CP5631 Networking Case Study: Network Redesign and Cloud Proposal

This case study focuses on redesigning the network for a data analytics company, XYZ, expanding its operations to Osaka and San Francisco. The project involves assessing the existing network, implementing VLSM subnetting to accommodate new offices, and proposing a cloud computing solution for enhanced security, scalability, and cost-effectiveness. The solution includes a network topology diagram, subnetting tables with IP address assignments, and a hardware resource requirements analysis using a weighted decision matrix. The case study also explores the feasibility of cloud computing, comparing in-house and cloud-based solutions, and recommends a shift to thin clients connected to the cloud to reduce operational costs and improve data security. Desklib is your go-to for more solved assignments and past papers.

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Student Name
Student ID
Course
Instructor
ateD

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PART 1 - Executive summary
An Australian based data analytics company, XYZ, opening new branch offices on
Osaka and San Francisco. These offices require new equipment and thus there is need to
redesign the existing network so as to meet the new requirements. The project is aimed at
ensuring that all the branches are able to access real time data without delay. As such network
redesign is necessary in order to ensure that every user is able to work independently on the
shared network. The new network will ensure reliability, efficiency, security of the data and
information, and scalability (Kuipers, 2012, p. 18). This are the major aspects that every
network should meet. XYZ is a company that deals with data analytics and data is a very
fragile and critical resource, therefore, security, privacy, and confidentiality is key.
The network will be able to meet these aspects. The main objective of the project is to
assess and redesign the existing network so as to meet the new requirements as the company
grows, that is, allow the new offices to access the network resources efficiently and
effectively. Secondly, the network should ensure that communication is effective and reliable.
Thirdly, sharing of resources (Mbale & Mufeti, 2011, p. 1). Fourthly, is load balancing to
provide a way to increase the overall system performance, and finally to allow only
authorized users to access the network.

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PART 2 - Network specifications and topology diagram

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Figure 1: Network Diagram

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PART 3 - Subnet the network using VLSM, and assign IP addresses
Table 1. Subnets
Subnet name Subnet
address
Subnet
mask
First useable
address
Last useable
address
Broadcast
address
Static address range DHCP address range
Seattle 172.10.0.0 /20 172.10.0.1 172.10.24.254 172.10.24.255 172.10.0.1-172.10.0.2
172.10.0.3 -
172.10.24.254
Hong Kong 172.10.15.0 /21 172.10.15.1 172.10.33.254 172.10.33.255 172.10.15.1
172.10.15.2 -
172.10.33.254
Osaka 172.10.95.0 /22 172.10.95.1 172.10.37.254 172.10.37.255 172.10.95.1
172.10.95.2-
172.10.37.254
Seoul 172.10.38.0 /22 172.10.38.1 172.10.21.254 172.10.21.255 172.10.38.1
172.10.38.2-
172.10.21.254
Vancouver 172.10.22.0 /23 172.10.22.1 172.10.23.254 172.10.23.255 172.10.22.1
172.10.22.2 -
172.10.23.254
San Francisco 172.10.98.0 /25 172.10.98.1 172.10.98.126 172.10.98.127 172.10.98.1
172.10.98.1 -
172.10.98.126
Seoul_Server
172.10.98.12
8 /29 172.10.98.129 172.10.98.134 172.10.98.135
172.10.98.129-
172.10.98.131
172.10.98.132-
172.10.98.134
Osaka_Server
172.10.98.13
6 /29 172.10.98.137 172.10.98.142 172.10.98.143
172.10.98.137-
172.10.98.139
172.10.98.140-
172.10.98.142
WAN SEO-Hong
Kong
172.10.98.14
4 /30 172.10.98.145 172.10.98.146
172.10.98.145-
172.10.98.146
WAN SEO-Seattle
172.10.98.14
8 /30 172.10.98.149 172.10.98.150
172.10.98.149-
172.10.98.150
WAN SEO-Osaka
172.10.98.15
2 /30 172.10.98.153 172.10.98.154
172.10.98.153-
172.10.98.154
WAN SEA-
Vancouver
172.10.98.16
0 /30 172.10.98.161 172.10.98.162
172.10.98.161-
172.10.98.162
WAN SEA-San
Francisco
172.10.98.16
4 /30 172.10.98.165 172.10.98.166
172.10.98.165-
172.10.98.166
WAN SAN-
Vancouver
172.10.98.16
8 /30 172.10.98.169 172.10.98.170
172.10.98.169-
172.10.98.170
Table 1: Subnet Table

