TECH2100 Information Networks - Network Design, Critical Analysis & AI Ethics : Study Guide + Solved Answer
If you're working through TECH2100 Information Networks, this guide is built for you. It covers everything in Assessment 1 - from designing a multi-layered OSI/TCP-IP network for a financial consulting firm, to critically analysing its performance, solving a real-world hardware/software upgrade scenario, and tackling the ethical implications of deploying generative AI in network environments. You'll find a full solved answer below, drawn directly from a submitted student response, with light grammar smoothing only.
Don't just read the solved content passively. Use this guide to understand how marks are actually earned - which frameworks to name, which citations to use, and where most students lose points. By the end, you'll know exactly what the marker is looking for and how to structure your own response with confidence.
Assessment Overview
Assessment for TECH2100 requires you to act as a network consultant designing and analysing a network for a financial consulting firm. The assessment is broken into four interconnected tasks covering design, critical analysis, scenario-based problem solving, and ethical reasoning around generative AI use.
- Task 1 - Network Design Architecture: Design a full network using OSI and TCP/IP models, justify hardware and protocol choices (~600-800 words)
- Task 2 - Critical Analysis: Analyse strengths, weaknesses, and causes of transmission rate fluctuations, then propose improvements (~400-500 words)
- Task 3 - Scenario-Based Problem Solving: Recommend hardware/software upgrades for an underperforming network (~300-400 words)
- Task 4 - Ethical Considerations of Generative AI: Identify ethical implications and risk mitigation strategies for deploying AI in network communications (~300-400 words)
- References: APA 7 format, minimum 8-10 peer-reviewed or credible sources
- Formatting: Professional report structure with headings, subheadings, and numbered sections
- Submission: Via the course LMS portal as a single .docx file
NETWORK DESIGN ARCHITECTURE
Network Design
The OSI model gives a framework to design as well as implement network architectures. The physical layer handles the actual transmission of raw data over physical hardware. Fiber optic cables play essential role in modern network design. These cables are essential for core connectivity that links devices including core switches, routers and data centers. These cables can handle high speed and high volume communication over long distance with minimal latency.
For financial consulting firm's network, within LAN fiber optic cables can be used to connect core switches for handling high volumes of internal traffic. Within LAN, devices such as PCs are connected to an access switch using Cat6 Ethernet cables, and then access switches are connected to core switches through fiber optics.
The data link layer is responsible for node to node data transfer and error detection. VLAN is a logical grouping of physical network that enables segmentation based on user group or department. It improves network security, performance and flexibility.
The network layer is responsible to reach data packets to their destination using IP addressing. Routers connect LAN and WAN using routing protocols such as OSPF and BGP (Kaur et al 2023). Firewalls inspect and filter traffic.
The transport layer ensures reliable data transfer using TCP and UDP. The session layer manages sessions, while the presentation layer defines data format and encryption.
The TCP/IP model includes network interface, internet, transport and application layers. Ethernet is widely used in LAN, while point to point protocols are used in WAN connections.
Tip: Clearly link each OSI layer to real devices - this is where most students lose marks.
"Fiber optic cables can handle high speed and high volume communication over long distance with minimal latency."
CRITICAL ANALYSIS
The design provides high performance due to fiber optic usage, enabling applications such as video conferencing and real time analytics. Scalability is supported through star topology and routing protocols such as OSPF and BGP (Zhu et al 2023). Security is ensured through firewalls and secure protocols.
However, cost is a major limitation due to expensive infrastructure. Complexity also increases with VLANs and routing protocols. A single point of failure may occur at the central switch.
Fluctuating data transmission can occur due to damaged cables or overloaded switches. Link aggregation can improve bandwidth and fault tolerance, while SD-WAN enables dynamic traffic control.
Tip: Always balance strengths with technical limitations - markers look for evaluation, not description.
"The use of fiber optic cables help to achieve high speed data transmission with minimal latency."
SCENARIO-BASED SOLUTION
Networking hardware can be upgraded using high performance switches such as Cisco Catalyst 9000 series and Aruba CX switches. Routers such as Cisco ISR 4000 series provide advanced traffic management.
SD-WAN improves WAN performance by dynamically selecting best paths. QoS policies help prioritise traffic, and DHCP enables efficient IP allocation.
Software defined networking helps manage traffic centrally using controllers such as Cisco ACI and VMware NSX.
Tip: Use real product examples - it shows applied knowledge and boosts marks.
"SD-WAN enables dynamic path selection based on network conditions and improves reliability."
ETHICAL CONSIDERATIONS
Generative AI improves automation and decision making but introduces ethical issues such as privacy, security and bias (Zhu et al 2023). Training AI on network data may expose confidential information (Madavarapu et al 2023).
