)

P power consumed by the hardware, networking or cooling equipment (Watts)R Number of racks utilized in a data centerU$,grid cost of grid power, in $/KWh or $/W per monthU$,A&M amortization and maintenance (depreciation) costs of either the power delivery or cooling equipment, in $/KWh or $/W per month

The Cost model is the aggregate of Cost of Space, Power hardware, Cooling and operations. It can be represented as follows:

Cost total =Cost space + Cost power + Cost Cooling + Cost Operations

In our example to estimate the total coast, we will assume that the facility is 30000 sq ft and occupied with 50%

3.3.2 Cost of Space

The value of real estate is estimated as the ration of Net Operating Income (Excess of Gross Operating Income over Operating Expenses) and the Capitalization rate (Like P/E rate). The capitalization rate is a representation of the ratio of current valuation to expected return.

The real estate value of commercial property is given by:-

Price Realestate = NOI / Cap rate

For a data center, however, a distinction is made between the total space, active space, and leased space However with the rate of occupancy of data centre space, the formula becomes:

Cost Space = (NOI / sq ft) (A data centre ) (% Occupancy)

(Cap rate)The average rate renting space are shown the table blew

Country Average rent (per sq ft)

Lagos, Nigeria $6.48 – 8.00

Accra, Ghana $3.7-5.1

Dakar, Senegal $ 5.5 – 7.8

Cape Town, South Africa $ 10 - 14

Average rent is

Cost Space = (NOI / sq ft) (A data centre ) (% Occupancy)

(Cap rate)

Assuming Cap rate as 10% and Operating Income as NIL, Average Rent = NOI

Country Average rent (/ sq ft) NOI

Lagos, Nigeria $6.48 – 8.00 (6.48 + 8) / 2 = 7.24

Accra, Ghana $3.7-5.1 (3.7 + 5.1) / 2 = 4.4

Dakar, Senegal $ 5.5 – 7.8 (5.5 + 7.8) / 2 = 6.65

Cape Town, South Africa $ 10 - 14 (10 + 14) / 2 = 12

TABLE - A

Country Cost Space - (A) Rate /sqft

Lagos, Nigeria (7.24 x 30000 sqft x 50%) / 0.10 = $ 1,086,000 (A)/30000= $36.2/ft

Accra, Ghana (4.4 x 30000 sqft x 50%) / 0.10 = $ 660,000 (A)/30000= $22/ft

Dakar, Senegal (6.65 x 30000 sqft x 50%) / 0.10 = $ 997,500 (A)/30000= $33.25/ft

Cape Town, SA (12 x 30000 sqft x 50%) / 0.10 = $ 1,800,000 (A)/30000= $60/ft

Chart 20 shows the coast of Space

Form the table and the graph above; it is evident that the cost of power is highest in Cape

Town followed by Lagos, Dakar and Accra in that order. If the cost of space was the only

parameter in the evaluation of the cost of a data center, then the cheapest option in this case is

Accra, Ghana. The cost of the a similar size data center cost twice as much in Cape Town, south

Africa. Thus in this situation Cape Town in South Africa is the least suitable location for a data

center facility.

3.3.4 Burdened Cost of Power Delivery

Electrical power is the heart of any data center; systems hosted by the data center require

uniquely conditioned power specifications for the m to work properly. Beyond the power

supplied by the national grid, data centers are equipped with online generators and battery back-

ups. A data center cannot afford to go offline and hence a crucial design consideration is the

redundancy of power transmission. To model the cost of power, elements such as maintenance

cost and depreciation of infrastructure responsible for power transmission and back should be

factored in.

The cost of power is therefore modeled as,

A. Cost power =U$,grid Pconsumed hardware + K1 U$,grid P consumed hardware

In addition to the Electricity cost of power from grid, is summed up with the increased cost of depreciation and amortization to call Cost of Power Delivery as Burdened cost of power delivery. K1 is the measure of the increased effective cost of power delivery due to amortization and maintenance costs associated with the power delivery system.