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Table 2. Router Interfaces
Location Interface IP address Subnet mask
Seoul
S0/0 104.200.16.26 /30
S0/1 172.10.98.153 /30
S0/2 172.10.98.149 /30
S0/3 172.10.98.145 /30
Fa 0/0 172.10.38.1 /22
Fa 0/1 172.10.96.129 /29
Hong Kong S0/0 172.10.98.146 /30
Fa 0/0 172.10.15.1 /21
Seattle
S0/0 172.10.98.150 /30
S0/1 172.10.98.161 /30
S0/2 172.10.98.165 /30
Fa 0/0 172.10.0.1 /20
Vancouver
S0/0 172.10.98.162 /30
S0/1 172.10.98.170 /30
Fa 0/0 172.10.22.1 /23
San Francisco
S0/0 172.10.98.166 /30
S0/1 172.10.98.169 /30
Fa 0/0 172.10.98.1 /25
Osaka
S0/0 172.10.98.154 /30
S0/1 172.10.98.157 /30
Fa 0/0 172.10.95.1 /22
Fa 0/1 172.10.96.137 /29
Table 2: Router Interfaces
Table 3. Servers
Location Server name IP address Subnet mask
Osaka DB 172.10.96.138 /29
USER 172.10.96.139 /29
Seoul WEB 172.10.96.130 /29
MAIL 172.10.96.131 /29
Table 3: Servers

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PART 4 - Research and source appropriate devices justifying choices
Executive summary
The devices being planned to be procured include two routers for Tokyo and Osaka,
switches for every LAN and one for the servers located in Osaka, two servers (User and DB
located in Osaka), and 200 PCs (150 for San Francisco and 50 for Osaka). The most critical
devices amongst are the servers because of the critical and vulnerable resource, data for XYZ
data analytics company which hold a lot of data for clients (Di Corato, 2013). Data analysis is
a very essential process and requires a computer with relatively high performance especially
the processor, hard disk, and RAM. Finally, it is important to consider affordable but reliable
devices.
Weighted Decision Matrix – Hardware resource requirements analysis.
The weights below apply for all the devices.
0 The scenario does not require the requirements
1 The requirements are not very essential
3 The requirements should be met
5 The requirements are very critical
0 The requirements have not been met totally
2 The requirements have been met partially
4 All the requirements have been met
6 The requirements have been met and surpassed
Router
Requirements
Requirement Description Weight
Speed 1000MBPS transfer speed 5
Price Not more than $400 1
Firewall Should be available 3
Ports Minimum of 2 ports and 4 ports respectively 3
Details
Model Ports Speed (Mbps) Cost ($) Firewall
Cisco RV325 16 1000 545 yes
Net Gear FVS336G 2 1000 350 Yes
Cisco RV042-AU 4 100 185 no

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Linksys LRT214-AU 6 1000 215 Yes
Cisco RV042G-K9-AU 4 1000 300 Yes
Weight Score
Requirement No. Ports Speed (Mbps) Cost ($) Firewall Total weight score
Description >=4 >=1000 <400 Yes
Weight 3 5 1 3
Cisco RV325 6 4 0 4 50
Net Gear FVS336G 0 4 4 4 36
Cisco RV042-AU 4 0 4 0 16
Linksys LRT214-AU 6 4 6 4 56
Cisco RV042G-K9-AU 4 4 4 4 48
Switch
Requirement
Requirement Description Weight
Cost <4500 for all 3
Speed 100M 3
Port number >=16 5
Manageable Yes 1
Details
Model No. Ports Speed (Mbps) Cost ($)/per device Management
Cisco SF 200E-24P 24 10/100/1000 387 Yes
HP J9981A 1820-48G 48 10/100 540 Yes
Cisco SF 100-24 24 10/100 105 Yes
Cisco SF 100D-16 16 10/100 80 No
D-Link DGS-1100-24 24 10/100/1000 200 Yes
Need number = 150/port number + 80/port number + 1 (for the main switch)
Weight Score:
Requirement No. Ports Speed (Mbps) Cost ($) Management Total weight score
Description >=16 >=100 <4500 Yes
Weight 5 3 3 1
Cisco SF 200E-24P 4 4 0 4 36
HP J9981A 1820-48G 6 6 2 4 52
Cisco SF 100-24 4 4 4 4 50

