Edge Computing Types
As more and more devices are introduced into networks, the volume of data being transmitted at any point in time has risen exponentially. Edge computing lessens the burden of collecting, processing, and distributing data by moving these tasks to the devices situated on the furthest reaches of the network instead of relaying everything through one server. This type of computing involves smaller processing units placed closer to the end users. Edge computing can be divided into three different types including local devices, localized data centers, and regional data centers.
Using different types of edge computing enables you to design the network in a way that can solve business issues such as latency associated with streaming high volume media files and other bandwidth-heavy formats causing network congestion and latency.
Local Devices
Local devices have defined, and specific purposes and deployment is “immediate”. They are most suitable for home or small office networks like running a security system or recording video footage on DVR. These devices are located at the edge of the network, still being connected to the internet with more on-board computing power than in the past. This enables them to do more things independently. A cloud storage gateway is another example of a local device. It is a network appliance acting as an intermediary between the application’s specific programming languages used by cloud storage and network end users; in other words, it enables users to integrate cloud storage into applications without moving the application into the cloud itself.
Localized Data Centers
These data centers provide significant processing and storage capabilities and are fast to deploy in existing environments. Localized data centers typically comprise several servers mounted on between one and ten pre-engineered server racks which are configure-to-order systems and can be assembled on site. Alternate forms of localized data centers are prefabricated micro data centers which are assembled in a factory and delivered to the site as is. Localized data centers have powerful processing and storage capabilities and realize cost savings by avoiding the need to build a new site to accommodate them.
Regional Data Centers
A regional data center comprises more than ten server racks, but is closer to the data at the end user end than to the centralized cloud data centers. Due to their scale, they will have more processing and storage capabilities than localized 1-10 rack data centers. Regional data centers can also be prefabricated or made to order and can be designed to fit specific business needs. While regional centers’ sizes provide greater processing and storage capabilities than the localized data centers, they also take longer to set up and require tremendous maintenance like dedicated power and air conditioning sources to keep the data centers cool.
In conclusion, based on the size and objectives of the business, one or all of these types of edge computing can be used within the business network.
Using Edge Computing Effectively
By moving a network’s computing and processing power closer to its end users, edge computing offers various benefits ranging from:
- faster response times
- increased relatability
- tremendous cost saving
- interoperability
- robust security
To understand the effectiveness of edge computing from a business perspective, let’s explore how edge computing is used effectively in real time.
Data Monitoring and Analysis
The amount of data that is streamed within networks for data monitoring and analysis continues to grow exponentially. In this modern digital era, there are sensors attached to almost everything, from smart watches to home appliances. Businesses that move data analytics to the edge are able to simplify and speed up their analysis of the data generated by these sensor-fitted devices and get timely and reliable insights about their activities.
Customer Behavior Analysis
In today’s modern digital world, it is critical for businesses to gain information about customers and keep informed with their ever-changing requirements. Many stores use edge devices to collect data based on the transaction history of customer smartphones. The high-volume mobile data generated makes it difficult to focus on the information that is most important. Edge analytics can use a process called mobile data thinning to help businesses to focus on the relevant data for faster timely decision making.
Compliance Analysis
In financial sectors, utilizing micro data centers located at financial branches can help to immediately catch and stop non-complaint transactions with no delay in real-time.
Monitoring and Analysis in Remote Sites
Edge computing enables better real-time monitoring and analysis in remote sites with the use of drones in war zones, mining, or agriculture.
Edge computing can add robust value when applied effectively.
Now, you have begun to grasp the types and uses of edge computing.
This quarter’s column is written by Anandhi Sutti with THE MITRE CORPORATION and has over 20 years of experience in Data Management. She has helped public and private sector clients to oversee and strategize the implementation of Data Management, Cloud Computing and Business Intelligence (BI) projects. She has strong expertise in Business Intelligence, Data Analytics, Data Modeling, Data Architecture, Data Catalog, Cloud and Data Strategy along with architecting complex systems and applications using a Software Development Life Cycle (SDLC). Anandhi has a master’s degree in computer applications and bachelor’s degree in mathematics.
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The author’s affiliation with The MITRE Corporation is provided for identification purposes only and is not intended to convey or imply MITRE’s concurrence with, or support for, the positions, opinions, or viewpoints expressed by the author.
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