Edge computing is a physical compute infrastructure that is placed on the spectrum between the device and the cloud and it supports various applications. Edge computing brings processing capabilities closer to the end user of data which eliminates the journey to the cloud data center and reduces latency
Implementation of Edge Computing are ideally suited in a number of situations. One is when IoT devices have insufficient connectivity and it is not feasible for IoT devices to be seamlessly connected to a central cloud. High latency, low spectral efficiency, and non-adaptive machine type of communication, these are some of the serious challenges of cloud computing framework that is leading to a shift to computing to the edge devices of the network.
Telecommunication incorporates the benefits of both local computing and cloud computing. The main advantages of edge computing consist of customers being able to run low latency applications better, as well as cache or process data close to the data source to reduce traffic volumes and costs.
Telecommunication operators often treat edge as synonymous with mobile edge computing or multi-access edge computing – compute based on the edge of the network. However, telecommunication edge compute includes workloads running on customer premise equipment and other points of presence at the customer site.
We say telecommunication edge is best thought of as distributed compute, managed by the operator, which may extend beyond the network edge and onto the customer edge.
On the other hand, like cloud, telecommunication edge compute should offer flexibility and scalability. Telecommunication edge compute can provide capacity to handle sudden spikes in workloads from unplanned increases in end-user activity or address enterprises’ need to scale quickly when developing, testing and deploying new applications. For mobile applications, edge compute not only needs to scale up and down, but also move across different telecommunication edge locations.
Architectural overview of Edge Computing :
These are the listed nodes plays an important part of the overall edge computing architecture.
1. Device Edge
The devices running on-premises at the edge such as cameras, sensors, and other physical devices that gather data or interact with edge data. Simple edge devices gather or transmit data, or both.The complex edge devices have processing power to do some additional activities. In either case it is important to be able to deploy and manage the applications on these edge devices. Examples of such applications include specialized video analytics, deep learning AI models, and simple real time processing applications
2. Local Edge
The systems running on-premises or at the edge of the network. The edge network layer and edge cluster can be separate physical or virtual servers existing in various physical locations or they can be combined,
There are two primary sub layers to this architecture layer are as given below :
Application layer: Applications that cannot run at the device edge because the footprint is too large for the device will run here.
Example of application layer includes complex video analytics and IoT processing.
Network layer: Physical network devices will generally not be deployed due to the complexity of managing them. The entire network layer is mostly virtualised or containerized.
Examples include routers, switches, or any other network components that are required to run the local edge.
3. Cloud
This last architecture layer is generically referred to as the cloud but it can run on-premise or in the public cloud. This architecture layer is the source for workloads, which are applications that need to handle the processing that is not possible at the other edge nodes and the management layers. Workloads include application and network workloads that are to be deployed to the different edge nodes by using the appropriate layers.
Conclusion :
In this overview of edge computing technology, The edge computing architecture identifies the key layers of the edge: the device edge, the local , and the cloud edge.
We’ve shown how edge computing is relevant to challenges faced by many industries, but especially the telecommunications industry.
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