B. K1 = J 1 U $ , A&M Power

U$,grid

The J1 is the capacity utilization factor is calculated as:

C. J1 = Installed (Max) Capacity(Watts) = P rated

Utilised Capacity(Watts) P consumed hardware

K1 is the ratio of the realized (weighed) amortization and maintenance costs per Watt of power delivered to the direct cost of electricity (per Watt) drawn from the grid. This can be calculated on a monthly basis. J1 weighs the amortization costs by measuring the level of utilization of the conditioned space in the data center.

Combining A, B & C, the formula becomes:

Cost power =U$,grid Pconsumed hardware + U$,A&M Power P rated

U$,grid = Direct Electricity Cost

U$,A&M Power = Indirect Electricity Cost

Example:

Country Power cost KWH

Lagos, Nigeria $0.18

Accra, Ghana $0.80

Dakar, Senegal $0.42

Cape Town, South Africa $0.17

Holding all factors constant, the cost of power is highest in Accra, Ghana followed by

Dakar, Senegal, then Lagos, Nigeria and cheapest in Cape Town, South Africa. In terms the cost

of power, the most conducive city is Cape Town in South Africa while the most expensive is

Accra in Ghana. Lagos, Nigeria is not also expensive. Considering this Africa, factor such as

frequency of power outages and power surges that may lead to equipment failure should also be

factored in. Power surge inflate infrastructure cost due to the need of voltage protectors on

virtually all equipment.

Assuming 10 MW data centre and U$,A&M, power ~ U$,grid.U$,A&M, power = U$,grid.Country Power cost KWH Working - U$,A&M, power = U$,grid =

Lagos, Nigeria $0.18 ($0.18 x 24 hr x 30 days) / 106 = 130 / watt / month

Accra, Ghana $0.8 ($0. 8 x 24 hr x 30 days) / 106 = 576 / watt / month

Dakar, Senegal $0.42 ($0.42 x 24 hr x 30 days) / 106 = 302 / watt / month

Cape Town, SA $0.17 ($0.17 x 24 hr x 30 days) / 106 = 122 / watt / month

J1 = P rated / P Consumed hardware

P Consumed hardware = (Given) 50% ie 5 kwh

J1 = 10 / 5 = 2 K1 = J1 U$,A&M Power / U$,grid = 2Cost power = U$,grid Pconsumed hardware + K1 U$,grid P consumed hardwareCountry U$,grid Cost Power - (A) Rate /sqft

Lagos, Nigeria

130 / watt / month

130 x 5 + 2 x 130 x 5 = $ 1950000 / mth

(A)/30000= $65/ft

Accra, Ghana 576 / watt / month

576 x 5 + 2 x 576 x 5 = $ 8640000 / mth

(A)/30000= $288/ft

Dakar, Senegal

302 / watt / month

302 x 5 + 2 x 302 x 5 = $ 4530000 / mth

(A)/30000= $151/ft

Cape Town, SA

122 / watt / month

122 x 5 + 2 x 122 x 5 = $ 1830000 / mth

(A)/30000= $61/ft

3.3.5 Burdened Cost of Cooling Resources

Any electrical equipment that takes in power produces heat energy. Heat energy creates a

hostile environment for the operation of most electrical components. A date center has electrical

infrastructure ranging from powerful processor, routers and circuit boards. All these require a

low optimum temperature for optimal performance. Cooling these resources is the responsibility

of the cooling system. There are several types of cooling system such as air cooled systems and

water cooling system. They types of cooling system are not the subject of this paper and

therefore their discussion is limited to that already mentioned. so that the cost of cooling can be

given as:

A. Cost Cooling =U$,grid Pcooling + K2 U$,grid P cooling

The load on the cooling equipment is directly proportional to the power consumed by the computer hardware. Load factor is L1

B. P cooling = L 1 P consumed hardwareMerging A and B

Cost Cooling = (1 + K2) L1 U$,grid P consumed hardware - (1)

K2 is a representation of the amortization and maintenance costs associated with the cooling equipment per unit cost of power consumed by the cooling equipment.

