Explore key differences and practical considerations between edge deployment and cloud deployment with this quiz. Boost your understanding of how data processing locations affect latency, bandwidth, and application scenarios in modern computing architectures.
Which deployment approach processes data locally on or near the source device rather than sending it to a remote centralized server?
Explanation: Edge deployment refers to processing data close to the originating device, minimizing the need to send information to a distant server. 'Cloud Deplyment' (spelling error) and 'Core Deployment' are incorrect because they do not imply local processing; instead, they often refer to processing in data centers. 'Bulk Deployment' is unrelated to data processing locations and refers to mass installation. Only edge deployment fits the described scenario.
What is a primary advantage of edge deployment when handling real-time applications like video surveillance?
Explanation: Edge deployment reduces the time for data to travel, resulting in lower latency and faster responses, which is crucial for real-time applications. Higher power consumption and greater bandwidth usage are typically disadvantages or unrelated. While edge deployment may sometimes increase network complexity, lower latency is its main benefit for such scenarios, making it the correct answer.
In which deployment scenario might sensitive data be kept local to improve privacy and security?
Explanation: Keeping sensitive data local is a feature of edge deployment since data does not need to traverse public networks to reach a cloud server. 'Cloud Deployment' typically sends data to remote servers, which could increase exposure. 'Edge Clouding' and 'Duck Deployment' are incorrect terms not associated with deployment types or security advantages.
Which deployment method can help reduce the need for constant, high-bandwidth internet connections when many devices generate data?
Explanation: Edge deployment processes data locally, so only essential or summarized information is sent to a central location, reducing bandwidth use. 'Cloud Delivery' sends all data to distant servers, increasing bandwidth demands. 'Flat Deployment' and 'Deep Deployment' are not recognized methods in this context. Edge deployment is correct for bandwidth savings.
Which deployment method allows easy and rapid scaling of resources to meet increased computational demand?
Explanation: Cloud deployment leverages large pools of resources, allowing fast and flexible scaling according to changing demands. 'Edge Delopment' (misspelled) is less scalable due to hardware constraints. 'Single-node Deployment' and 'Island Deployment' lack the distributed, scalable nature of cloud deployment, making cloud deployment the correct choice.
Which scenario best suits cloud deployment over edge deployment?
Explanation: Cloud deployment is effective for scenarios that can tolerate latency and require significant computational power, like processing large data sets overnight. Real-time control and instant analysis are better handled by edge deployment due to latency concerns. 'Immediate alarms' are also time-sensitive, making cloud less suitable. Thus, batch processing in the cloud is the best match.
How does power consumption typically compare between edge and cloud deployment for devices performing complex analytics on-site?
Explanation: Edge devices handle computation locally, often requiring more processing power and thus higher energy use. 'Cloud deployment always consumes more power' is incorrect because most of the computation is done remotely in the cloud, reducing device-level power needs. It's rarely identical, and power is often a crucial consideration, so the other distractors aren't suitable.
Which deployment method is likely to be more resilient when network connectivity is limited or interrupted?
Explanation: Edge deployment can process and store data locally, allowing continued operation even when network access to central systems is intermittent or lost. 'Cloud Deplotment' (spelling error), 'Grid Deployment', and 'Centralized Deployment' generally rely on constant connectivity to remote servers, making them less resilient under poor network conditions.
Which deployment is typically simpler to update and maintain across a large number of devices?
Explanation: With cloud deployment, updates are often managed centrally and applied to all users or devices at once, simplifying maintenance. Edge deployment (misspelled as 'Edge Delpoyment') involves updating each device, which can be complex. 'Hard Deployment' and 'Cluster Deployment' don't accurately describe easy, widespread maintenance. The cloud approach stands out for centralized management.
Which deployment approach can help reduce data transfer costs by processing and filtering information close to the data source?
Explanation: Edge deployment processes data locally, sending only necessary results to the cloud and minimizing data transfer. 'Cloud Depolyment' (misspelled) may increase these costs due to raw data transmission. 'Core Deployment' and 'Fixed Deployment' aren't standard models for this benefit. Edge deployment clearly helps reduce transfer costs.