\[ \text{Number of transmissions} = \frac{3600 \text{ seconds}}{5 \text{ seconds/transmission}} = 720 \text{ transmissions} \] Next, we calculate the total data generated by one sensor in one hour. Given that each data packet is 256 bytes, the total data generated by one sensor is: \[ \text{Total data (bytes)} = 720 \text{ transmissions} \times 256 \text{ bytes/transmission} = 184320 \text{ bytes} \] To convert bytes to megabytes, we use the conversion factor where 1 MB = \(1024^2\) bytes: \[ \text{Total data (MB)} = \frac{184320 \text{ bytes}}{1024 \times 1024} \approx 0.175 \text{ MB} \] Now, to find the total data generated by all 500 sensors, we multiply the data generated by one sensor by the total number of sensors: \[ \text{Total data for 500 sensors (bytes)} = 184320 \text{ bytes} \times 500 = 92160000 \text{ bytes} \] Converting this to megabytes gives: \[ \text{Total data for 500 sensors (MB)} = \frac{92160000 \text{ bytes}}{1024 \times 1024} \approx 87.5 \text{ MB} \] Thus, the total data generated by all sensors in one hour is approximately 87.5 MB. This scenario illustrates the significant data generation potential of IoT devices in a smart city context, emphasizing the need for efficient data management and analysis strategies to handle such large volumes of information. Understanding these calculations is crucial for urban planners and IT professionals working with IoT systems, as it informs decisions regarding data storage, transmission, and processing capabilities.

Manual documentation, while better than having no records, is prone to human error and can quickly become outdated, especially in dynamic environments where configurations change frequently. A shared drive may not provide the necessary security or versioning capabilities, making it difficult to track who made changes and when. Using a spreadsheet to track changes can also be inefficient and error-prone, as it lacks the automation and integration capabilities of dedicated configuration management tools. Spreadsheets can become cumbersome as the number of devices increases, leading to potential oversights. Lastly, relying solely on the built-in logging features of devices is insufficient for comprehensive configuration management. While logging can provide insights into changes, it does not facilitate proactive management or version control, which are critical for maintaining network integrity and compliance. In summary, a centralized configuration management tool is the most effective approach for ensuring that all devices are properly configured, changes are documented, and the network remains secure and compliant with organizational policies. This strategy aligns with best practices in network management and supports the need for scalability and efficiency in large enterprise environments.

Moreover, automated compliance checks can continuously monitor the configurations against established benchmarks, alerting administrators to any deviations that may arise due to manual changes or errors. This proactive approach allows for immediate remediation before issues escalate into significant downtime. In contrast, increased manual intervention during updates can lead to inconsistencies and errors, as human operators may overlook critical steps or misinterpret configuration requirements. Enhanced physical security measures, while important, do not directly impact the configuration processes that lead to downtime. Similarly, improved user training programs can help reduce errors but do not provide the immediate, systematic checks and balances that automation offers. Thus, the most significant benefit of automation in this scenario is its ability to ensure consistent and compliant configurations, which directly contributes to minimizing downtime during network changes. This understanding of automation’s role in network management is essential for IT professionals aiming to enhance operational efficiency and reliability in their environments.

While the command `show ip protocols` can provide insights into the routing protocols configured on the router, it does not directly indicate the operational status of the interfaces. Similarly, `show running-config` displays the current configuration of the router, which may include routing protocols and interface configurations but does not provide real-time status information. Lastly, `show access-lists` would show any access control lists that might be filtering traffic but would not directly address the issue of interface status or route accessibility. In summary, the most effective command to diagnose the issue of an inaccessible route is `show ip interface brief`, as it directly reveals the operational status of the interfaces involved in routing decisions. Understanding the state of these interfaces is essential for troubleshooting routing issues, as a down interface will prevent packets from being forwarded, leading to the observed problem.

\[ 500 \text{ sensors} \times 2 \text{ MB/sensor} = 1,000 \text{ MB/hour} \] For the traffic cameras, each generating 5 MB of data per hour, the total data generated per hour is: \[ 300 \text{ cameras} \times 5 \text{ MB/camera} = 1,500 \text{ MB/hour} \] Now, we can find the total data generated per hour by both types of devices: \[ 1,000 \text{ MB/hour} + 1,500 \text{ MB/hour} = 2,500 \text{ MB/hour} \] Next, to find the total data generated in a 24-hour period, we multiply the hourly total by 24: \[ 2,500 \text{ MB/hour} \times 24 \text{ hours} = 60,000 \text{ MB} \] To convert this to gigabytes, we divide by 1,024 (since 1 GB = 1,024 MB): \[ \frac{60,000 \text{ MB}}{1,024} \approx 58.59 \text{ GB} \] Now, if the city plans to store this data for 30 days, we need to calculate the total storage requirement: \[ 58.59 \text{ GB/day} \times 30 \text{ days} = 1,757.7 \text{ GB} \] However, since we need to round to the nearest whole number, the total storage requirement is approximately 1,758 GB. This scenario illustrates the importance of understanding data generation rates in IoT architectures, particularly in smart city applications where multiple devices contribute to large volumes of data. It emphasizes the need for efficient data management and storage solutions to handle the influx of information generated by IoT devices. Additionally, it highlights the significance of planning for data retention policies and the implications of data storage costs in urban environments.

Caching, on the other hand, allows frequently requested data to be stored temporarily, reducing the need for repeated calls to the server for the same information. This not only speeds up response times but also decreases the load on the server, leading to improved overall performance. By combining these two strategies, the network engineer can effectively manage the request loads while ensuring that the data integrity is maintained, as cached data can be invalidated or updated based on specific conditions. In contrast, using synchronous calls for all API requests can lead to bottlenecks, as each request must be completed before the next one can begin, which is inefficient in a high-demand environment. Allowing unrestricted access to the API may lead to abuse and potential security vulnerabilities, while relying solely on HTTP GET requests limits the API’s functionality, as it would not support operations like creating, updating, or deleting resources. Therefore, the most effective approach involves a combination of rate limiting and caching to enhance both performance and reliability in RESTful API interactions.

Once in Privileged EXEC mode, the engineer needs to enter Global Configuration mode to make changes to the router’s configuration. This is accomplished by typing `configure terminal`. In Global Configuration mode, the engineer can modify the router’s settings, such as interface configurations, routing protocols, and other critical parameters. Each mode has specific implications for command availability. User EXEC mode is limited to basic commands like `ping` and `show`, while Privileged EXEC mode expands the command set to include configuration and diagnostic commands. Global Configuration mode allows for the most extensive command set, enabling the engineer to make changes that will persist across reboots. Understanding the hierarchy and purpose of these modes is essential for effective network management. Missteps in transitioning between these modes can lead to configuration errors or an inability to access necessary commands, which can hinder troubleshooting efforts. Thus, the correct sequence of commands is vital for ensuring that the engineer can effectively manage and configure the router.

Setting the VTP mode to “client” is essential for the new switch in this scenario. In client mode, the switch can receive VLAN updates from VTP servers but cannot create or delete VLANs itself. This is important for maintaining the integrity of the existing VLAN configurations, as it prevents unauthorized changes to VLANs. Additionally, ensuring that the VTP version matches (in this case, version 2) is necessary for compatibility, as different versions may have varying features and capabilities. Choosing “transparent” mode would allow the switch to forward VTP messages without participating in the VLAN management process, which is not suitable for this scenario where integration into the existing VLAN structure is required. Assigning a different VTP domain name would isolate the new switch from the existing VLANs, leading to a fragmented network. Configuring the switch as a VTP server would also be inappropriate, as it could lead to conflicts and inconsistencies in VLAN management, especially if the existing VTP servers have already established VLAN configurations. In summary, the correct approach involves aligning the new switch’s configuration with the existing VTP domain settings to ensure seamless integration and proper VLAN propagation, thereby maintaining network stability and functionality.

On the other hand, session-based authentication (option b) can introduce statefulness, which may lead to bottlenecks as the server must manage session data for each user. This can hinder performance, especially when the number of concurrent users increases. While session-based authentication can be useful in certain contexts, it is not ideal for a RESTful API designed for high scalability. Strict data validation (option c) is important for security and data integrity, but it does not directly address performance in a high-traffic scenario. While it is essential to validate incoming requests to prevent malicious data from being processed, the validation process itself can add latency if not implemented efficiently. Allowing for synchronous processing of requests (option d) contradicts the principles of RESTful design. Synchronous processing can lead to delays as each request must be completed before the next one can be processed, which is not suitable for environments requiring high throughput and responsiveness. In summary, prioritizing statelessness in API interactions is crucial for achieving optimal performance and reliability in a high-traffic environment, as it allows for better scalability and resource management.

In contrast, the other options present plausible but incorrect scenarios. For instance, while static routes can be inactive, the command `show running-config` would not directly indicate the operational status of the interface. Similarly, checking for a missing next-hop address with `show ip route ` would not address the interface status issue, as the route could still be present but inactive due to the interface state. Lastly, while access control lists (ACLs) can affect traffic flow, they do not directly cause a route to be marked as inactive; thus, using `show access-lists` would not provide relevant information regarding the interface status. Understanding the relationship between routing and interface status is crucial for effective network troubleshooting, making the correct command choice essential for resolving the issue at hand.

Once the Root Bridge is established, RSTP will determine the port roles based on the topology. The ports on the Root Bridge will transition to the Forwarding state, allowing traffic to flow through them. The neighboring switch, which is not the Root Bridge, will have its ports configured based on their roles in relation to the Root Bridge. In this case, since the neighboring switch has a higher Bridge ID, its ports will not be designated as Root Ports and will instead transition to the Blocking state to prevent loops in the network. The RSTP convergence process is rapid, allowing for quick adjustments to the network topology. The states of the ports are critical for maintaining a loop-free environment. The Listening state is a transitional state where the switch prepares to forward frames but does not yet do so, while the Learning state allows the switch to learn MAC addresses but still does not forward frames. In this scenario, the local switch’s ports will not enter the Learning state, as they will directly transition to the Forwarding state due to its status as the Root Bridge. Thus, the correct outcome is that the local switch becomes the Root Bridge, and its ports transition to the Forwarding state, while the neighboring switch’s ports transition to the Blocking state to maintain network stability.

On the other hand, EIGRP is a hybrid routing protocol that combines features of both distance-vector and link-state protocols. It is known for its fast convergence times and efficient use of bandwidth due to its use of the Diffusing Update Algorithm (DUAL). EIGRP also supports variable-length subnet masking (VLSM) and can handle larger networks effectively. However, it is proprietary to Cisco, which may limit interoperability with non-Cisco devices. Administrative distance is another important consideration. OSPF has an administrative distance of 110, while EIGRP has a lower administrative distance of 90, making it more preferred in scenarios where both protocols are present. However, in a purely OSPF environment, the advantages of OSPF’s scalability and faster convergence times make it a more suitable choice for large enterprise networks. In conclusion, while both OSPF and EIGRP have their strengths, OSPF is often favored in large, complex networks due to its scalability, faster convergence, and ability to manage large routing tables effectively. This makes it the more appropriate choice for optimizing routing decisions in the given scenario.

1. **Calculating the number of bits for subnets**: To find the number of bits required for 6 subnets, we use the formula \(2^n \geq \text{number of subnets}\), where \(n\) is the number of bits. Here, \(2^3 = 8\) is the smallest power of 2 that meets the requirement, so we need 3 bits for subnetting. 2. **Calculating the number of bits for hosts**: Next, we need to ensure that each subnet can support at least 30 hosts. The formula for the number of usable hosts in a subnet is \(2^h – 2\), where \(h\) is the number of host bits. We need at least 30 usable addresses, so we solve for \(h\): \[ 2^h – 2 \geq 30 \implies 2^h \geq 32 \implies h = 5 \] Thus, we need 5 bits for hosts. 3. **Determining the total bits**: The original subnet mask for a /24 network has 32 bits in total. If we allocate 3 bits for subnets and 5 bits for hosts, we have: \[ 24 + 3 = 27 \text{ bits for the subnet mask} \] This means the new subnet mask is /27, which corresponds to a decimal notation of 255.255.255.224. 4. **Calculating usable IP addresses**: Each subnet with a /27 mask will have: \[ 2^5 – 2 = 32 – 2 = 30 \text{ usable IP addresses} \] Therefore, each subnet will provide exactly 30 usable IP addresses, meeting the requirement. In summary, the correct subnet mask that allows for at least 6 subnets, each supporting at least 30 hosts, is 255.255.255.224, providing 30 usable IP addresses per subnet.

Enhanced network agility and flexibility stem from the ability to programmatically adjust network configurations and policies in real-time. This means that as the demands of each tenant change, the administrator can quickly adapt the network resources to meet those needs without the need for manual reconfiguration of individual devices. This dynamic resource allocation is crucial in multi-tenant environments, where different SLAs may require varying levels of service quality and bandwidth. While improved hardware utilization, simplified network management, and increased security through segmentation are also benefits of SDN, they are not as directly related to the specific scenario of managing bandwidth requirements dynamically. Improved hardware utilization refers to maximizing the use of physical resources, which is a broader benefit of SDN but not the primary focus here. Simplified network management is a result of centralized control but does not specifically address the dynamic nature of tenant requirements. Increased security through segmentation is important in SDN, but it does not pertain to the immediate need for agility in resource allocation. Thus, the most relevant benefit in this context is the enhanced network agility and flexibility that SDN provides, allowing for real-time adjustments to meet the diverse needs of multiple tenants effectively. This capability is essential for maintaining optimal performance and compliance with SLAs in a competitive data center environment.

However, the inbound traffic behavior is primarily influenced by the routing policies of the ISPs and the BGP attributes they consider, such as AS path length, next-hop IP address, and other attributes like MED (Multi-Exit Discriminator). The local preference setting does not affect how the ISPs route traffic to the organization; it only affects how the organization routes traffic to the ISPs. Therefore, the expected behavior is that the inbound traffic for the 192.0.2.0/24 prefix will be preferred over the 198.51.100.0/24 prefix due to the higher local preference value set within the organization’s AS. In summary, while local preference is a powerful tool for managing outbound traffic, it does not directly influence how inbound traffic is handled by ISPs. The organization must consider other BGP attributes and possibly implement additional routing policies to achieve the desired balance and redundancy in inbound traffic.

Increasing the transmit power of all access points may seem like a viable solution; however, this can lead to further interference and does not address the root cause of the congestion. Additionally, simply switching to the 5 GHz band without evaluating client capabilities can lead to connectivity issues, as not all devices support this frequency. Finally, disabling the 2.4 GHz band entirely is impractical, as many legacy devices rely on this band for connectivity. Thus, the most effective approach is to strategically reassign access points to non-overlapping channels, which will enhance the overall performance of the wireless network by reducing interference and improving signal quality. This method aligns with best practices in wireless network management, emphasizing the importance of channel planning and interference mitigation in maintaining a robust wireless environment.

However, the presence of legacy devices that only support WPA2 poses a significant challenge. If the administrator opts for an exclusive WPA3 implementation, any device that cannot connect to WPA3 will be unable to access the network, potentially disrupting business operations and affecting productivity. Therefore, a thorough assessment of all devices on the network is crucial. This includes identifying which devices are critical for daily operations and whether they can be upgraded or replaced to support WPA3. On the other hand, maintaining a mixed environment with both WPA2 and WPA3 allows for broader compatibility but introduces vulnerabilities associated with WPA2. WPA2 is known to have weaknesses, such as susceptibility to the KRACK (Key Reinstallation Attack) vulnerability, which can be exploited by attackers to intercept data. Thus, while a mixed environment may provide immediate connectivity for all devices, it compromises the overall security posture of the network. Ultimately, the decision should be guided by a risk assessment that considers the sensitivity of the data being transmitted, the criticality of legacy devices, and the organization’s long-term security strategy. The administrator may also explore transitional strategies, such as implementing WPA3 in phases or using WPA2/WPA3 mixed mode, to balance security needs with operational requirements.

The Bridge ID for the local switch can be calculated as follows: \[ \text{Bridge ID}_{\text{local}} = \text{Bridge Priority} + \text{MAC Address} = 32768 + 00:1A:2B:3C:4D:5E \] And for the neighboring switch: \[ \text{Bridge ID}_{\text{neighbor}} = \text{Bridge Priority} + \text{MAC Address} = 24576 + 00:1A:2B:3C:4D:5F \] Since the neighboring switch has a lower Bridge ID, it will be elected as the root bridge. Consequently, the local switch will not be the root bridge and will take on the role of a designated bridge for its segment, as it has the next lowest Bridge ID in its local context. In STP, the designated bridge is responsible for forwarding traffic towards the root bridge, while other switches may enter blocking states to prevent loops. Therefore, the local switch will not be in a blocking state but will actively participate in forwarding traffic, confirming its role as a designated bridge. This understanding of STP roles and the election process is crucial for maintaining a loop-free topology in Ethernet networks.

$$ \text{Number of Subnets} = 2^n $$ where \( n \) is the number of bits borrowed from the host portion of the address. To accommodate at least 5 subnets, we need to find the smallest \( n \) such that \( 2^n \geq 5 \). The smallest \( n \) that satisfies this condition is 3, since \( 2^3 = 8 \) (which is greater than 5). Next, we need to ensure that each subnet can support at least 30 hosts. The formula to calculate the number of usable hosts in a subnet is: $$ \text{Usable Hosts} = 2^h – 2 $$ where \( h \) is the number of bits remaining for host addresses. Since we are using a /24 subnet mask (which has 32 total bits), we have: $$ \text{Total Bits} = 32 – 24 = 8 \text{ bits for hosts} $$ After borrowing 3 bits for subnetting, we have: $$ h = 8 – 3 = 5 $$ Calculating the usable hosts gives us: $$ \text{Usable Hosts} = 2^5 – 2 = 32 – 2 = 30 $$ This meets the requirement of supporting at least 30 hosts per subnet. The new subnet mask after borrowing 3 bits from the host portion is: $$ /24 + 3 = /27 $$ In decimal notation, a /27 subnet mask is represented as 255.255.255.224. Each subnet will thus provide 30 usable IP addresses, which is sufficient for the company’s needs. The other options do not meet both criteria: – 255.255.255.192 (or /26) provides 62 usable hosts but only allows for 4 subnets. – 255.255.255.240 (or /28) allows for 16 usable hosts, which is insufficient. – 255.255.255.248 (or /29) allows for only 6 usable hosts, which is also insufficient. Thus, the correct subnet mask that meets both the subnet and host requirements is 255.255.255.224.

To mitigate the risks associated with using Telnet, organizations should adopt best practices such as replacing Telnet with SSH for remote management and administrative tasks. SSH not only encrypts the data but also provides additional security features such as public key authentication, which enhances the overall security posture of the network. Furthermore, organizations should conduct regular security audits to ensure that only necessary ports are open and that insecure protocols like Telnet are disabled on firewalls and network devices. In addition to replacing Telnet, it is also essential to implement network segmentation and access control lists (ACLs) to restrict access to sensitive systems. This layered security approach helps to minimize the attack surface and protect critical assets from potential threats. Overall, understanding the vulnerabilities associated with legacy protocols like Telnet and adopting modern, secure alternatives is crucial for maintaining a robust network security framework.

Additionally, reducing the transmit power of the access points can help minimize interference from neighboring networks and devices. This adjustment allows for a more controlled coverage area, ensuring that clients are connected to the nearest access point with the least interference. While increasing the number of access points might seem beneficial, it could exacerbate the problem if they are not properly configured to avoid overlapping channels. Switching all clients to the 5 GHz band may not be feasible, as some devices may not support this frequency, and it could lead to underutilization of the 2.4 GHz band. Enabling band steering can help guide clients to the 5 GHz band, but it does not directly address the congestion and interference issues on the 2.4 GHz band itself. Therefore, the most effective strategy is to optimize the channel usage and power settings on the access points operating in the 2.4 GHz band.

1. Calculate the increase in bandwidth: \[ \text{Increase} = \text{Current Peak Usage} \times \text{Percentage Increase} = 800 \, \text{Mbps} \times 0.20 = 160 \, \text{Mbps} \] 2. Add this increase to the current peak usage to find the new required bandwidth: \[ \text{New Required Bandwidth} = \text{Current Peak Usage} + \text{Increase} = 800 \, \text{Mbps} + 160 \, \text{Mbps} = 960 \, \text{Mbps} \] 3. Since the current provisioned bandwidth is 100 Mbps per VM and there are 10 VMs, the total provisioned bandwidth is: \[ \text{Total Provisioned Bandwidth} = 10 \, \text{VMs} \times 100 \, \text{Mbps} = 1000 \, \text{Mbps} \] 4. The company needs to ensure that they can handle the peak usage without degradation, which means they should provision enough bandwidth to cover the new required bandwidth of 960 Mbps. Since their current provisioned bandwidth of 1000 Mbps already exceeds this requirement, they need to ensure they have the additional bandwidth to handle the increase. Thus, the minimum additional bandwidth they should provision to accommodate the 20% increase in peak usage is 160 Mbps. This ensures that during peak traffic periods, the network can handle the increased load without performance issues. The other options do not accurately reflect the necessary calculations for accommodating the projected increase in bandwidth usage.

