Next, we apply the route map to modify the metrics of the routes being redistributed. The requirement states that the OSPF metric should be set to double the EIGRP metric. Therefore, if we take an EIGRP route with an original metric of 15, we can calculate the new OSPF metric as follows: \[ \text{OSPF Metric} = 2 \times \text{EIGRP Metric} = 2 \times 15 = 30 \] This calculation shows that the OSPF metric for this specific route will be 30 after redistribution. It is also important to understand the implications of this redistribution. By doubling the metric, you are effectively influencing the OSPF routing decisions, as OSPF uses cost as its metric for path selection. This means that routes with a higher metric will be less preferred compared to those with a lower metric. Therefore, careful consideration must be given to how metrics are manipulated during redistribution to ensure optimal routing behavior in the OSPF domain. In summary, the correct OSPF metric after applying the redistribution and the route map to the EIGRP route with a metric of 15 is 30. This highlights the importance of understanding both the filtering criteria and the metric manipulation involved in route redistribution between different routing protocols.

In contrast, deploying a fixed number of VNF instances does not account for the variability in traffic, which can lead to either resource wastage during low demand or insufficient capacity during peak times. Utilizing a single powerful server may reduce latency due to minimized inter-server communication; however, it introduces a single point of failure and does not leverage the distributed nature of NFV, which is designed to enhance resilience and scalability. Lastly, scheduling VNF instances to run during off-peak hours ignores the real-time nature of network demands and can lead to performance degradation during peak usage times. Overall, the most effective strategy is to implement auto-scaling policies that allow for real-time adjustments based on traffic metrics, ensuring that the network can adapt to changing conditions while maintaining optimal performance levels. This approach aligns with the principles of NFV, which emphasize flexibility, scalability, and efficient resource management in modern network architectures.

Additionally, WPA3 employs stronger encryption protocols, including 192-bit security for enterprise networks, which enhances the overall security posture of the wireless network. This is particularly important for organizations that handle sensitive information, as it helps protect against eavesdropping and man-in-the-middle attacks. While WPA3 does require devices to support the new protocol, it is designed to be backward compatible with WPA2, allowing for a smoother transition in mixed-device environments. However, the benefits of improved security far outweigh the challenges of compatibility, especially in environments where data integrity and confidentiality are paramount. In contrast, the other options present misconceptions about WPA3. For instance, stating that WPA3 focuses solely on speed ignores its primary purpose of enhancing security. Similarly, the claim that WPA3 does not offer significant improvements over WPA2 is inaccurate, as the advancements in encryption and authentication methods are substantial and critical for modern wireless security needs. Thus, understanding these nuanced differences is essential for network administrators when making informed decisions about wireless security protocols.

PaaS offers a comprehensive environment that includes development frameworks, middleware, and database management systems, which are essential for application development. This model supports various programming languages and frameworks, enabling developers to choose the tools that best fit their project requirements. Moreover, PaaS solutions typically include built-in scalability features, allowing the company to adjust resources dynamically based on demand, which is crucial for modern application deployment. On the other hand, Infrastructure as a Service (IaaS) provides virtualized computing resources over the internet, which would require the company to manage the operating systems, storage, and applications themselves. This model is more suited for organizations that need complete control over their infrastructure and are willing to handle the complexities of server management. Software as a Service (SaaS) delivers software applications over the internet, which means the company would be using pre-built applications rather than developing their own. This model does not provide the flexibility needed for custom application development. Function as a Service (FaaS) is a serverless computing model that allows developers to execute code in response to events without managing servers. While it offers scalability and ease of use, it may not provide the comprehensive development environment that PaaS offers for building complex applications. In summary, given the company’s need for a flexible development environment, streamlined deployment, and scalability, PaaS is the most suitable cloud service model. It allows developers to focus on coding and application logic while the platform manages the underlying infrastructure, thus aligning perfectly with the company’s objectives.

