Refer to the exhibit. Approximately 4000 oil platforms, each with 400 sensors, are spread in the Gulf of Mexico and all of their data must come together into one dashboard. Which general architecture

Question

Exhibit

Options

• A4-tier: sensor - edge device (Intel Atom CPU) - fog device (Intel Xeon CPU) - cloud
• B5-tier: intelligent sensor- edge device (Intel Atom CPU) - fog device (Intel Xeon CPU) - edge
• C2-tier: intelligent sensor - cloud
• D3-tier: sensor - edge device (Intel Atom CPU) - cloud

• A
  5% (2)
• B
  65% (24)
• C
  11% (4)
• D
  19% (7)

Explanation

Option B is correct because the massive scale - 4,000 platforms × 400 sensors = 1.6 million data sources - demands a 5-tier hierarchy to progressively filter and aggregate data before it reaches the cloud dashboard; intelligent sensors pre-process locally, Atom-based edge devices aggregate per platform, Xeon-based fog devices handle regional consolidation, and a final edge tier buffers before cloud ingestion.

Option A is wrong because it uses dumb "sensors" instead of intelligent ones, missing local pre-processing at the source tier, and 4 tiers is insufficient for this data volume.

Option C is wrong because a 2-tier direct-to-cloud approach would overwhelm bandwidth and cloud compute - streaming 1.6 million raw sensor feeds simultaneously is not feasible at scale.

Option D is wrong because 3 tiers skips the fog layer, forcing too much unprocessed data to travel all the way to the cloud, and again uses non-intelligent sensors.

Memory tip: Scale = tiers. The larger and more distributed the sensor network, the more intermediate processing layers you need. Think of it as a funnel - intelligent sensors at the wide end, each layer narrowing the data flow before it reaches the cloud.

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