A2.1.2 Describe the purpose, benefits and limitations of modern digital infrastructures.

A2.1.2 Describe the purpose, benefits and limitations of modern digital infrastructures. 
• Modern digital infrastructure: the internet, cloud computing, distributed systems, edge computing, mobile networks 
• Examples where specific networks are used may include the worldwide web (WWW), cryptocurrency blockchains, smart traffic lights, a school.

The big idea

Modern digital infrastructures are the engineered foundations that let computation, data storage and real-time communication scale from a single device to planetary scope. They combine hardware (servers, cables, base-stations, sensors) with layered protocols and orchestration software so that end-users experience seamless, location-independent services.


Overview of the five infrastructures in the syllabus

InfrastructurePurpose (what problem it solves)Primary benefitsKey technical or socio-economic limitations
InternetProvide an open, packet-switched global network that interconnects autonomous systems using TCP/IP.Universal reach, protocol independence, innovation without central permission (“end-to-end principle”).Best-effort delivery: variable latency, congestion, no built-in security; governance disputes over routing, net-neutrality and address exhaustion (IPv4).
Cloud computingPool compute, storage and platform services in provider data-centres, accessed on demand over a network.Elastic scaling, pay-as-you-go cost model, geographic redundancy, managed security/compliance.Vendor lock-in, opaque data locality, shared-tenancy risks, latency to edge devices, high egress charges.
Distributed systemsCoordinate multiple networked nodes so they behave as a single logical service (consensus, replication, sharding).Fault tolerance, horizontal scalability, locality-aware performance, no single point of failure.CAP-theorem trade-offs, complex consistency models, increased attack surface, debugging difficulty.
Edge computingPlace compute and storage close to data-generating sources (IoT gateways, base-stations, roadside cabinets).Millisecond-level latency, bandwidth savings by pre-processing data locally, resilience when backhaul fails, privacy by locality.Constrained resources, heterogeneous hardware, management complexity at thousands of small sites, physical tampering/environmental hazards.
Mobile networksProvide ubiquitous wireless access via cellular radio (4G/5G) and mobility management across cells.True mobility, wide coverage, integrated authentication and QoS classes, rapid deployment via spectrum reuse.Spectrum scarcity, handover interruptions, indoor coverage gaps, dependence on licensed operators, energy consumption of radio access network.

Illustrative scenarios

ScenarioUnderlying infrastructure(s)Explanation
Worldwide Web (WWW)Internet + (optionally) Cloud computingHTTP(S) sessions between browsers and web servers ride the public Internet; most large sites scale by hosting front-end instances and databases in cloud regions.
Cryptocurrency blockchain (e.g., Bitcoin)Distributed systems + InternetFull nodes distributed worldwide reach consensus (proof-of-work or proof-of-stake) and replicate an append-only ledger; peer traffic flows across the Internet.
Smart traffic-light networkEdge computing + Mobile networks + InternetRoadside controllers run inference at the edge using sensor feeds; 5G or LPWAN backhaul reports telemetry to a municipal cloud dashboard; fall-back to local timing if WAN fails.
Typical schoolCloud computing + Internet + (on-prem) LANs + Mobile networks (BYOD)Learning-management systems and email are SaaS; wired/wireless LAN connects labs; students’ tablets join via Wi-Fi or cellular; content filters mitigate Internet risks.

Synthesis

Modern infrastructures are complementary layers of the same ecosystem:

  • Internet supplies the universal routing fabric.
  • Cloud concentrates heavy workloads; edge pushes latency-critical functions outward.
  • Distributed systems give both cloud and edge the reliability and scale students and faculty expect.
  • Mobile networks extend reach to any handheld device in motion.

Designers balance benefits (elasticity, reach, low latency) against limitations (cost, consistency, security) to meet each application’s performance, reliability and ethical requirements. A clear grasp of these trade-offs enables you to reason about why, for example, an autonomous car company would fuse edge inference with cloud-based fleet learning, or why a school still needs a resilient on-site network despite moving its email to the cloud.