C. K2 = J1 U$,A&M colling / U$,grid

Combining A, B & C as above the formula becomes finally:

Costcooling =U$,grid L 1 P consumed hardware + U$,A&M Colling J1 L1 P consumed hardware

Example:

Based on study of cooling equipment purchase and preventive maintenance costs for a10-MW data center with typical redundancies, amortization and maintenance costs for the cooling infrastructure are approximately one-half the costs incurred for the power delivery.

U$,A&M,cooling = 0.5 U$,A&M,power

Country Power cost KWH Working - U$,A&M, cooling = 0.5 U$, A&M Power =

Lagos, Nigeria $0.18 ($0.18 x 24 hr x 30 days x 0.5) / 106 = 65 / watt / month

Accra, Ghana $0.8 ($0. 8 x 24 hr x 30 days x 0.5) / 106 = 288 / watt / month

Dakar, Senegal $0.42 ($0.42 x 24 hr x 30 days x 0.5) / 106 = 151 / watt / month

Cape Town, SA $0.17 ($0.17 x 24 hr x 30 days x 0.5) / 106 = 61 / watt / month

J1 = P rated / P Consumed hardware

P Consumed hardware = (Given) 50% ie 5 kwh

J1 = 10 / 5 = 2 K2 = J1 U$,A&M colling / U$,grid

= 2 x 0.5 / 1 = 1Further, typical state-of-the art data center has a cooling load factor of 0.8, i.e. 0.8 W of power is consumed by the cooling equipment for 1 W of heat dissipation in the data center.

Cost Cooling = (1 + K2) L1 U$,grid P consumed hardware -( As (1) above)

TABLE - C

Country U$,A&M, cooling Cost Cooling - (A) Rate /sqft

Lagos, Nigeria

65 / watt / month (1 + 1) (0.8 x 65 x 5) / 106 = $ 520,000

(A)/30000= $17.33/ft

Accra, Ghana 288 / watt / month (1 + 1) (0.8 x 288 x 5) / 106 = $ 2,304,000

(A)/30000= $76.80/ft

Dakar, Senegal

151 / watt / month (1 + 1) (0.8 x 151 x 5) / 106 = $ 1,208,000

(A)/30000= $40.27/ft

Cape Town, SA

61 / watt / month (1 + 1) (0.8 x 61 x 5) / 106 = $ 488,000

(A)/30000= $16.27/ft

The cost of cooling is highest in Accra, Ghana followed by Dakar, Senegal, then Lagos,

Nigeria and cheapest in Cape Town, South Africa. In terms the cost of cooling, the most

conducive city is Cape Town in South Africa while the most expensive is Accra in Ghana.

Lagos, Nigeria is not also expensive

3.3.6 Overall Model for Data Center Cost of Space, Power and CoolingTotaling – Table A , Table B & Table CCountry Cost Space – A Cost Power - B Cost Cooling – C Total Cost =

A+B+C

Lagos, Nigeria $36.2/ft $65/ft $17.33/ft $118.53/ft

Accra, Ghana $22/ft $288/ft $76.80/ft $386.80/ft

Dakar, Senegal $33.25/ft $151/ft $40.27/ft $224.52/ft

Cape Town, SA $60/ft $61/ft $16.27/ft $137.27/ft

Cost Space Cost Power Cost Cooling Total Cost $0.00

$50.00 $100.00 $150.00 $200.00 $250.00 $300.00 $350.00 $400.00 $450.00

Over all Caost Per sq ft

Lagos, Nigeria Accra, Ghana Dakar, Senegal Cape Town, SA

Among the four cities, from estimation of cost of space, power and cooling, Lagos emerges as

the cheapest. It has a moderate real estate cost and almost the least cost power. Accra is the

cheapest in term of space but the most expensive in terms of power. Cape Town is the cheapest

in terms of power and the most expensive in terms of real estate. Dakar is somewhere in

between.

STILL Working

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