MCS 227 Solved Assignment 2024-25
Cloud Computing and IoT
MCS 227 Solved
Assignment 2024-25 : All assignments are in PDF format which would be send
on email/WhatsApp (9958676204) just after payment.
Assignment Code: ASST/ MCS 227 /2024-25
Marks: 100
Attempt all the questions:
Q.1 Explain the term
Resource Provisioning in context of cloud computing. Also, explain the various
approaches used for Resource Provisioning. Discuss the problems of
Over-provisioning and Under provisioning.
Resource provisioning in cloud computing refers to the process of allocating and managing computing resources such as CPU, memory, storage, and network bandwidth to meet the demands of applications and services hosted on a cloud infrastructure. It involves dynamically assigning resources based on workload requirements to ensure optimal performance, scalability, and cost-effectiveness.
Manual
Provisioning: This approach involves human intervention in allocating resources
based on estimations or predefined configurations. Administrators manually
provision resources according to anticipated demand, which can be
time-consuming and may lead to inefficiencies due to under or over-provisioning.
Rule-based
Provisioning: In this approach, predefined rules or policies are used to
automate resource allocation decisions. Rules can be based on factors such as
workload characteristics, performance metrics, and service-level agreements
(SLAs). While rule-based provisioning reduces human intervention, it may not
always adapt well to fluctuating workloads or unexpected changes in demand.
Predictive
Provisioning: Predictive analytics techniques are employed to forecast future
resource requirements based on historical data, usage patterns, and trends.
Machine learning algorithms can analyze data to predict workload variations and
dynamically adjust resource provisioning to meet anticipated demand. This
approach enhances scalability and efficiency by proactively allocating
resources, but it requires accurate data and continuous refinement of
predictive models.
Auto-scaling:
Auto-scaling is a dynamic provisioning approach that automatically adjusts
resource allocation in response to changes in workload demand. It typically
involves setting up triggers or thresholds based on metrics such as CPU
utilization, network traffic, or request latency. When the workload surpasses
predefined thresholds, additional resources are provisioned to handle the
increased demand, and vice versa. Auto-scaling improves efficiency by scaling
resources up or down as needed, minimizing underutilization and
over-provisioning.
Problems of
over-provisioning and under-provisioning can significantly impact the
performance, cost, and reliability of cloud-based systems:
Over-provisioning:
Over-provisioning occurs when excess resources are allocated beyond actual
requirements. This leads to wasted capacity and increased costs, as
organizations pay for unused resources. Over-provisioning may also result in
decreased efficiency and scalability, as resources are not utilized optimally.
Moreover, it can lead to resource contention and performance degradation in
multi-tenant environments, affecting the quality of service for other users.
Under-provisioning:
Under-provisioning occurs when inadequate resources are allocated to meet
workload demands. This can lead to performance bottlenecks, slowdowns, or
service disruptions, negatively impacting user experience and business
operations. Under-provisioning may also result in SLA violations, penalties,
and loss of customer trust. Additionally, it can limit scalability and hinder
the ability to accommodate sudden spikes in demand, potentially causing service
outages during peak periods.
Addressing
these challenges requires effective resource management strategies, such as
proactive capacity planning, dynamic scaling mechanisms, and optimization
techniques. By accurately forecasting demand, leveraging automation, and
adopting elastic provisioning models, organizations can mitigate the risks of
over-provisioning and under-provisioning, ensuring efficient resource
utilization, cost savings, and high availability of cloud services.
Q.2 Explain the following types of network connectivity
in cloud computing:
1. Public Inter cloud
Networking
2. Private Inter cloud
Networking
3. Public Intra cloud
Networking
4. Private Intra cloud
Networking
Q.3 What is Edge
computing? Discuss the working of Edge computing. Also, describe the relation
between Edge computing, Fog computing and Cloud Computing, with the help of a
suitable block diagram?
Q.4 What is Tenancy in
context of cloud computing? Compare Multi-Tenancy model and Single Tenancy
model of resource sharing. Explain the various ways through which Multi-Tenancy
can be implemented.
Q.5 Explain the term
Internet of Things (IoT).List and explain the various components used to
implement IoT. Give characteristics of IoT. Briefly discuss the following types
of IoT:
1. Consumer IoT (CIoT)
2. Industrial
IoT(IIoT)
3. Infrastructure IoT
4. Internet of
Military Things (IoMT)
MCS 227 Solved
Assignment 2024-25 : All assignments are in PDF format which would be send
on email/WhatsApp (9958676204) just after payment.
MCS 227 Solved
Assignment 2024-25, MCS 227 Solved Assignment 2024-25, MCS 227 Solved Assignment
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they will also checkout their assignment marks & result. All this is often
available in a web mode. After submitting the assignment, you'll check you MCS
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