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Cisco SF 100D-16 4 4 6 0 50
D-Link DGS-1100-24 4 6 4 4 54
Server
Requirement
Requirement Description Weight
Cost < 3500 $ 1
CPU >= quad core 5
RAM >=16GB 5
Network Controller 1000Mbps 3
Details
Model
Cost($
) Processor
Memor
y Network Controller
Lenovo 5457C5M x3100
M5 1800 Intel quad Core-3.4 GHz 8GB Gigabit Ethernet
HP ProLiant ML10 1599 Intel Xeon-3.1GHz 8GB HP Ethernet 1Gb 2-port
332i Adapter
LENOVO x3100 1750 Intel Xeon quad Core-3.1
GHz 16GB Gigabit Ethernet
Cisco UCS C220 M3 SFF 899 Intel E5-2620v2(6 Core)
-2.10 GHz 32GB Ethernet 1Gb
HP 778641-B21 DL80
Gen9 3099 Intel Xeon 6 core-1.9 GHz 16GB Ethernet Adapter -1Gb 361i
Weight Score
Requirement
Cost($
) Processor
Memor
y
Network
Controller
Total weight
score
Description
<=350
0
>= quad
Core >=16G >=1000Mbps
Weight 1 5 5 3
Lenovo 5457C5M 6 4 0 4 38
Cisco UCS C220 M3 4 6 6 4 76
HP 778641-B21 4 6 4 4 66
HP ProLiant ML10 6 0 0 4 18
HP J9981A 1820-
48G 6 4 4 4 58

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Computer
Requirement
Requirement Description Weight
Cost <= 1500 $ 5
CPU >= core i7 5
RAM >=8GB 3
ROM >=500GB 3
Details
Model
Cost($
) Processor Memory Storage
Intel core i7 6600
Turbo Pack 750 Core i7 quad core 3.3GHz 8GB 1TB
Umart ASUS Vivo 659 Asus VM62-G039M 8GB 500GB
Intel i7 6700 Extreme
Pack 1350 Intel Core i7 6700 Quad
Core 3.4GHz 16GB 2TB
Intel XEON
workstation 3599 Intel Xeon E5-2630v3 CPU
- 2.4Ghz 16GB 2 x Hitachi 1TB
Intel Core i3 4170
Value Pack 599 Intel Core i3 4170 3.6Ghz 4GB 500GB
Weight Score:
Requirement Cost($) Processor Memory Storage Total weight score
Description <=1500 >=i7 >=8GB >=500G
Weight 5 5 3 3
Intel i7 6600 Turbo
Pack 4 4 6 6 76
Umart ASUS Vivo PC
Pack 6 4 4 4 74
Intel i7 6700 Extreme
Pack 4 6 6 6 86
Intel XEON CAD
Workstation 0 6 6 6 66
Intel Core i3 4170
Value Pack 6 0 4 4 54
Budget Summary
Item No Item Quantity Price ($) Total Cost ($)

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1 Router-Linksys LRT214-AU 2 215 430
2 Switch-D-Link DGS-1100-24 6 200 1200
3 Sever- Cisco UCS C220 M3 SFF
2xE5-2620v2 2x 2 899 1798
4 PCs- Intel i7 6700 Extreme Pack 10 1350 13500
TOTAL BUDGET 16,928
The budget set out for this project was $10,000 but based on the requirements and the needs
of the new offices the budget have exceeded by $6,928. However, this cost is worth it
because affordable, more reliable, and secured devices have been selected. Thus, over time
there is minimal maintenance required on these devices.

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PART 5 – Cloud computing proposal
Currently, there are several cloud service providers around the world like Amazon,
Alibaba, Microsoft Azure, Google, and many others can choose from. Cloud computing offer
centralized access to resources and the company will not have to worry about the
management of resources (Hoque & Gupta, 2012, p. 29). Replacing all workstations with thin
clients connect to the cloud reduces operational costs by a big margin. Thin clients are
computers that connected to a network with no local storage. Thin clients run virtual desktops
using virtualization technologies from Citrix, Microsoft, and VMware in remote servers,
either in-house or outsourced (Karyakina & Melnikov 2017, p. 253). Shifting to cloud
computing using thin clients reduces the costs, enhance data security, improve overall
performance, reduces energy consumption and cuts power costs by up to 80%, and offer
efficient and effective remote management (Wickboldt et al., 2015, p. 281). The table below
give a comparison of the three scenarios in order to make a recommendation: