A Primer on Edge Computing

Edge Computing is a distributed computing paradigm in which processing and computation are performed mainly on classified device nodes known as smart devices or edge devices as opposed to processed in a centralized cloud environment or data centers. It helps to provide server resources, data analysis, and artificial intelligence to data collection sources and cyber-physical sources like smart sensors and actuators. Is edge computing seen as necessary? In the realization of physical computing, smart cities, computing, multimedia applications such as augmented reality and cloud gaming, and the Internet of Things (IoT). It is a way to streamline the movement of traffic from IoT devices and implement real-time local data analysis.

Data produced by the Internet of Things (IoT) devices to be processed where it is created instead of taking away to the routes to data centers with the help of edge computing. It also benefits Remote Office/Branch Office (ROBO) environments and organizations that have dispersed user base geographically. A significant benefit is that it improves time to action and reduces response time to milliseconds, while also conserving network resources.

“Practice of processing data near the edge of your network locally or on own server produced by IoT(Internet of Things) instead of centralized data processing warehouse. ”

Internet of Things (IoT) and Edge Computing

In IoT, with the help of edge computing, intelligence moves to the edge. Like if you have massive amounts of data and for this, you have to leverage in such end to endways or highly sensor intensive or data-intensive environments where data is generated at the edge, which is due to IoT as data sensing at the edge.

And also, with real-time information, the increasing unstructured data of which sensor and IoT data are part, traditional approaches don’t meet the requirements which are needed. There are various scenarios where speed and high-speed data are the main components for management, power issues, analytics, and real-time need, etc. helps to process data with edge computing in IoT.

Benefits of Enabling Edge Computing for the Internet of Things (IoT)

• Lesser Network Load
• Zero Latency
• Reduced Data Exposure
• Computational Efficient
• Costs and Autonomous Operation
• Security and Privacy

Future Directions of Computing for the Internet of Things (IoT)

• Edge-to-Cloud data exchange capabilities
• Common-on-Edge data exchange capabilities
• Streaming Data Analytics and Batch frameworks and APIs
• Controlled rolling and Versioning upgrades of applications
• Status of application monitoring from an Ad-Hoc Cloud Dashboard
• Cloud-Based Deployments of Edge Computing Applications

Why is Edge Computing Important?

• New Functionalities are offered.
• Easier configurations.
• Hacking Potential is increased.
• The load on the server is reduced.
• Load on Network is reduced.
• Application Programming Interface.
• Increases Extensibility.
• Centralized Management.
• Costs of Licensing.
• Support and Updates.

Advantages of Enabling Edge Computing

• Speed is increased.
• Reliability is increased.
• The random issue is reduced.
• The compliance issue is reduced.
• Hacking issues are reduced.
• Random issues are reduced.

Cloud Computing vs. Edge Computing vs. Fog Computing

Edge Computing and Fog Computing are the extensions of Cloud Networks, which are a collection of servers comprising a distributed network. Such networks allow organizations to exceed the resources that would be otherwise available to them. The main advantage of cloud networks is that they allowed data to be collected from multiple sources, which is accessible anywhere over the internet. While Fog Computing and Edge Computing are almost similar, where the talk about intelligence and processing of data at the time of creation.

However there is a crucial difference between these two in terms of intelligence and computing power, where Fog Computing focus more on intelligence at local area network and this architecture transmits data from endpoints to a gateway where it is sent to sources for processing and return to transmission while Edge Computing focus more on computing power and processing of data locally at the edge of a network. It performs processing on embedded computing platforms interfacing to sensors and controllers.

Security in Edge Computing

There are two sides of security in edge computing –

One of them is that the security in edge computing is better than any other part of the data storage application because data is not traveling over the network; it stays where it is created.

The flip side of it is that security in edge computing is less secure because the edge devices in themselves can be more vulnerable.

In conclusion, data encryption, access control, and the use of virtual private networks are crucial elements to protect the edge computing system.

Use Cases where Edge Computing becomes critical

• Having low latency, e.g., Closed-loop interaction between machine insights.
• For real-time analytics, access to temporal data.
• Low connectivity, e.g., Remote Location.
• The high cost of transferring data to the cloud.
• Bandwidth.
• Cybersecurity constraints.
• Compliance and Regulation.
• The immediacy of Analysis, e.g., To check machine performance.
• Predictive Maintenance.
• Energy Efficiency Management.
• Flexible Device Replacement.

Why Edge Computing Matters?

• When IoT devices have poor connectivity.
• Not efficient for IoT devices to be in constant touch with the central cloud.
• The latency factor reduces latency because data doesn’t have to traverse over a network to a central cloud for processing.
• Where latencies are untenable like manufacturing or financial services.
• As soon as data is produced, it doesn’t need to send over a network; instead, it compiles the data and sends daily reports to the cloud for long term storage, i.e., reduces the data traversing.
• The buildout of the next-generation 5G cellular networks by telecommunication companies.
• Direct access to gateway into the telecom provider’s network, which connects to a public IaaS cloud provider.