1. Describe Benefits of Edge Computing 200-901 Practice Questions (Page 5)

Questions 21–25

1. 21application · medium

   A mining company operates remote equipment in an area with intermittent connectivity. The equipment must continue to operate safely when the connection to the central office is lost. Which edge computing benefit is most directly applied in this scenario?

   • ALower latency for real-time control.
   • BIncreased data storage capacity at the edge.
   • CImproved reliability through local autonomy.
   • DReduced bandwidth usage by sending only summaries.
   Reveal Solution Discussion Select an answer first
2. 22application · medium

   A logistics company uses GPS trackers on delivery vehicles. The trackers send location updates every second to a central cloud, consuming significant cellular bandwidth. The company only needs to know the vehicle's location at delivery stops and when it deviates from the planned route. Which edge computing approach reduces bandwidth while meeting the business need?

   • AConfigure the on-vehicle edge device to filter GPS data and send only stop events and route deviations.
   • BStore GPS data on the vehicle and upload it only when the vehicle returns to the depot.
   • CSend all GPS data to the cloud but compress it before transmission.
   • DReduce the GPS update frequency to once per minute for all vehicles.
   Reveal Solution Discussion Select an answer first
4. 23expert · hard

   A company is designing a network automation solution for a set of remote oil wells. Each well has sensors that generate data every second. The company wants to use machine learning to predict equipment failures, but the wells have intermittent satellite connectivity. Which architecture best supports the machine learning workflow?

   • AUse a mesh network between wells to relay data to a central well with better connectivity.
   • BSend all sensor data to the cloud for machine learning inference, and rely on satellite connectivity.
   • CRun the machine learning model on an edge device at each well and send only model updates and anomaly alerts to the cloud.
   • DStore all sensor data locally and upload it to the cloud only when connectivity is available, but run the model only in the cloud.
   Reveal Solution Discussion Select an answer first
5. 24expert · hard

   A city deploys smart traffic lights that must respond to real-time traffic conditions. The system also needs to collect data for long-term urban planning. The traffic lights have limited compute resources. Which architecture best meets both real-time response and long-term planning needs?

   • AUse a central cloud for control and store data locally for planning.
   • BUse only local controllers with no central data collection.
   • CUse edge nodes at intersections for real-time control and send aggregated data to a central cloud for planning.
   • DSend all traffic data to the central cloud and have it control the lights in real time.
   Reveal Solution Discussion Select an answer first
6. 25application · medium

   A retail chain wants to deploy video analytics in its stores to detect shelf-stock shortages. Each store has a limited WAN connection that is also used for point-of-sale transactions. The analytics must run continuously and only alert when a shortage is detected. Which deployment model best fits this requirement?

   • AStream all video to a central cloud for analysis and send alerts back to the store.
   • BRun the analytics on an edge server in each store and send only shortage alerts to the central office.
   • CUse a central cloud but schedule the video upload during off-peak hours.
   • DRecord video locally and upload it to the cloud at the end of each day for batch analysis.
   Reveal Solution Discussion Select an answer first