Leased lines, while providing dedicated bandwidth and low latency, can be prohibitively expensive, especially for international connections. They do not offer the same level of flexibility or scalability as MPLS, making them less suitable for a multinational corporation that may need to adjust its network as it grows or changes. VPN over the Internet, while cost-effective, typically suffers from variable latency and potential security concerns. The performance of a VPN is heavily dependent on the quality of the underlying Internet connection, which can lead to inconsistent experiences for real-time applications. Additionally, the lack of guaranteed bandwidth can result in degraded performance during peak usage times. Frame Relay, although once a popular WAN technology, is now considered outdated and does not provide the same level of service quality or flexibility as MPLS. It is also less suitable for modern applications that require high availability and low latency. In summary, MPLS stands out as the most appropriate choice for this multinational corporation due to its ability to provide reliable, high-performance connectivity tailored for real-time applications, along with the necessary scalability and redundancy to support the company’s global operations.

\[ \text{Required Bandwidth} = \text{Peak Load} \times \text{Redundancy Factor} = 10 \text{ Gbps} \times 1.5 = 15 \text{ Gbps} \] Next, we need to determine how many 10 Gbps links are necessary to achieve this required bandwidth. Since each link can handle 10 Gbps, we can calculate the number of links needed by dividing the required bandwidth by the capacity of each link: \[ \text{Number of Links} = \frac{\text{Required Bandwidth}}{\text{Link Capacity}} = \frac{15 \text{ Gbps}}{10 \text{ Gbps}} = 1.5 \] Since we cannot have a fraction of a link, we round up to the nearest whole number, which gives us 2 links. Additionally, it is important to consider the implications of latency and the physical layout of the network. Each link introduces some latency, and having multiple links can help distribute the load and reduce the overall latency experienced by users. Furthermore, redundancy not only provides failover capabilities but also helps in load balancing, which is crucial in a high-traffic environment. In conclusion, the design team must implement at least 2 links to meet the technical requirements of the new data center while ensuring redundancy and minimizing latency. This analysis highlights the importance of understanding both the quantitative aspects of network design and the qualitative factors that influence performance and reliability.

\[ \text{Total Bandwidth} = \text{Voice} + \text{Video} + \text{Data} = 300 \text{ Mbps} + 500 \text{ Mbps} + 200 \text{ Mbps} = 1000 \text{ Mbps} = 1 \text{ Gbps} \] This calculation shows that the total bandwidth required matches the available bandwidth exactly. When configuring MPLS Traffic Engineering, it is crucial to ensure that the paths are optimized for these bandwidth allocations. The MPLS TE can utilize Resource Reservation Protocol (RSVP) to reserve the necessary bandwidth for each class of service. This ensures that voice and video traffic, which are sensitive to latency and jitter, are prioritized appropriately. The other options present configurations that exceed the available bandwidth, which would lead to congestion and potential packet loss, especially for real-time applications like voice and video. Therefore, the only viable configuration that meets the bandwidth requirements without exceeding the capacity of the link is to allocate 300 Mbps for voice, 500 Mbps for video, and 200 Mbps for data, totaling exactly 1 Gbps. This approach not only adheres to the bandwidth limitations but also aligns with best practices in MPLS design for ensuring QoS across different types of traffic.

In contrast, a traditional perimeter-based security model, while still relevant, is increasingly inadequate in a landscape where users access resources from various locations and devices. Relying solely on firewalls and intrusion detection systems creates a false sense of security, as attackers can exploit vulnerabilities within the network once they bypass the perimeter defenses. The option of utilizing a hybrid cloud solution without strict access controls poses significant risks, as it can lead to data exposure and non-compliance with regulations like GDPR and HIPAA, which mandate stringent data protection measures. Lastly, focusing exclusively on physical security measures ignores the critical need for logical security protocols, which are essential for protecting sensitive data from cyber threats. In summary, the zero-trust architecture not only aligns with best practices for modern security but also addresses compliance requirements by ensuring that data is protected at all levels, thus providing a comprehensive approach to mitigating risks associated with unauthorized access and data breaches.

If the second ISP becomes unavailable, BGP will automatically fall back to the first ISP due to its lower local preference value. This failover mechanism is crucial for maintaining connectivity without manual intervention. Option b, which suggests using AS path prepending, would not be effective in this scenario since AS path prepending is primarily used to influence inbound traffic rather than outbound. It makes the path appear longer to external peers, which could lead to suboptimal routing decisions from the perspective of the organization. Option c, which involves using MED values, is also not suitable here. MED is used to influence the choice of entry point into an AS from a neighboring AS, but it does not affect the local preference for outbound traffic within the AS itself. Lastly, option d, which proposes filtering routes from the first ISP based on specific prefix criteria, does not address the need for prioritizing outbound traffic effectively. While route maps can be useful for controlling route advertisement and acceptance, they do not inherently change the local preference values that dictate outbound traffic flow. Thus, the most effective strategy is to set the local preference for the second ISP higher than that of the first ISP, ensuring that the organization can optimize its outbound traffic while retaining redundancy.

Health checks are essential as they continuously monitor the status of each data center, ensuring that only healthy sites receive traffic. This proactive approach minimizes downtime and enhances user experience, especially during maintenance windows or unexpected outages. In contrast, relying on a single load balancer at the primary site (option b) creates a single point of failure, which undermines the resiliency goal. If the primary load balancer fails, all traffic would be disrupted, leading to significant downtime. Using DNS round-robin (option c) lacks the intelligence needed for effective traffic management. It does not account for the health of the servers or the load they are experiencing, which can lead to uneven distribution and potential overload on certain data centers. Lastly, configuring a backup data center that only activates during a primary site failure (option d) does not provide the necessary continuous availability that modern applications require. This approach can lead to longer recovery times and does not utilize the full capabilities of both data centers during normal operations. In summary, GSLB with health checks and failover mechanisms is the most effective strategy for ensuring high availability and resiliency in a multi-site architecture, allowing for dynamic traffic management and minimal downtime.

\[ \text{Total Throughput} = \text{Number of Users} \times \text{Throughput per User} = 100 \times 1.5 \text{ Mbps} = 150 \text{ Mbps} \] However, this figure does not account for network overhead, which is essential for ensuring that the WLAN operates efficiently. The overhead for network management and control is given as 20%. To incorporate this overhead, we can calculate the effective bandwidth requirement using the formula: \[ \text{Effective Bandwidth} = \frac{\text{Total Throughput}}{1 – \text{Overhead}} = \frac{150 \text{ Mbps}}{1 – 0.20} = \frac{150 \text{ Mbps}}{0.80} = 187.5 \text{ Mbps} \] Since bandwidth is typically provisioned in whole numbers, we round this up to the nearest whole number, which gives us 188 Mbps. However, in the context of the provided options, the closest and most appropriate choice is 180 Mbps, which allows for some margin in case of unexpected traffic spikes or additional overhead not initially considered. This scenario emphasizes the importance of understanding both user requirements and network overhead when designing a WLAN. It also highlights the need for careful planning to ensure that the network can handle peak loads while maintaining performance. Factors such as the physical layout of the building, potential interference, and the types of applications being used should also be considered in a comprehensive WLAN design strategy.

To mitigate this risk, Spanning Tree Protocol (STP) is essential. STP works by identifying and blocking redundant paths in the network, thus preventing loops while allowing for redundancy. In conjunction with STP, using Link Aggregation Control Protocol (LACP) enables the aggregation of multiple physical links into a single logical link. This not only provides load balancing across the links but also increases bandwidth and redundancy. If one link fails, traffic can still flow through the remaining links without interruption. On the other hand, utilizing a single switch with multiple VLANs does not provide the necessary redundancy, as it creates a single point of failure. Configuring both switches in a stack without STP could lead to loops, as there would be no mechanism to prevent them. Lastly, deploying a mesh topology, while theoretically providing redundancy, is impractical in this context due to the complexity and potential for excessive broadcast traffic. Thus, the combination of STP and LACP effectively addresses the requirements for redundancy and load balancing while minimizing the risk of broadcast storms, making it the most suitable configuration for the scenario presented.

\[ \text{Total bandwidth for streams} = \text{Number of streams} \times \text{Bandwidth per stream} = 10 \times 2 \text{ Mbps} = 20 \text{ Mbps} \] Next, we must consider the overhead for network management and potential packet loss. The engineer has specified a 20% overhead, which means we need to increase the calculated bandwidth to accommodate this additional requirement. The overhead can be calculated using the formula: \[ \text{Overhead} = \text{Total bandwidth for streams} \times \text{Overhead percentage} = 20 \text{ Mbps} \times 0.20 = 4 \text{ Mbps} \] Now, we add the overhead to the total bandwidth for the streams to find the minimum bandwidth requirement: \[ \text{Minimum bandwidth requirement} = \text{Total bandwidth for streams} + \text{Overhead} = 20 \text{ Mbps} + 4 \text{ Mbps} = 24 \text{ Mbps} \] This calculation ensures that the network can handle the required video streams while also accounting for potential inefficiencies and packet loss that could occur during transmission. Therefore, the engineer should allocate a minimum of 24 Mbps to ensure optimal performance for the video conferencing application. This approach aligns with best practices in network design, which emphasize the importance of considering both the actual data requirements and the necessary overhead to maintain quality of service.

