FRAMEWORKC FOR SELECTING DATA CENTER

FRAMEWORKC FOR SELECTING DATA CENTER Last Update: Tuesday, January 28, 2014 Committee Members and Signatures: Ahmed Alharthi s Master Project Proposal Approved by Date Project Advisor: Dr. Edward Chow Member: Dr. Jia Rao Member: Dr. Kristen Walcott-Justice

1. Introduction This project proposal report gives a description of the research and process which will be undertaken in delivering a research paper to the management of Amazon EC2 on factors which have been analyzed when considering the best location for the Company to base its new data center away from its regular locations [1]. The paper will mainly analyze regions in Africa and the Middle East, regions within which the Company does not have a single data centre. The final research paper will consist of two documents and a program that will be used in collect data which will be critical in arriving at the best possible location for the data center. 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. There are different factors considered when answering this question including facilities, the efficiency of operations of the center and cost factor which among the three is the most important element and which 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 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 both Africa and the Middle East. This project will attempt to produce a detailed list of the most important factors [2], [3], [4]. In this project, we will discuss the various risk factors that may impact data centers especially the geography in Africa and the Middle East. Similar cases, such as the geographic advantage of choosing Colorado 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 Amazon EC2 Global Infrastructure Amazon EC2 has nine regions and forty two edges around the globe, but it can be seen clearly from figure 1 that there are no data center facilities on the African or Middle East regions, and that is because of the lack of data availability on these regions. As result, Africa and the

Middle East have fewer options to communicate efficiently with the Amazon infrastructure. The mentioned regions have more latency and higher power costs consumption when it comes to interact with Amazon EC2 environments. In this research we intend to suggest new data center locations for Amazon EC2 in both Africa and the Middle East. Figure 1. Amazon EC2 global infrastructure [1] 1.2 Related work On related work, the paper will analyze the presence of any previous work undertaken concerning the suitability of locating data centers in Africa or the Middle East regions. This data will come in handy since it gives a preview of what has already been researched and what needs to be researched further. Critical issues and factors which need to be analyzed when determining the location of data centers will also be researched, by evaluating work done on factors to consider when deciding the bet location for data centers. Research on related work will span different regions, factors to consider, mitigating risks and also methods of undertaking such kinds of research.

There are few public researches about strategies of picking up data center locations for Africa and Middle East. In same time, there are perfect 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 about different factors about preventing specific locations [3]. 2. Problem description There is lack of sufficient research and information regarding Africa and the Middle East regarding possible best locations in which data centers can be put up to aid in the globalization movement that has led to ease of doing business and world trade [5]. For this reason, this research paper will focus on Africa and the Middle East and analyze and evaluate the following countries with an aim of proposing the best location for Amazon EC 2 to base its data center within these two geographical regions: Africa: Senegal, Guinea, Liberia, Ghana, Togo, Benin, Nigeria, Cameron, Congo, Angola, Democratic Republic of the Congo, Namibia, south Africa, Mozambique, Tanzania, Kenya, Somalia and Madagascar. Middle East counties: Yemen, Oman, and Saudi Arabia. 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 a major internet and communication infrastructure [6]. Furthermore, Amazon EC2 has requested an in depth evaluation of these countries since it plans on having a data centre in these parts of the world to help the company with its service delivery and expansion plans into new markets and regions. 2.1 Targeted audience The targeted audience for this research is the management at Amazon EC2. They are planning to expand their operations into new regions and based on their current market presence as shown in the map of the Company s global infrastructure, the Company does not have data centers in Africa and the Middle East. The senior management at Amazon EC2 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. The report will also be analyzed by technical teams of Amazon EC2 who will assist the senior management in deciding on the best location to base their new data center within this new region of operation. Although the paper will give a clear and precise location of the most suitable location, the final decision on where the data center will be located will lie with the senior management assisted by the Company s technical teams. 3. Research Plan The research will involve analyzing the following two factors; natural disasters and weather and workforce and business climate [7], [8]. On natural disasters and weather, research will dwell on the following specific areas that determine the suitability of a location for building a data center: Geological factors Hydrological factors Un-natural disasters Marine cables Hypothetical future disasters On Workforce and business climate factors, the location of a business center is determined by numerous factors. Some of the critical factors include literacy levels of the local population, government regulations such as tax and ease of doing business in that specific country. Other factors include political atmosphere and other costs of doing business in a country. These factors will have to be evaluated critically for a location to be chosen as the main location for Amazon EC2 s next data center outside its main locations. 3.1 Methodologies and technology There are numerous methods for collecting and analyzing data when deciding on the location for a particular project [9]. In this case, the data has to be collected from the departments and government agencies that have collected data on geological, hydrological, un-natural and

