Edge computing is an architectural approach that processes data closer to where it is generated, rather than sending all data to centralized cloud data centers. This improves performance by reducing latency and bandwidth usage. Edge computing provides benefits like cost savings, security, and enhanced user experience through faster response times and improved collaboration. Key applications of edge computing include manufacturing, field services, and real-time/near real-time processing of IoT and sensor data to enable insights. Direct benefits to users are faster applications, easier collaboration through technologies like AR/VR, and more personalized experiences.

1. Edge Computing: -
Edge computing is a shift of computing power and storage to locations closer to the
source or creation of data. Edge Computing is NOT a specific technology, in and of
itself, but an architectural approach to improve the performance of the overall
environment. Figure 1 is a simple diagram showing the edge computing architecture.
Figure 1: Edge Computing Architecture
As we’ll see below, edge computing brings business and IT benefits like cost savings,
bandwidth optimization, and enhanced security, all of which benefit end users
indirectly. Yet edge computing also brings direct benefits to end users, including faster
application response times, improved support for collaboration, greater
personalization, more productivity, and a heightened user experience.
DIRECT BENEFITS TO BUSINESS AND IT
1. Maximizing Bandwidth
The need to optimize available bandwidth is critical and will continue to increase. New
technologies like 5G, 6G and WiFi6 are becoming available and satellite connectivity is
making progress, but the amount of data moving between points will keep rising.
Think about something as simple as the cameras in cell phones. In comparison to years
past, these cameras are capturing and uploading massively more data today per photo
and video. All the while, people are taking a lot more photos and videos.

2. In moving this increased amount of information, constant monitoring and optimization
of the bandwidth utilization is required so that the end user experience remains
topnotch. Through the use of edge technology, data can be processed closer to the
source. Data compression and data deduplication can be used to limit the amount of
data. Technologies are also available to prioritize and optimize data movement through
the pipes.
2. Lowering latency
Latency is another key reason to look into edge computing. Network latency refers to
the delay between when data is spent and when it is received. For most topologies,
latency in the last mile is usually the highest and most impactful. The lower the amount
of latency, or delay, the better the end user experience will be for interacting with
applications and data. This is especially important for legacy applications and
interactive applications that are more sensitive to network latency.

3. Here are five ways in which edge can help with latency:
 Distance: It sounds obvious, but geographical distance can increase latency. The
closer the device is located to the servers responding to the request, the less the
round-trip delay.
 Number of hops: Each time a packet of information is sent to a new source,
router, bridge or gateway point, and then pushed forward to the next, that step
amounts to a hop. The fewer the number of hops the data packet must pass
through, the faster it will take to reach its destination.
 Congestion: Congestion, another barrier to data throughput, can occur when a
network (or part of the network) or a network node is overloaded with data.
 Jitter: Jitter is the variations in latency, which can cause disruption in the normal
sequence of sending data packets over a network connection.
 Packet sizes: Latency is directly proportional to packet size. So larger packets
have higher latencies, which is why it’s traditionally taken longer to send video
files over the network.
3. Leveraging workload distribution
Workload distribution, an important aspect of edge computing, is about moving the
workloads closer to the end user as well as spreading workload processing across a
higher number of devices, zones and regions. This strategy can improve the end user
experience in three ways:
 Reducing the distance between the compute environment and the end user and
lowering the number of hops involved in data transfer, for lower latency.
 Increasing the performance of the compute environment by involving more
machines, storage and networking in workload processing.

4.  Improving the resiliency of the hosting environment through the ability to
process the workload in a hybrid and multi-cloud infrastructure. If there is a
failure in a component in one of the edge or cloud areas, end users can be
automatically redirected to a redundant component. While performance might
temporarily become degraded, employees will be able to work continuously, and
business disruption will be avoided.
4. Enhancing Security
The security of an edge computing server, if compromised, doesn’t require an entire
network shutdown. In the event of an attack, it is easier for the business to shut down
the affected server without disrupting the entire network. Due to the distributed nature
of the architecture, work can be redirected to other edge nodes or back to the cloud.
5. Optimizing IT spending
Edge computing reduces some of the inhouse demands of traditional computing, while
introducing IT hiring needs associated with the new environment. The demand for jobs
like system administrators, database administrators, admin, and support functions will
be affected by the improved automation, resiliency and performance brought about by
edge computing. On the other hand, job roles in edge computing projects, software
development, network maintenance, and analysis will see a rise.
Are there certain areas in your business where specific workloads can benefit from
improved bandwidth utilization, lower latency, and workload distribution? Do you
need help in understanding your current infrastructure topology to be able to plan an
edge strategy?
APPLICATIONS FOR EDGE COMPUTING
Edge computing can be applied to many different workloads. Here are three of the most
critical areas that companies are investigating today.
1. Manufacturing
For manufacturers who rely on data for rapid decision-making, edge computing offers
an opportunity to move away from traditional data closets to a more resilient and
flexible infrastructure. The data gathered through sensors and robotics can be analyzed
and applied to improve processes, maintain systems, and respond to real-time issues
on the factory floor.
Sophisticated sensors, for example, can improve quality control and monitor
maintenance. Industrial robots can operate autonomously and communicate with
manufacturing systems. Introducing or expanding the use of augmented or virtual
reality (AR/VR) devices can help improve safety and training for industrial workers
and reduce downtime of factory maintenance events.
How can manufacturers harness the full potential of these advanced data-driven
technologies, such as the IoT, AI, and robotics, to boost productivity, streamline
processes, and increase flexibility?