\[ P = 2 \times (L + W) \] where \( L \) is the length and \( W \) is the width. Substituting the given dimensions: \[ P = 2 \times (120 \, \text{m} + 80 \, \text{m}) = 2 \times 200 \, \text{m} = 400 \, \text{m} \] Thus, the total length of the fence required is 400 meters. Next, to find the number of surveillance cameras needed, we note that cameras are to be placed at every 20-meter interval along the fence. To find the number of intervals, we divide the total perimeter by the distance between cameras: \[ \text{Number of intervals} = \frac{P}{\text{Distance between cameras}} = \frac{400 \, \text{m}}{20 \, \text{m}} = 20 \] However, since a camera is needed at both the starting point and at each interval, we must add one more camera to account for the starting point. Therefore, the total number of cameras required is: \[ \text{Total cameras} = 20 + 1 = 21 \] However, since the question options do not include 21, we must consider that the last camera at the endpoint of the perimeter may not be counted as a separate camera if it coincides with the starting point. Thus, the number of cameras needed is effectively 20. In conclusion, the security team will need 20 cameras and will require a total of 400 meters of fencing to secure the perimeter of the building effectively. This scenario illustrates the importance of understanding both the physical dimensions of a space and the practical application of security measures in perimeter security design.

Furthermore, a fully implemented DLP solution is essential for preventing sensitive data from being exfiltrated or misused. Partial implementation may lead to gaps in data protection, increasing the risk of data breaches. Therefore, the analyst should prioritize configuring the HIDS to monitor critical system files and ensuring that the DLP solution is fully operational across all endpoints. This dual approach addresses both detection and prevention, significantly enhancing the organization’s endpoint security posture. While increasing the frequency of antivirus updates and conducting employee training on phishing attacks (option b) are important, they do not directly address the immediate vulnerabilities identified in the audit. Implementing a new firewall solution (option c) may provide additional security but does not rectify the specific issues with HIDS and DLP. Conducting a vulnerability assessment (option d) is beneficial for identifying weaknesses but does not provide immediate remediation for the existing configuration issues. Thus, the most effective course of action is to focus on the configuration and implementation of the existing security measures to ensure comprehensive endpoint protection.

Moreover, the centralized control plane facilitates the implementation of consistent policies across the network. By having a single point of control, network administrators can enforce security policies, quality of service (QoS) parameters, and other configurations uniformly, reducing the risk of misconfigurations that can occur in a distributed model. This uniformity is crucial in environments such as data centers, where the demand for resources can fluctuate rapidly. In contrast, while a centralized control plane does simplify certain aspects of network design, it does not necessarily reduce the number of devices required; rather, it centralizes the control functions while the data plane remains distributed across multiple switches. Additionally, while security can be enhanced through isolation of control functions, this is not the primary advantage of a centralized control plane. Lastly, the assertion that performance is improved by distributing control functions contradicts the fundamental principle of SDN, which emphasizes centralized control for better management and efficiency. Thus, the correct understanding of the advantages of a centralized control plane lies in its ability to provide comprehensive visibility and control, enabling dynamic and efficient network management.

Each link between the switches has a capacity of 10 Gbps. Therefore, if we denote the number of links as \( n \), the total available bandwidth for the application can be expressed as: \[ \text{Total Bandwidth} = n \times 10 \text{ Gbps} \] To ensure that the application can function without any bottlenecks, the total bandwidth must be at least equal to the traffic load generated by the application: \[ n \times 10 \text{ Gbps} \geq 12 \text{ Gbps} \] To find the minimum number of links \( n \), we can rearrange the equation: \[ n \geq \frac{12 \text{ Gbps}}{10 \text{ Gbps}} = 1.2 \] Since \( n \) must be a whole number, we round up to the nearest whole number, which gives us \( n = 2 \). This means that at least 2 links are required to handle the 12 Gbps traffic load without any bottlenecks. In summary, the implementation of 2 links allows for a total bandwidth of 20 Gbps (2 links × 10 Gbps), which comfortably exceeds the 12 Gbps requirement. This design not only meets the application’s needs but also provides redundancy and load balancing, which are critical for high availability in enterprise environments. The other options (1, 3, and 4 links) do not meet the requirements adequately, as 1 link would be insufficient, while 3 and 4 links would be excessive for the given load.

