PRESENTATION 2
Distinguish parallel and distributed computing systems
The main area of difference between distributed and parallel computing is where jobs are
processed. Multiple processors within a single computer are used in parallel computing to
work on many aspects of a task at once. In contrast, distributed computing entails a number
of separate computers cooperating, frequently via a network, to address a more significant
issue. By breaking a problem down into smaller components, parallel computing distributes
those components among several processors on the same computer. To coordinate their tasks,
these processors can speak to one another and share memory. Dispersed computing
deconstructs an issue and divides the task among several separate computers connected by a
network. These computers may have different amounts of processing power and may be
spread out geographically. “Generally speaking, parallel computing is to deal with some
tasks with slightly less logic but large amount of data.” (Liu, 2022) Each computer may be
responsible for a certain task or address a different aspect of the issue. Peer-to-peer networks,
distributed databases, and cloud computing are a few examples. Because distributed
computing is frequently more scalable, you can add more machines to perform more
complicated or large-scale activities. Distributed computing makes use of several machines,
whereas parallel computing uses a single system with multiple cores. Distributed computing
depends on network communication between machines, whereas parallel computing usually
uses communication within the same system (usually faster and less complex). Managing
distributed systems can be more difficult, particularly when it comes to network problems
and communication overhead. “Distributed Computing Systems process this data, providing
actionable insights and enabling advanced analytics and machine learning for future trend
predictions” (Rosario, 2024) While distributed computing is utilized for applications that
PRESENTATION 3
need to handle massive volumes of data or require a high degree of reliability and scalability,
parallel computing is frequently employed for computationally demanding activities within a
single system. Distributed computing is similar to having various teams working on different
aspects of a project from separate places, whereas parallel computing is similar to having
multiple employees working on one project in the same office.
Contrast computing infrastructure used by competing organizations
There are several things to consider while examining computing infrastructure. There are two
options: cloud computing and on-premises. Another option is to use a hyrid cloud, private cloud,
or public cloud. You might examine the differences between single and multi-cloud computing,
as well as how edge computing might be incorporated into cloud computing. Another option is to
purchase an integrated infrastructure or create your own. Organizations own and oversee their
physical infrastructure, which includes servers, storage, and other components, when it comes to
on-premises. gives total command over systems and data. requires a large initial outlay of funds
as well as continuous upkeep. may have less accessibility and scalability than the cloud.
“A company-owned data center provides full control of data, hardware, and software. Such an
operational model is commonly referred to as an “on-premises IT,” or “on-prem” for short”
(Shaltavev, 2023) You would use third-party providers for infrastructure services (IaaS, PaaS,
and SaaS) when considering cloud computing. It provides advantages like cost-effectiveness,
accessibility, and scalability. The well-known providers are GCP, Azure, and AWS. Companies
that use cloud infrastructure include Capital One, Netflix, and Airbnb. When considering cloud
computing, you must also consider whether you want to use a private, public, or hybrid cloud.
“The cloud computing platform is dynamic and easy to expand, and the resources are obtained
through the network through virtualization technology; users do not need to have professional
PRESENTATION 4
knowledge; there is no need to participate in construction and management .” (Yu,
2022)Resources in the public cloud are shared by several tenants. provides quick scalability and
cost savings. may give rise to worries regarding compliance and data security. When considering
the use of a private cloud, one business can benefit from its dedicated infrastructure. provides
more personalization and control, especially for sensitive data. demands a larger initial
investment. The use of a hybrid cloud might then be considered as well. This is a hybrid of
private and public cloud settings. allows you flexibility in utilizing the benefits of both strategies.
For instance, GE makes use of both Azure and AWS services.“The hybrid model can be an
attractive option for companies which are not willing to give up control over their business
data.<“ (Shaltavev, 2023) The following criteria are used by organizations when selecting their
computing infrastructure:
Scalability: The capacity to manage a range of tasks.
Cost-efficiency: Making the most of infrastructure-related costs.
Security and Compliance: Preserving private information and fulfilling legal obligations.
Performance: Making sure services and apps function properly.
Flexibility and Control: The extent of personalization and control.
Organizations can choose the computer infrastructure that best supports their business objectives
and provides them with a competitive edge by carefully weighing these considerations.
Appraise advanced business technologies for scalable infrastructure
“There are four major challenges in establishing a comprehensive IoT data infrastructure for
buildings. Scalability is the fourth challenge.” (Anik, 2022) Scalable infrastructure and cutting-
edge business technology are essential for companies looking to expand and stay competitive.
They facilitate effective use of resources, encourage company expansion, and improve flexibility
PRESENTATION 5
in response to shifting market conditions. In essence, they let companies expand and change
without sacrificing efficiency, security, or affordability. As the company grows, scalable
infrastructure can manage rising workloads and client needs. Companies can save money by
optimizing resource utilization and avoiding overprovisioning. Businesses can swiftly adjust to
new market possibilities and difficulties thanks to scalable systems. Employees can concentrate
on more important duties by using technology to automate repetitive work and increase overall
productivity. Scalable systems improve workflows and streamline procedures, which improves
production and coordination.
PRESENTATION 6
References
Anik, S. M. H., Gao, X., Meng, N., Agee, P. R., & McCoy, A. P. (2022). A cost-effective,
scalable, and portable IoT data infrastructure for indoor environment sensing.Journal of
Building Engineering,49, 104027. doi:10.1016/j.jobe.2022.104027
Lappo, V., Soichuk, R., & Akimova, L. (2022). DIGITAL TECHNOLOGIES OF SUPPORT
THE SPIRITUAL DEVELOPMENT OF STUDENTS. Information Technologies and Learning
Tools,88(2), 103-114. https://doi.org/10.33407/itlt.v88i2.3403
Leone-Sheehan, D. , Flanagan, J. & Willis, D.<(2024).<Intensive Care Unit Nurses' Experience of
Watson's Theory of Human Caring Caritas Process III.<Advances in Nursing Science,47(1),<59-
72. doi: 10.1097/ANS.0000000000000489.
Liu, Y., & Li, J. (2022). Brand Marketing Decision Support System Based on Computer Vision
and Parallel Computing.Wireless Communications & Mobile Computing
(Online),2022https://doi.org/10.1155/2022/7416106
Rosário, A. T., & Raimundo, R. (2024). Internet of Things and Distributed Computing Systems
in Business Models.<Future Internet,<16(10), 384. https://doi.org/10.3390/fi16100384
Shaltayev, D. S., & Hasbrouck, R. B. (2023). Teaching case “IT outsourcing at Smithfield
Foods: From on-premises data center to a cloud-based ERP system”. Journal of Information
Technology Teaching Cases, 14(1), 80-89. https://doi.org/10.1177/20438869221150823
(Original work published 2024)
Yu, X., Zhai, J., & Ye, J. (2022). Construction of Water Conservancy and Energy Engineering
Structure Platform Based on Cloud Computing.Wireless Communications & Mobile Computing
(Online),2022https://doi.org/10.1155/2022/3262257
