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AI CERTs AI+ NetworkExamination Sample Questions (Q38-Q43):
NEW QUESTION # 38
(How are devices within a VNET able to communicate with devices on other networks?)
- A. By using Layer 2 switching for traffic forwarding.
- B. By setting up routing protocols for path selection.
- C. By configuring NAT rules for external routing.
- D. By defining IP address boundaries and subnets.
Answer: B
Explanation:
Devices within a Virtual Network (VNET) communicate with devices on other networks through routing mechanisms that determine the best path for traffic. AI+ Network foundational networking documents explain thatrouting protocolsor static routing configurations enable Layer 3 connectivity between separate IP networks.
Routing protocols such as OSPF, BGP, or static routes allow routers and virtual gateways to exchange network reachability information. This ensures that packets can traverse different network segments, cloud regions, or on-premise environments. Without routing, devices would be limited to local subnet communication only.
NAT may be used for address translation but does not itself enable network-to-network communication.
Defining IP subnets establishes network boundaries but does not provide connectivity. Layer 2 switching operates within the same broadcast domain and cannot forward traffic across different networks.
AI+ Network training materials consistently reinforce that routing is the core mechanism enabling inter- network communication in both physical and virtualized environments.
NEW QUESTION # 39
(Which type of switch is most suitable for powering security cameras in a remote warehouse that require both power and data, without running separate power cables?)
- A. Unmanaged Switch
- B. PoE Switch
- C. Fiber Switch
- D. Managed Switch
Answer: B
Explanation:
A Power over Ethernet (PoE) switch is the most suitable choice for powering security cameras that require both data connectivity and electrical power over a single cable. AI+ Network foundational documentation explains that PoE technology allows Ethernet cables to carry both power and data, eliminating the need for separate electrical wiring.
This is especially beneficial in remote or hard-to-access locations such as warehouses, where installing additional power outlets can be costly and impractical. PoE switches simplify deployment, reduce infrastructure costs, and improve flexibility when placing devices like IP cameras, VoIP phones, and wireless access points.
Managed and unmanaged switches do not inherently provide power delivery unless they specifically support PoE. Fiber switches transmit data over optical fiber but cannot supply electrical power. AI+ Network materials consistently highlight PoE switches as an efficient and scalable solution for powering network- connected devices.
NEW QUESTION # 40
(Scenario: A smart city project integrates IoT-enabled traffic sensors, public safety cameras, and real-time weather monitors. However, the network experiences high latency during peak hours, causing delays in traffic light adjustments and emergency alerts. The city requires a solution to prioritize critical data and ensure smooth operations during high-demand periods.
Question: Which AI-driven approach best addresses this challenge?)
- A. Segregating IoT devices into isolated networks for improved security.
- B. Manual reconfiguration of network routers to handle peak-hour loads.
- C. Deploying static network slices to reduce overall data processing load.
- D. Traffic prioritization and real-time routing optimization using AI models.
Answer: D
Explanation:
AI-driven traffic prioritization and real-time routing optimization is the most effective approach for addressing latency challenges in smart city networks. AI+ Network documentation explains that AI models can analyze live traffic conditions, application criticality, and network congestion to dynamically prioritize essential data flows.
In smart city environments, emergency alerts and traffic control systems require ultra-low latency and high reliability. AI ensures these data streams are prioritized over non-critical traffic during peak hours. Unlike static slicing or manual reconfiguration, AI-driven optimization adapts instantly to changing conditions.
AI+ Network frameworks emphasize intelligent routing and dynamic QoS enforcement as essential for large- scale IoT deployments and real-time urban infrastructure.
NEW QUESTION # 41
(How does network virtualization enhance infrastructure management?)
- A. By allowing multiple operating systems to run on a single server.
- B. By allocating storage dynamically across different environments.
- C. By enabling isolated virtual networks to operate on shared physical hardware.
- D. By packaging applications for use across various platforms.
Answer: C
Explanation:
Network virtualization enhances infrastructure management by enabling multiple isolated virtual networks to operate on shared physical hardware. AI+ Network documentation explains that network virtualization abstracts physical networking resources into logical networks that can be independently managed, secured, and scaled.
This approach allows organizations to deploy segmented networks for different applications, tenants, or departments without requiring separate physical infrastructure. Network virtualization improves agility, simplifies provisioning, and reduces operational costs by maximizing hardware utilization.
Options such as running multiple operating systems relate to hardware virtualization, while application packaging and storage allocation address different virtualization domains. AI+ Network materials consistently identify network virtualization as a key enabler of scalable, flexible, and multi-tenant cloud and enterprise networks.
NEW QUESTION # 42
(How does DeepSlice enhance 5G network slicing?)
- A. By automating penetration testing for security vulnerabilities.
- B. By preemptively blocking threats to web applications and APIs.
- C. By using deep learning to optimize load management.
- D. By focusing on static DNS domain classifications.
Answer: C
Explanation:
DeepSlice enhances 5G network slicing by applying deep learning techniques to optimize load management across network slices. AI+ Network documentation explains that 5G slicing allows multiple virtual networks to operate on the same physical infrastructure, each tailored to specific service requirements such as latency, bandwidth, or reliability.
DeepSlice continuously analyzes traffic demand, user mobility, and application performance metrics. Using deep learning models, it dynamically adjusts resource allocation to ensure each slice receives the appropriate level of service. This improves efficiency, reduces congestion, and maintains Quality of Service (QoS) for diverse use cases such as autonomous vehicles, IoT, and enhanced mobile broadband.
Other options relate to security or DNS analysis and do not address slice optimization. AI+ Network materials identify DeepSlice as a critical innovation for intelligent, adaptive 5G resource management.
NEW QUESTION # 43
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