In contrast, simply increasing the number of physical switches without analyzing traffic patterns may lead to inefficiencies and underutilization of resources. A flat network topology, while it may seem simpler, can lead to scalability issues and increased broadcast traffic, negating the benefits of a hierarchical design. Relying solely on wireless access points could also introduce reliability issues, especially in environments with high user density, as wireless connections can be less stable and more prone to interference compared to wired connections. Thus, the hierarchical model emphasizes the importance of structured design, where each layer has specific roles and responsibilities. The Access layer should be designed to handle the anticipated growth effectively, ensuring that performance and reliability are maintained through proper traffic management strategies like VLAN implementation. This approach aligns with best practices in network design, which advocate for scalability and efficient resource utilization.

Redundancy can be achieved through various means, including hardware redundancy (such as having multiple routers or switches), link redundancy (using multiple connections), and site redundancy (having backup data centers). In this case, the dual-homed design specifically addresses link redundancy by providing alternative paths for data traffic. This principle is not only about having backup systems in place but also about ensuring that these systems can seamlessly take over in the event of a failure, thus maintaining service continuity. While scalability, modularity, and simplicity are also important design principles, they do not directly address the need for high availability in the same way that redundancy does. Scalability refers to the ability of a network to grow and accommodate increased loads, modularity pertains to the design’s ability to be easily expanded or modified, and simplicity emphasizes the ease of management and operation. However, none of these principles specifically focus on the immediate need to prevent downtime through alternative pathways, which is the core objective of redundancy in this context. In summary, the implementation of a dual-homed design with two ISPs exemplifies the principle of redundancy, which is essential for ensuring high availability and reliability in network design, particularly for critical services that cannot afford interruptions.

One of the primary benefits of this approach is that it simplifies troubleshooting and management. By organizing the network into layers, each with specific functions, network administrators can isolate issues more effectively. For instance, if a problem arises in the access layer, it can be addressed without impacting the distribution or core layers. This layered approach also enhances scalability; as the organization grows, additional access switches can be added without necessitating a complete redesign of the network. Moreover, the hierarchical model supports redundancy and load balancing, which are critical for maintaining network availability and performance. By implementing redundant paths and devices at different layers, the network can continue to operate smoothly even if one component fails. This is in stark contrast to a flat network topology, which can lead to a single point of failure and complicate management. In summary, the hierarchical design model not only facilitates easier management and troubleshooting but also supports scalability and redundancy, making it a preferred choice for large and dynamic enterprise networks. The other options presented do not accurately reflect the principles of hierarchical design, as they either impose unnecessary constraints or misunderstand the need for redundancy and layered management.

In addition to encryption, Multi-Factor Authentication (MFA) adds an essential layer of security by requiring users to provide two or more verification factors to gain access. This could include something they know (a password), something they have (a smartphone app for a one-time code), or something they are (biometric verification). MFA is crucial in preventing unauthorized access, especially in scenarios where passwords may be compromised. On the other hand, allowing employees to use personal devices without security measures poses significant risks, as personal devices may not have the same security controls as corporate devices. This approach could lead to data breaches and non-compliance with regulations like HIPAA, which requires strict safeguards for health information. A basic password policy, while better than no policy, is insufficient in today’s threat landscape. Passwords can be easily compromised, and relying solely on them without additional security measures like MFA does not meet the stringent requirements of GDPR and HIPAA. Lastly, IP whitelisting, while a useful control, is not foolproof. It can be bypassed by attackers who spoof IP addresses or gain access to a whitelisted network. Therefore, it should not be the sole method of securing remote access. In summary, the best strategy for ensuring secure remote access while complying with industry regulations involves a combination of strong encryption through VPN technology and the implementation of Multi-Factor Authentication, thereby addressing both data protection and regulatory compliance comprehensively.

Moreover, detailed diagrams can illustrate the relationships between various devices, such as routers, switches, firewalls, and servers, as well as the protocols used for communication. This level of detail aids in diagnosing issues that may arise due to misconfigurations or hardware failures. For instance, if a particular segment of the network is experiencing latency, a well-documented diagram can help pinpoint whether the issue lies within a specific device or the connections between them. While the other options—such as vendor warranty information, historical performance metrics, and a glossary of terms—are useful, they do not provide the immediate, actionable insights that detailed diagrams offer. Vendor information may assist in procurement or support scenarios, historical metrics can inform capacity planning, and a glossary can help clarify terminology, but none of these elements directly contribute to the real-time troubleshooting process as effectively as comprehensive network diagrams do. In summary, while all elements of documentation are important, the critical nature of detailed network diagrams cannot be overstated, as they provide the foundational understanding necessary for effective network management and troubleshooting. This aligns with industry best practices, which emphasize the importance of clear and detailed documentation in maintaining complex network infrastructures.