Bias in AI models can result in unfair treatment, and lack of transparency reduces trust. To address risks, organisations should implement data anonymisation and comply with GDPR or CCPA.
Explainable AI improves transparency, while diverse datasets reduce bias (Van Huynh et al 2024). Regular audits are essential (Liu et al 2024).
Tip: Always connect ethical issues with real mitigation strategies.
"Generative AI models are working as black boxes that lead to difficulties in understanding their decisions."
Want the Full Solved Solution for TECH2100 Information Networks assessment?
This guide covers the key solved sections. The complete solution includes all four task areas, fully formatted in-text citations, APA 7 reference list, network design rationale, and the full ethical analysis with mitigation strategies.
How to Score High in TECH2100 Information Networks Assessment
- Map every hardware and protocol choice explicitly to an OSI or TCP/IP layer - don't just describe the device; explain which layer it operates at and why
- Use specific product names (Cisco Catalyst 9000, Juniper MX series, Aruba CX) rather than generic terms like 'managed switch' - specificity signals applied knowledge
- Cite academic sources for every major technical claim - Edwards et al. (2015) for fiber optics/OSI, Kaur et al. (2023) for routing protocols, Zhu et al. (2023) for scalability
- In the critical analysis, go beyond listing strengths and weaknesses - show you understand the trade-offs (e.g. high performance comes with cost and complexity)
- Address the single point of failure in star topology directly and propose redundancy solutions - this shows awareness of real-world network resilience concerns
- In the scenario task, name both the hardware and the reason for the recommendation - 'Cisco ISR 4000 because it supports advanced QoS and BGP' scores far higher than just 'upgrade the router'
- For the AI ethics task, match each risk to a specific mitigation - privacy risk → data anonymisation + GDPR compliance; bias risk → diverse training data
- Reference GDPR and CCPA by name in the ethics section - these are industry-standard regulations and their inclusion signals real-world awareness
- Use formal report structure throughout: numbered headings, subheadings, professional prose paragraphs - no bullet points in the main body of your submission
Why Students Struggle With This Assessment
- Describing layers without justifying hardware choices. Most students can list the OSI layers, but lose marks when they don't connect each layer to a specific device or protocol decision. Fix: For every component you include, state which OSI/TCP-IP layer it belongs to and why it's the right choice for that layer.
- Weak critical analysis that reads as a summary. Writing that a design has 'good performance' or 'some weaknesses' doesn't demonstrate critical thinking. Fix: Be specific - state that fiber optic cables enable 100 Gbps throughput with zero EMI interference, or that a central switch creates a single point of failure requiring redundancy planning.
- Vague improvement recommendations. Saying 'upgrade hardware' or 'improve security' is not a recommendation. Fix: Name the technology (SD-WAN, NGFW, link aggregation), explain the mechanism by which it improves performance, and cite a source.
- AI ethics treated as an add-on. Many students produce a generic list of AI risks without contextualising them in a network or financial services environment. Fix: Tie every risk to a network-specific scenario (e.g., training on network traffic reveals financial transaction data) and tie every mitigation to a regulatory standard.
- Missing or inconsistent citations. Using in-text citations sporadically - or not at all for technical claims - costs significant marks. Fix: Every claim about protocols, hardware performance, or AI behaviour should have a supporting citation in APA 7 format.
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Frequently Asked Questions
Q: What is Assessment 1 actually asking me to do?
A: You're acting as a network consultant for a financial services firm. Your job is to design a complete network (LAN + WAN) using OSI and TCP/IP models, critically evaluate its strengths and weaknesses, recommend hardware/software upgrades for a real-world scenario, and address the ethical implications of deploying generative AI in that network environment. It's a four-part report, not four separate essays - your analysis should build on your design.
Q: How many references do I need, and what format?
A: Aim for a minimum of 8-10 references in APA 7 format. Your sources should include peer-reviewed journal articles for technical claims (OSI model, routing protocols, fiber optic performance) and credible industry sources or academic texts for AI ethics. Don't pad your reference list with random citations - every source should support a specific claim in your report.
Q: Can I use generative AI tools to write my answer?
A: Check your course's specific academic integrity guidelines. Most institutions require disclosure of AI tool use and prohibit submitting AI-generated text as your own work without substantial transformation and attribution. Ironically, given that this assessment includes an entire task on the ethical implications of generative AI, your marker will be particularly alert to AI-generated responses. Write in your own voice, use your own analysis.
Q: Do I need to draw an actual network diagram?
A: Yes - the assessment typically expects a visual network diagram showing your LAN and WAN topology, including device placement, connection types, and protocol labelling. Tools like draw.io or Cisco Packet Tracer work well. Your written content should describe and justify what is shown in the diagram, not repeat it verbatim.