In the age of digital transformation, organizations are using technological innovations to increase the level of productivity and improve performance. While cloud computing is one of the leading facilitators of this transformation, edge computing is rapidly entering the field to accelerate the pace.

What is Edge Computing?

Edge computing refers to a network that advocates decentralized processing power. It enables data processing at the edge of a network instead of holding that processing power in a cloud or a central data warehouse. The name "edge" in edge computing indicates that it processes data at the source or the point at which traffic enters or exits the network.

Edge computing allows data generated by IoT devices to be processed closer to its source instead of sending it across storage networks. This helps organizations to analyze the data in near real-time.  So, in edge computing, data is processed by the IoT connected device by itself or by a local server, rather than being transmitted to a data center. Local edge computing system can send daily reports to the central network instead of directing the data as soon as it's generated.

Role of Edge Computing

The main role of edge computing is to ingest, store, filter, and send data to cloud systems. Edge computing becomes ideal in many circumstances. Edge computing reduces latency because data does not have to travel over a network to any central data center. This is ideal for many industries such as financial services or manufacturing. Though IoT is the key driver of edge computing, many other technologies and uses are accelerating the pace of adoption of edge computing environment. It becomes an essential component of the data-driven applications.

The use of this technology beyond desktops and mobile and into Wi-Fi and fixed access technologies has given rise to multi-access edge computing (MEC). MEC permits multiple types of access at the edge. MEC is a network architecture that brings real-time access to radio network information, allowing operators to open their networks to a new ecosystem and value chain.

Strategic Advantages of Using Edge Computing

The Industrial Internet of Things (IIoT) will create US$7.5 T in value by 2025. This means that connected devices will generate a huge volume of data from disparate sources.  While the cloud will play a critical role in enabling new levels of performance, edge computing would be able to deliver on the promise of the IoT in the following ways:

Decrease in Cost: Transmitting massive amounts of data is quite expensive. With edge computing, data is processed near the source and only relevant data is sent to the central network. Hence, the cost of computing eventually goes down.

Real-time data access: It helps in accessing temporal data for real-time analytics. So, immediate analysis and reports of real-time data is easily available. Time-sensitive data can be processed at the point of origin by a localized processor.

Improves Efficiency: Transmitting huge amounts of raw data puts tremendous pressure on networks. So, in most cases, it is more efficient to process data near its source and send only the data that is relevant and has value to the intermediate network.

Reduces response time: A major advantage of edge computing is that it reduces response time and thus lifts off pressure from network resources.

Decreases traffic: It significantly decreases the volumes of data that must be transferred and thus the consequent traffic. This, in turn, leads to reduced transmission costs, shrinking latency, and improved quality of service.

Decentralisation: It decreases the dependency on the core computing center and thus removes a major bottleneck and potential point of failure.

Improved security: It leads to increased security as encrypted data is verified as it passes through protected firewalls and other security joints, where viruses, compromised data, and active hackers can be caught easily.

Use Cases

Edge computing allows smart devices to respond immediately and reduce time lag. It is critical for technologies such as self-driving cars which are essentially datacenters on wheels. Self-driving cars will generate 40TB of data every eight hours of a ride. It would be unnecessary to send all that data to the cloud because this particular set of data will have only short-term value.

Another use case pertains to augmented reality services. Augmented reality services require an application to analyze data from a user's camera to construct a digital representation with information such as images and texts. With MEC platform over the cloud, the data relevant to the point of interest is highly localized. Moreover, the MEC platforms can process the user's whereabouts quickly with low latency.

Relationship Between Edge & Cloud

Edge computing is not an alternative to cloud computing. In contrast, both the technologies should work together for industries to get a more efficient solution. The cloud plays a crucial role where significant computing power is required to efficiently deal with the massive volumes of data generated from different devices. But in some cases, edge computing can be more instrumental. So, both cloud and edge are necessary for organizations to gain the most values and insights from the huge volume of data generated. The two technologies should complement each other.

Some Challenges of the Technology

Security: There are dual opinions regarding the security of edge computing network. Some experts argue that security is better in case of an edge computing environment since data is not traveling over the whole network, and it is staying close to its source. While some believe that edge computing is less secure because the edge devices themselves can be more susceptible.

Licensing issues: There may be hidden licensing costs. The basic version of an edge client might initially have a low price but with additional functionalities, it can be licensed separately and this, in turn, drives up the price.

Configuration issues: Administrators may inadvertently create security gaps if the device manager is not centralized and strong. Failing to change the default password on each edge device or neglecting to update firmware in a consistent manner can cause configuration drift.

Conclusion

Though not particularly a new concept, the adoption of edge computing environment is gaining popularity rapidly. Together both edge computing and cloud computing system can solve most of the problems faced by organizations today. With the increased adoption of IoT technology, the importance of edge computing will increase more than ever.