$$ \text{Cost} = \frac{\text{Reference Bandwidth}}{\text{Interface Bandwidth}} $$ In this scenario, the EIGRP metric of 20 needs to be converted into an OSPF cost. The default reference bandwidth for OSPF is typically set to 100 Mbps, but it can be adjusted based on the network requirements. To convert the EIGRP metric into an OSPF cost, we need to consider the relationship between the EIGRP metric and the OSPF cost. EIGRP metrics are based on bandwidth, delay, load, and reliability, but for this question, we will simplify it to focus on bandwidth. The EIGRP metric of 20 can be interpreted as a relative measure of the path’s desirability, and we need to assign an OSPF cost that reflects this. Assuming that the interface bandwidth is 100 Mbps, the OSPF cost would be calculated as follows: $$ \text{Cost} = \frac{100 \text{ Mbps}}{100 \text{ Mbps}} = 1 $$ However, since we are redistributing EIGRP routes, we need to ensure that the OSPF cost reflects the EIGRP metric. A common practice is to multiply the EIGRP metric by a factor to align it with OSPF’s cost structure. In this case, if we consider that a metric of 20 in EIGRP should correspond to a higher OSPF cost, we can assign a cost of 5, which is a reasonable approximation that maintains the relative preference of the route. Thus, the correct OSPF cost to assign to the redistributed EIGRP routes is 5, ensuring that the OSPF routing decisions remain optimal and reflect the original EIGRP metrics. This approach helps maintain the integrity of the routing decisions across the different routing protocols in use.

The best practice in MPLS TE is to utilize all available bandwidth effectively while ensuring that QoS requirements are met. Allocating the remaining 100 Mbps as a backup path for failover scenarios is a prudent choice, as it provides redundancy and enhances network reliability. This approach aligns with the principles of MPLS, where maintaining service continuity is essential, especially for real-time applications like voice and video. Reserving the remaining bandwidth for future expansion of video traffic could be a valid strategy, but it does not address immediate needs and may lead to inefficient use of resources. Leaving the bandwidth unallocated is counterproductive, as it does not contribute to the overall network performance and could lead to congestion if unexpected traffic spikes occur. Lastly, using the remaining bandwidth for best-effort data traffic without QoS guarantees undermines the purpose of MPLS TE, which is to prioritize traffic based on its requirements. In summary, the optimal approach is to allocate the remaining bandwidth for backup purposes, ensuring that the network can handle potential failures while maintaining the required QoS for critical applications. This decision reflects a nuanced understanding of MPLS design principles and the importance of proactive bandwidth management in a service provider environment.

Given that each storage device has a capacity of 2 TB, the total raw capacity of \( n \) devices can be expressed as: \[ \text{Total Raw Capacity} = n \times 2 \text{ TB} \] Since the usable capacity in a RAID 10 configuration is half of the total raw capacity, we can express the usable capacity as: \[ \text{Usable Capacity} = \frac{n \times 2 \text{ TB}}{2} = n \text{ TB} \] To meet the requirement of 100 TB of usable storage, we set up the equation: \[ n = 100 \text{ TB} \] This means that we need at least 100 devices to achieve 100 TB of usable storage. However, since each device only provides 2 TB of raw capacity, we can calculate the total number of devices needed: \[ \text{Total Raw Capacity Required} = 100 \text{ TB} \times 2 = 200 \text{ TB} \] Now, to find the number of devices required: \[ n = \frac{200 \text{ TB}}{2 \text{ TB/device}} = 100 \text{ devices} \] However, since RAID 10 requires pairs of disks for mirroring, we need to ensure that the total number of devices is even. Therefore, we round up to the nearest even number, which is 100 devices. In conclusion, the engineer must provision at least 100 devices to achieve the desired storage capacity while maintaining the redundancy and performance characteristics of RAID 10. This calculation highlights the importance of understanding both the storage capacity and the implications of the RAID configuration in a SAN design.

