Introduction to Edge Computing
Edge computing brings computation and data storage near to the source of data. This is
part of distributed computing paradigm.
By bringing computation and storage near to the source of data, over all response time be
reduced and it helps in saving bandwidth etc.
Interesting Things about Edge Computing:
1. Edge computing brings data processing and analysis closer to the source of data
generation, reducing latency and enabling real-time decision-making.
2. It enables intelligent devices and applications to operate offline or with limited connectivity by processing data locally.
3. Edge computing enhances data privacy and security by reducing the need to transmit
sensitive information to centralized cloud servers.
4. Internet of Things (IoT) is an example of Edge Computing. You can read my article related Internet of Things at
raktimsingh.com/internet-of-things-iot/
5. Edge Computing helps in real time processing of the data, at or near the application,
which needs this processed data.
6. It is estimated that total data generated will be around 175 zettabytes
(1 zettabyte = 1000 7 bytes). Lot of that data will be required by various IoT devices.
Storing, processing that data in central cloud and sending that amount of data over
network may not be feasible or data transmission will be delayed. Applications which
need to process real time data for critical functions will move towards Edge Computing.
7. By moving services to the edge or devices ( smart objects , smart phone..),
companies can get other advantages like content caching, better service delivery, better
response time etc.
What is Edge Computing:
Edge computing refers to the paradigm of processing and analyzing data at or near the
data source, instead of relying solely on centralized cloud servers.
By bringing computational power closer to the edge of the network, edge computing
enables faster response times, improved reliability, and enhanced privacy and security.
On its own, Edge computing is not ‘A’ technology.
Important point to note is that Edge Computing is an architecture, which involves location
and topology form of distributed computing.
Rather than sending raw data, which an application has generated to central data storage (
cloud ), necessary analysis and processing of that data happens at the application side only.
Only the relevant results like various business insights or actionable steps etc. are sent to
central data storage.
History of Edge Computing:
The concept of edge computing emerged as a response to the increasing demand for low-
latency and real-time processing.
In the late 90’s, Content Delivery Networks (CDNs) played a role in edge computing by
caching content closer to end-users.
In recent years, the rise of Internet of Things (IoT) devices and the need for real-time
analytics have further propelled the development of edge computing solutions.
Notable milestones include the establishment of the OpenFog Consortium in 2015 and the
emergence of edge computing frameworks like Apache Edgent and TensorFlow Lite for edge
devices.
How Edge Computing Works:
Edge computing involves distributing computing resources, such as processing power,
storage and analytics, to the edge of the network, closer to where data is generated.
This is achieved through edge devices or gateways that collect, process, and analyze data
locally. Edge computing systems may leverage technologies like edge servers, edge
gateways, and edge data centers to enable efficient data processing and communication
between edge devices and centralized cloud servers.
Important Features of Edge Computing:
1. Low Latency: By processing data closer to the source, edge computing minimizes the
time it takes for data to travel to the cloud and back, enabling real-time or near real-time
decision-making.
2. Bandwidth Optimization: Edge computing reduces the amount of data transmitted to
the cloud by processing and filtering data locally, optimizing bandwidth usage.
3. Offline Operation: Edge devices can continue to function even in the absence of a
stable internet connection, making them suitable for use in remote or intermittently connected environments.
Advantages of Edge Computing:
1. Reduced Latency: By processing data locally, edge computing minimizes the time it
takes for data to traverse the network, enabling faster response times for critical
applications.
2. Enhanced Reliability: Edge computing allows devices to function autonomously, even
in the event of network disruptions, ensuring uninterrupted operation.
3. Improved Data Privacy and Security: Edge computing reduces the need to transmit
sensitive data to the cloud, enhancing privacy and reducing the attack surface for
potential cyber threats.
4. Quicker data processing and better content delivery resulting in an overall better
experience for the end consumer.
5. Sometime Edge Computing is preferred over cloud Computing as it helps in processing
time sensitive data. Also, Edge computing removes the challenges related to unreliable
network.
6. Increased Uptime : Edge computing also helps in keeping various applications up as
they not much dependent on central servers or network.
Use Cases of Edge Computing:
1. Smart Home Automation: Edge computing enables smart home devices to process
and respond to commands locally, ensuring quick response times without relying on cloud
connectivity.
2. Autonomous Vehicles: Edge computing allows vehicles to process sensor data in real-
time, enabling rapid decision-making for navigation and collision avoidance.