To further investigate the routing protocols in use and their configurations, the engineer should execute the command `show ip protocols`. This command provides detailed information about the routing protocols that are currently active on the router, including the networks being advertised, the timers, and the neighbors. By analyzing this output, the engineer can determine if the routing protocol is correctly configured and whether it is actively exchanging routing information with neighboring routers. The other options present plausible scenarios but do not directly address the issue of the route being marked as inaccessible. For instance, checking the interface statuses with `show ip interface brief` may reveal if an interface is down, but it does not provide insight into the routing protocol’s operation. Similarly, reviewing access lists with `show access-lists` could help identify if traffic is being filtered, but it does not explain why the route is not being advertised. Lastly, using `show ip route ` would provide details about that specific route but would not address the underlying issue of why it is marked as inaccessible in the first place. Thus, understanding the routing protocol configuration is crucial for diagnosing and resolving the connectivity issue effectively.

To further investigate the routing protocols in use and their configurations, the engineer should execute the command `show ip protocols`. This command provides detailed information about the routing protocols that are currently active on the router, including the networks being advertised, the timers, and the neighbors. By analyzing this output, the engineer can determine if the routing protocol is correctly configured and whether it is actively exchanging routing information with neighboring routers. The other options present plausible scenarios but do not directly address the issue of the route being marked as inaccessible. For instance, checking the interface statuses with `show ip interface brief` may reveal if an interface is down, but it does not provide insight into the routing protocol’s operation. Similarly, reviewing access lists with `show access-lists` could help identify if traffic is being filtered, but it does not explain why the route is not being advertised. Lastly, using `show ip route ` would provide details about that specific route but would not address the underlying issue of why it is marked as inaccessible in the first place. Thus, understanding the routing protocol configuration is crucial for diagnosing and resolving the connectivity issue effectively.

To facilitate communication between these VLANs, the administrator must create a virtual interface (also known as a Switched Virtual Interface, or SVI) for each VLAN on the Layer 3 switch. This allows the switch to route traffic between the VLANs while maintaining their isolation. Each SVI will have an IP address assigned to it, which serves as the default gateway for devices within that VLAN. For example, the SVI for VLAN 10 (HR) might be assigned the IP address 192.168.10.1, while VLAN 20 (Sales) could be 192.168.20.1, and VLAN 30 (IT) could be 192.168.30.1. The other options present significant drawbacks. Configuring all switch ports as trunk ports (option b) would allow all VLANs to communicate freely, undermining the purpose of VLAN segmentation. Assigning all ports to VLAN 1 (option c) would eliminate the benefits of VLANs altogether, and using ACLs on a single VLAN (option d) would not provide the same level of isolation and performance as dedicated VLANs. Therefore, the correct approach is to implement access ports for each VLAN and enable inter-VLAN routing through SVIs on the Layer 3 switch, ensuring both security and efficient communication between departments.

Moreover, personal devices may connect to unsecured networks, such as public Wi-Fi, further exposing corporate data to interception by malicious actors. The absence of a robust security framework to manage these devices can result in a fragmented security posture, making it difficult to enforce policies and monitor compliance. While enhanced productivity and improved employee satisfaction are potential benefits of allowing personal devices, they do not outweigh the security risks involved. Additionally, reduced costs associated with corporate device procurement may seem appealing, but they can lead to significant long-term costs if a data breach occurs, including legal fees, regulatory fines, and damage to the organization’s reputation. In summary, the scenario emphasizes the critical need for organizations to implement comprehensive security policies that address the risks associated with personal devices, including the establishment of guidelines for secure access, regular security training for employees, and the use of mobile device management (MDM) solutions to enforce security measures.