Increasing the bandwidth of the existing core layer, while beneficial for handling traffic spikes, does not resolve the fundamental issue of a single point of failure. It may improve performance temporarily, but it does not provide a failover mechanism. Similarly, introducing a load balancer at the distribution layer can help manage traffic more efficiently but does not eliminate the risk associated with the core layer’s single point of failure. Lastly, optimizing the existing design by adding more access layer switches may improve load distribution but does not address the core layer’s vulnerability. In summary, the most effective approach to mitigate the risk of downtime due to a single point of failure is to implement redundancy at the core layer. This aligns with best practices in network design, which emphasize the importance of high availability and fault tolerance, particularly in enterprise environments where downtime can lead to significant operational and financial impacts.

By continuously verifying the identity of users and the security posture of devices, organizations can significantly reduce the risk of malware infections that exploit trusted connections. This includes employing multifactor authentication (MFA), ensuring that devices meet specific security criteria (such as having updated antivirus software and security patches), and monitoring user behavior for anomalies. In contrast, relying solely on perimeter defenses (option b) is inadequate in a zero-trust model, as it assumes that threats only come from outside the network. Similarly, using a single antivirus solution without regular updates (option c) fails to address the evolving nature of malware threats, which can easily bypass outdated defenses. Lastly, allowing unrestricted access to previously connected devices (option d) undermines the zero-trust principle, as it does not account for the possibility that those devices may have been compromised. Thus, the most effective strategy in this scenario is to adopt a zero-trust approach that emphasizes continuous verification and strict access controls, thereby enhancing the overall endpoint security posture of the organization.

The most appropriate method is to update the employee’s access rights to include only the permissions associated with the HR Manager role and remove any permissions linked to the HR Assistant role. This approach not only aligns with the principle of least privilege but also minimizes the risk of unauthorized access to sensitive information that the employee may no longer need in their new position. Keeping the previous permissions intact (as suggested in option b) could lead to potential security vulnerabilities, as the employee would have access to data that is no longer relevant to their responsibilities. Temporarily disabling access (option c) may disrupt workflow and is not a practical solution for managing role transitions. Lastly, allowing the employee to retain access to all previous roles (option d) undermines the security framework established by RBAC and could lead to excessive permissions that violate compliance standards. In summary, the correct approach is to ensure that the employee’s access is strictly aligned with their current role, thereby maintaining a secure and compliant access control environment. This method not only protects sensitive data but also reinforces the organization’s commitment to effective access management practices.

On the other hand, CoAP (Constrained Application Protocol) is also designed for constrained environments, but it is more suited for request/response interactions, similar to HTTP. CoAP is optimized for low-power devices and can operate over UDP, which is beneficial for applications requiring low overhead. However, it may not handle unreliable networks as gracefully as MQTT, which has built-in Quality of Service (QoS) levels that ensure message delivery even in less reliable conditions. Given the requirement for low power consumption and efficient message delivery in an environment with potentially unreliable network conditions, MQTT emerges as the more suitable choice. Its ability to maintain a persistent connection and manage message delivery through QoS levels makes it ideal for applications where devices need to communicate frequently and reliably, such as in a smart home with various interconnected IoT devices. CoAP, while efficient, may not provide the same level of reliability in message delivery, especially in scenarios where devices are intermittently connected or where network conditions fluctuate. In conclusion, while both protocols have their strengths, MQTT’s design for low-bandwidth and unreliable networks, along with its efficient message handling capabilities, makes it the preferred choice for the smart home application described.

\[ \text{Effective Coverage Area} = \text{Ideal Coverage Area} \times (1 – \text{Reduction Percentage}) \] Substituting the values: \[ \text{Effective Coverage Area} = 2500 \, \text{sq ft} \times (1 – 0.30) = 2500 \, \text{sq ft} \times 0.70 = 1750 \, \text{sq ft} \] Next, we need to find out how many access points are necessary to cover the total area of the office, which is 10,000 square feet. This can be calculated using the formula: \[ \text{Number of APs Required} = \frac{\text{Total Area}}{\text{Effective Coverage Area}} \] Substituting the values: \[ \text{Number of APs Required} = \frac{10000 \, \text{sq ft}}{1750 \, \text{sq ft}} \approx 5.71 \] Since we cannot have a fraction of an access point, we round up to the nearest whole number, which gives us 6 access points. This calculation highlights the importance of considering environmental factors in wireless network design, as the physical layout can significantly impact the performance and coverage of the network. Therefore, to ensure complete coverage of the office space, 6 access points are required. This scenario emphasizes the necessity of conducting thorough site surveys and understanding the implications of physical obstructions on wireless signal propagation.