hypothetical future disasters for the specific countries listed above. Data can also be collected from previous research done within these countries, data not necessarily connected with the determination for the location of a data center. This can be data collected for building projects or determination of seismic activity and impact of weather patterns. Data from well established international organizations such as Google maps will be used to map out potential locations for the establishment of a data center [10]. Data will be analyzed through the program developed for this project which will evaluate specific factors based on the criterion of choosing the best possible location where a data center can be located [11]. The program will be developed in such a way that it is able to analyze huge quantities of data since the countries under evaluation are numerous spanning different areas and containing diverse cultures and environments. For instance countries in the Middle East are mostly desert countries, while some countries in Africa have very wet conditions. As for technologies use, the internet will play a critical role in collection and analysis of data. Different software and programs will be used to collect and analyze data as well taking in mind the fact that the countries under analysis are in different parts of the world and different researchers will be posted in different regions and the most critical aspect of the research will be to have the data collected and analyzed in real time or in limited durations of time so as to save the time required to complete the research and also give Amazon EC2 the opportunity to establish a data center within the stated regions within a limited period of time so as to compete favorably with its competitors. 4. Schedule and Tasks - Research done during Fall 2013 1. Research economical, costs and characteristics of different countries. 2. Research the basic needs of establishing data center facilities. 3. Research the most reliable marine cables such as, South Atlantic Express (SAEx), Atlantis-2, SAFE, South Atlantic Cable System (SACS), SAT-3/WASC, SEACOM/Tata TGN-Eurasia, FLAG Europe-Asia (FEA), The East African Marine System (TEAMS) and others more [12].

4. Research all the related information for every marine cable such as, cable length, owners, landing points and design capacity [13]. 5. Estimating and calculation distances between different data centers and edges. 6. Read about common data center facilities. - In Progress - Work during Spring 2014 1. Research on different locations, facilities and edges. 2. Collect existing information, facts, and considerations about picking up locations. 3. Research the most important consideration factors for choosing locations. 4. Perform simulation for choosing data center locations for Amazon EC2. 5. Report the process of the research with all explanations, facts, implementations, experiments, and so on. 6. Design a program that helps to search and manage these data. 5. Deliverables The deliverables for this project will include two written documents and a program. The first document will include the research undertaken on the countries listed above. This will include the evaluation of all the factors that have been set out as the main factors to consider when deciding on the best location to set up the data centre. Document two on the other hand will apply the results of the first document and suggest the final location for setting up the data center for Amazon EC2. A program that will manage all the data analyzed by the first document will be designed for the purpose of helping with data analysis and storage. There are numerous programs which are developed to analyze collected data when making decisions on implementation of new projects such as in the medical field [14].

6. References [1] Amazon Web Services. (2014). Global Infrastructure. Retrieved from http://aws.amazon.com/about-aws/globalinfrastructure/ [2] Rath, John. DATA CENTER SITE SELECTION. Tech. N.p.: n.p., n.d. Print. [3] "BlackSwan Zine." Data Center: 10 Places You Don t Want to Build. Blackswanzine, 2010. Web. 2 Jan. 2014. [4] Chang, Shin-Jyh Frank, Susmit Harihar Patel, and James Marc Withers. "An optimization model to determine data center locations for the army enterprise."military Communications Conference, 2007. MILCOM 2007. IEEE. IEEE, 2007. [5] Henry, C. M., & Springborg, R. (2010). Globalization and the Politics of Development in the Middle East (Vol. 1). Cambridge University Press. [6] Agrawal, G. P. (2010). Fiber-optic communication systems (Vol. 222). John Wiley & Sons. [7] Linnenluecke, M., & Griffiths, A. (2010). Beyond adaptation: resilience for business in light of climate change and weather extremes. Business & Society, 49(3), 477-511. [8] Doeringer, P. B., & Terkla, D. G. (1995). Business strategy and cross-industry clusters. Economic Development Quarterly, 9(3), 225-237. [9] Robson, C. (2002). Real world research: A resource for social scientists and practitionerresearchers (Vol. 2). Oxford: Blackwell. [10] Stanton, J. M., & Rogelberg, S. G. (2001). Using internet/intranet web pages to collect organizational research data. Organizational Research Methods, 4(3), 200-217. [11] Hand, D. J. (2007). Principles of data mining. Drug safety, 30(7), 621-622. [12] "Submarine Cable Map." Submarine Cable Map. N.p., n.d. Web. 11 Nov. 2013. [13] "Submarine Cable." Submarine Cable. N.p., n.d. Web. 25 Dec. 2013. [14] Liu, C. L., Prapong, W., Natkunam, Y., Alizadeh, A., Montgomery, K., Gilks, C. B., & van de Rijn, M. (2002). Software tools for high-throughput analysis and archiving of immunohistochemistry staining data obtained with tissue microarrays. The American journal of pathology, 161(5), 1557-1565.