Edge computing is revolutionizing the way we process and analyze data.
This article provides clear explanation on edge and cloud computing, how it came into existence, it's features and how it is applicable in our today's world
Introduction
The world has gone through a series of developments, from the large supercomputers used in the 20th century to the small and portable devices which are currently used.
As the world develops, individuals and businesses generate large amounts of data and thus need a reliable storage system.
Currently the problem of storage has been partly satisfied through cloud storage. Most companies have built their entire system off cloud computing.
While cloud computing offers many benefits to companies it has some challenges. The major challenge of cloud computing is location. This inspired the innovation of a new technology called "edge computing" which moves computing closer to its end users
What is edge computing?
Edge computing is an emerging IT architecture which moves computing resources closer to the data source where it is being generated.
Edge computing moves processing power to the network edge, thereby reducing latency, saving cost, improving response time and better bandwidth availability.
Edge devices, such as routers, gateways, and IoT devices, are equipped with computational power and storage capabilities to perform data processing tasks.
To understand edge computing we must consider the emergence of cloud computing.
What is cloud computing?
Cloud computing is a model that offers computing resources such as servers, storage, database, software and networking over the internet.
It allows users to access and make use of these resources on a demand through a pay-as-you-go price model.
It is usually managed by a cloud service provider.
Examples of some popular cloud service providers are; Amazon web service (AWS), Microsoft Azure, Google cloud platform (GCP), IBM cloud, Oracle cloud, Alibaba cloud etc.
Features of cloud computing
Wide network accessibility:
Cloud computing has a wide network accessibility which allows users to access and make use of resources from anywhere with an internet connection. Users can also gain access through various gadgets and devices.
Centralized infrastructure:
it provides centralized computing resources. This allows users to access the resources remotely through the internet.
Scalability:
Cloud computing allows flexible scalability, which means users can easily increase or decrease their use of resources such as; storage, memory and processing power. This allows businesses to manage fluctuating workloads.
Pay-as-you-go pricing:
Cloud computing provides a pay-as-you-go pricing model which allows users to pay for only the amount or size of resources they will use. Example individuals can pay for the actual computing power, RAM and processing power they need. This helps businesses plan their budget and reduce expenses based on their needs.
Resource sharing:
Cloud computing allows for sharing of computing resources among multiple users and organizations.
Reliability:
Cloud computing has been proven to be reliable through its data backup and disaster recovery mechanism. This ensures safety of data
Security:
Cloud computing provides security measures to protect data from unauthorized access, threats and data breaches.
How does Edge Computing step in?
As earlier said, Edge computing emerged as a solution to solve some challenges associated with cloud computing. Some of these problems which edge computing has helped to solve are;
Latency:
Cloud computing processes data in centralized data centers, which are far away from the end users. This latency causes delay in data transmission and response.
Edge computing brings computing resources closer to the end users, which reduces latency. This is beneficial for real-time applications like internet of things (IoT), autonomous vehicles, and video streaming.
Bandwidth limitations:
Sending large volumes of data to the cloud for storage strains network bandwidth and results in higher costs.
Edge computing allows data to be processed locally which reduces the need for extensive data transfers to the cloud. This helps end bandwidth limitations and lowers network congestion.
Internet connectivity:
Cloud computing requires a steady internet connection to upload data and this may not be accessible in rural communities.
Edge computing allows local processing, making sure operations can continue without a steady internet connection.
Data privacy and security:
Cloud computing involves uploading and storing data in remote data centers, which can raise concerns about data privacy and security.
Edge computing keeps sensitive data closer to its users, reducing the risk of data breaches during transmission to the cloud.
Cost:
Cloud computing usually incurs high cost especially for large data processing and storage.
Edge computing carries out data storage at the edge, which reduces the need for large cloud infrastructures. This helps in cost reduction.
Applications of Edge Computing
Internet of Things (IoT):
IoT is the concept of connecting everyday physical devices and applications to the internet and allowing them to communicate with each other.
Edge computing is integral to IoT as it enables data processing and analysis at the edge of devices. This ensures quick decision-making and reduces the need for regular communication with the cloud.
Autonomous Vehicles:
Autonomous vehicles are vehicles that can operate without human intervention. It is a combination of advanced technologies and artificial intelligence.
Edge computing helps autonomous vehicles by enabling fast processing of sensor data for decision making. This allows vehicles to respond faster.
Smart Cities:
Smart cities are urban areas that make use of technology and data to enhance the quality of life for their residents, improve sustainability, and optimize resource management.
Edge computing helps power smart city operations by processing data from various facilities and devices located throughout the city.
Industrial Automation:
Industrial automation involves the use of advanced technologies and systems to control machines processes and operations
Some examples of industrial automation are; Robotic automation, control systems, process automation, SCADA (Supervisory Control and Data Acquisition) systems etc
Edge computing helps in the monitoring and control of industrial automation, which reduces latency and improves efficiency of machines.
Use cases of edge computing with real world examples
Manufacturing:
Edge computing is being used by industrial companies to track manufacturing, to identify production mistakes and improve product quality. It provides information on how each product is being manufactured and how long the products are in stock.
The availability of environmental sensors throughout the production plant is usually aided by edge computing.
Farming:
Edge computing has come to play a great role in the farming sector. With edge computing farmers can detect nutritional density, predict the best planting and harvesting time, measure water usage and stay updated on climate change
Healthcare:
The amount of patient data acquired each day, through devices, sensors, and other medical equipment has increased massively. This massive data volume requires the use of edge computing.
Robot assisted surgery also makes the experience easier for surgeons and this is also facilitated by edge computing.
Transportation:
Autonomous vehicles use and create from 5 to 20 TB of data each day. They collect data of their position, vehicle condition, road conditions, speed, traffic conditions, and other vehicles. It enhances a great amount of onboard processing since each autonomous vehicle acts at an "edge."
Optimization of network:
Edge computing is used to detect network performance for users. It is also used to "steer" traffic around the network to get the best possible performance for time sensitive traffic.
Programming languages for edge development
When dealing with edge development programmers make use of various programming languages.
The choice of programming language depends on specific requirements or preference of the team.
Some of the programming language used in edge development are:
Python
C/C++
Java
TensorFlow Lite for Microcontrollers (TFLite Micro)
JavaScript/Node.js
Rust
Conclusion
It is important to note that while edge computing solves some
challenges, it may not completely replace cloud computing.
Both approaches have their strengths and are often used together in hybrid architectures to get the best results.