5. How can they scale the smart factory initiatives that will help them stay ahead of the
competition, while maintaining data privacy and security?
2. Field services
Some examples of edge computing for field services are enterprises in the industrial,
manufacturing, mining, energy, and oil and gas industries. Many of these companies are
working to take advantage of the edge to let them run the core elements of their
solutions locally. Local devices can save their state, interact with each other, and send
important alerts and notifications. Even if the Internet connectivity goes, the edge
processing in the factory, warehouse, industrial site, or mine keeps working, enabling
continuity of business processes and operations.
These advantages are spurred by mobile edge computing devices that capture data
directly from equipment or from sensors attached to legacy equipment. Organizations
are using these edge computing capabilities to translate out-of-date machine protocols
into more modern languages and interact with the modern equipment. Companies can
then compute a variety of data coming in from different sensors to provide operational
information with increased accuracy and reliability, or to produce intelligence that can
be used for other purposes.
How can your organization utilize edge computing to run core elements of your
network in local regions? Is it feasible to integrate IoT data into your edge computing
solution?
3. Real-time and near real-time processing
Edge computing can minimize the network and bandwidth issues associated with
moving large amounts of data to or from IoT devices and reduce reliance on the
network. During edge analytics, the processing control of all applications, services, and
data is then shifted from the cloud to the edge of the network, where a physical contact
is made with the data source.
Edge analytics has been adopted by many vendors for use on servers, allowing
businesses to pre-process their data near its creation instead of transmitting and
processing in the cloud. Companies are looking to edge solutions that can process data
at the source and provide summary information about what’s going on. These solutions
eliminate the need for the SIM cards, data plans, and other network costs that would
accrue when the data is instead transported from the device to a network. Edges can
use simple logic or advanced AI algorithms to understand and build summary
information.
How can pre-processing data and the increasing reliability of operations on edge
technologies support your corporate initiatives? Are there areas within your business
that have the ability to acquire insights faster to reduce time-to-market, operational
expenses, or allow for predictive maintenance?
DIRECT BENEFITS TO THE USER EXPERIENCE

6. Beyond the many IT and business benefits with indirect advantages to end users,
organizations are also realizing direct end user benefits that can improve abilities to
attract, retain, train employees and make the workplace a more productive
environment.
1. Faster response times
One of the major complaints IT organizations face from end users is the response time
of the applications they work with on a daily basis. End users do not understand the
underlying complexity of connecting the applications to their data, nor should they
need to do so. Improving response time by bringing the various different parts closer
enables employees to work more efficiently and effectively. Customers, too, obtain a
better engagement experience.
The goal is to give end users the perception that their environment is close at hand,
when it really might not be. Sometimes users are working with data that’s been
distributed from the cloud to the edge, and sometimes the data there is thinner and
optimized for their ingestion.
2. Easier collaboration
More and more of the work performed by employees does NOT happen in the siloed
world of the past, where one person creates something for someone else to consume
independently and serially. Organizations are uncovering an increased requirement to
use technology to enhance collaboration, especially with the rise in remote work since
the pandemic. Edge computing enables and enhances collaboration by allowing for
faster and thinner data access.
At the same time, technologies like augmented reality/virtual reality (AR/VR) in the
workplace are allowing for real-time collaboration in the workplace, in contrast to
approaches of the past which were limited to audio communication at best. Solutions
like Virtual Desktop Infrastructure (VDI) and engineering VDI (eVDI) or graphical VDI
empower users to share information rapidly and quickly by minimizing the movement
of data. Combining those technologies with edge can reduce the networking path,
enhancing end user experience and significantly improving end users’ perception of the
ecosystem.
3. Individualized experience
Finally, by bringing edge technologies closer to end users and customers, businesses
can offer more personalized experiences. These can include improvements in the
collection of information such as customer sentiment while shopping, for instance.
Improvements in data collection can lead, in turn, to greater efficiencies in supply chain
and distribution.
It's possible with edge technologies to create regional, local and even personal
experiences for users. The data and the people can be nearly co-located, with no need
to keep connecting back into the cloud and/or the datacenter.

7. What are the best ways for your organization to harness the power of edge computing
for improved collaboration, personalization, productivity, and satisfaction? Are you
looking at incorporating live streaming video, AR/VR, or VDI into your edge computing
solution?