The number of subnets created can be calculated using the formula: $$ \text{Number of Subnets} = 2^n $$ where \( n \) is the number of bits borrowed. In this case, \( n = 2 \): $$ \text{Number of Subnets} = 2^2 = 4 $$ Next, we need to determine the number of usable IP addresses in each subnet. The formula for calculating the number of usable IP addresses is: $$ \text{Usable IPs} = 2^h – 2 $$ where \( h \) is the number of bits remaining for hosts. After borrowing 2 bits from the original 8 bits for hosts, we have: $$ h = 8 – 2 = 6 $$ Thus, the number of usable IP addresses in each subnet is: $$ \text{Usable IPs} = 2^6 – 2 = 64 – 2 = 62 $$ The subtraction of 2 accounts for the network address and the broadcast address, which cannot be assigned to hosts. Therefore, the engineer can create 4 subnets, each with 62 usable IP addresses. This understanding of subnetting principles is crucial for efficient network design, as it allows for optimal use of IP address space while ensuring that the network can accommodate the required number of devices.

For instance, outdated software may have known exploits that attackers can leverage, while weak passwords can lead to unauthorized access. By scoring these vulnerabilities based on their likelihood of exploitation and the potential impact on the organization, the administrator can create a risk matrix that helps in decision-making. This prioritization is crucial because it allows for the efficient allocation of resources to mitigate the most critical vulnerabilities first. On the other hand, focusing solely on patching outdated software without considering other vulnerabilities may leave the organization exposed to threats that could be equally or more damaging. Similarly, implementing a blanket password policy without assessing password strength does not address the root cause of weak passwords and may lead to user frustration and non-compliance. Ignoring vulnerabilities altogether and relying solely on a firewall is a dangerous approach, as firewalls can only provide a certain level of protection and cannot mitigate all types of threats. Therefore, conducting a qualitative risk assessment is the most effective strategy for categorizing and addressing vulnerabilities, ensuring that the organization can proactively manage its security risks. This approach aligns with best practices in risk management and is essential for maintaining a robust security posture in an increasingly complex threat landscape.

\[ A = \pi r^2 \] Substituting the radius \( r = 150 \) feet into the formula, we find: \[ A = \pi (150)^2 \approx 70685.75 \text{ square feet} \] This means that each access point can effectively cover approximately 70,685.75 square feet. However, since the total area of the office is only 10,000 square feet, we need to consider how many of these coverage areas can fit into the total area. Next, we calculate the number of access points required by dividing the total area of the office by the coverage area of one access point: \[ \text{Number of APs} = \frac{\text{Total Area}}{\text{Coverage Area of one AP}} = \frac{10000}{70685.75} \approx 0.141 \] Since we cannot have a fraction of an access point, we round up to the nearest whole number, which is 1. However, this calculation assumes ideal conditions without interference from walls or other obstacles. In practice, due to the presence of walls and other physical barriers, the effective coverage area of each AP may be reduced significantly. To ensure robust coverage and account for potential dead zones, it is prudent to deploy multiple access points. A common practice is to use a density of approximately 1 AP per 1,500 square feet in office environments, which leads to a more practical approach. Thus, for an area of 10,000 square feet, the calculation would be: \[ \text{Number of APs} = \frac{10000}{1500} \approx 6.67 \] Rounding up, the network engineer would ideally deploy 7 access points to ensure complete coverage, accounting for potential interference and ensuring a strong signal throughout the office space. Therefore, the closest option that reflects a practical deployment strategy, considering the need for redundancy and coverage, is 6 access points, which would provide a solid foundation for wireless connectivity in the given environment.

In contrast, the 802.11n standard, while also capable of operating in both 2.4 GHz and 5 GHz bands, does not provide the same level of performance as 802.11ac in high-density scenarios. It supports a maximum throughput of 600 Mbps under optimal conditions, which may not suffice for environments with numerous high-bandwidth applications running concurrently. The older standards, 802.11g and 802.11b, are even less suitable. 802.11g operates at a maximum speed of 54 Mbps and is limited to the 2.4 GHz band, which is more susceptible to interference from other devices such as microwaves and Bluetooth devices. Similarly, 802.11b, with a maximum throughput of 11 Mbps, is outdated and cannot support modern applications effectively. In summary, for a high-density environment requiring robust performance and minimal interference, 802.11ac is the most appropriate choice due to its advanced capabilities and higher throughput potential, making it ideal for supporting multiple simultaneous connections in a conference room setting.