What is edge computing?

Edge computing involves processing data at the edge of networks, close to end devices like IoT sensors, to reduce latency and improve response times. Traditional models relying on centralized data centers face challenges with the growing volume of IoT data. Edge computing addresses these by enabling local data processing, which is crucial for real-time applications. However, it introduces security and reliability concerns that need to be managed. As edge computing becomes mainstream, its importance will grow with the increasing use of real-time applications.

What is a primary reason for the need for faster connections in edge computing?

• To increase the number of connected devices

• To improve the speed of software updates

• To reduce the cost of data centers

• To ensure timely responses in critical situations

How do edge devices help in managing data traffic?

• By increasing the volume of data sent

• By sending data directly to the cloud

• By performing preliminary data analysis

• By storing all data locally

What is a key benefit of edge computing in agriculture?

• Increased data volume

• Cost-effective data transmission

• Real-time data storage

• Immediate data analysis

What is a potential downside of edge computing?

• Higher data storage costs

• Reduced data accuracy

• Security vulnerabilities

• Increased latency

Why is redundancy important in edge computing?

• To enhance data processing speed

• To increase the number of IoT devices

• To prevent downtime if a node fails

• To reduce the cost of edge devices