3.Healthcare Monitoring: Edge devices can collect and analyze patient data in real-time,
allowing healthcare providers to monitor vital signs and detect anomalies promptly.
4. Remote monitoring of assets: This is especially very useful in oil and gas industry.
5. Manufacturing and heavy machine industry: Edge computing helps in real time
monitoring of heavy machines. Health of various machines can be known quickly and
proactive maintenance can be planned.
6. Power Sector: With Smart grids powered with edge computing, energy consumption
and optimization on a real time basis can be done.
7. Smart Cities: Edge computing is used at various places in Smart Cities like better traffic
management, smart building etc.
8. Gaming and Entertainment Industry: By local content caching, overall, a better
experience can be provided to the user.
9. Hyper personalization: Edge Computing is helping various industries in offering hyper-
personalized product or services to their customer. As Edge Computing involves last mile
‘computing’ it can take into account data relevant to that customer and move away from
‘one size fits all’ model.
10. Wearables in Metaverse : Various wearable in Metaverse uses the power of Edge Computing
Companies Using Edge Computing:
1. Amazon Web Services (AWS): AWS provides edge computing services through AWS
Greengrass, allowing customers to run local compute, messaging, and data caching for
connected devices.
2. Microsoft Azure: Azure offers Azure IoT Edge, a platform that extends cloud capabilities
to edge devices, enabling local data processing and analytics.
3. Google Cloud: Google Cloud’s Edge TPU (Tensor Processing Unit) empowers edge
devices with accelerated machine learning capabilities, enabling real-time AI inference.
Apart from these TESLA, APPLE etc. are using Edge Computing in their various devices.
Industries Using Edge Computing:
1. Manufacturing: Edge computing optimizes production processes, enables predictive
maintenance, and facilitates real-time quality control in manufacturing environments.
2. Retail: Edge computing enhances customer experiences by enabling personalized
recommendations, inventory management, and real-time analytics at the point of sale.
3.Energy: Edge computing is employed in the energy sector for smart grid management,
demand response systems, and real-time monitoring of energy infrastructure.
4.Transportation and Logistics: Edge computing can improve fleet management, optimize
logistics operations, and enable real-time tracking of assets.
5.Telecommunications: Edge computing can enhance network performance, reduce latency,
latency , and enable the efficient delivery of high-bandwidth applications.
6.Agriculture: Edge computing can be utilized in precision farming for real-time monitoring
of soil conditions, crop health, and irrigation management.
7. Finance Industry: By the virtue of better data analytics, financial firms are able to
offer better services to their customers, be it in terms of better insights from the data
analytics or it can be a facility like ‘High frequency Trading’ , which require latency at
almost zero. Also, it is helping in better regulatory compliance as customer data need not
be sent across locations over the network.
Related Technologies in Edge Computing:
Internet of Things (IoT): Edge computing and IoT are closely intertwined, as edge devices
often collect and process data generated by IoT devices, enabling real-time analytics and decision-making.
Fog Computing: Fog computing extends the principles of edge computing by creating a
network continuum from edge devices to centralized cloud servers, enabling distributed data processing and analysis.
What Edge Computing Doesn’t contain:
Edge computing is not a replacement for cloud computing but rather complements it. While
edge computing brings processing closer to the source, cloud computing provides vast
storage and computational resources for more extensive data analysis and long-term storage.
When You Should Not Use Edge Computing:
Edge computing may not be suitable when extensive data processing, long-term storage,
or complex analytics are required. In such cases, leveraging centralized cloud computing
resources may be more appropriate.
Future of Edge Computing:
As the proliferation of IoT devices continues and the demand for real-time data processing
grows, edge computing is expected to play a vital role in enabling efficient and responsive
systems.
Advancements in edge AI, 5G connectivity, and distributed computing architectures will
further propel the adoption of edge computing in various domains, including smart cities, healthcare, and industrial automation.
Conclusion:
Edge computing represents a paradigm shift in data processing, bringing computation
closer to the edge of the network.
With its ability to minimize latency, enhance reliability, and improve data privacy and
security, edge computing is unlocking new possibilities in industries ranging from
manufacturing and retail to healthcare and transportation.
As the technology continues to evolve,
we can expect edge computing to revolutionize the way we interact with data, enabling real-time decision-making and empowering the future of connected systems.
