The year of 2020 marks a significant and exciting year for networking and communication. First, 2020 is the year for the announced launch of 5G network, and all the technological hypes associated with 5G, such as IoT (Internet of Things), VR/AR, autonomous vehicles, collaborative robots, smart homes, artificial intelligence, Block Chain and full industrial automation. Indeed, the industry is anticipating the realization of these exciting and beneficial use cases.
For the past couple years, the network architecture has gone through a revolutionary transformation, from a highly centralized cloud when the concept of cloud was first introduced, to a now disaggregated, distributed network architecture. We have observed that services and applications have been migrated from the cloud to the edge. In other words, edge is what drives all the hyped out technologies.
“Rising Edge Computing”
There is no doubt that edge computing plays an integral role in the deployment of 5G network. As an initiative to broaden 5G service coverage, there will be more and more edge edges to minimize the latency and balance the load, particularly the last-mile route. Like all the widespread technologies, the wide-adoption will lead to diversity. Indeed, there have been derivative edge computing topologies developed to address certain applications. Some edges are device edge, mainly a white-box low-power CPU based computing device running third-party software. For instance, connected fleet management is one of the verticals that uses device edge for telematic application.
On the other hand, there are infrastructure or cloud edges, with higher compute, networking and storage capabilities than device edge. These types of edges have similar functionality like the central cloud, but they are deployed to minimize the latency by being situated closely to users or user-oriented service or applications.
In general, we will see more diverse edge topology models.
The development of 5G can be considered as a network decentralization from cloud to edge, and thus edge computing will evolve to be more and more sophisticated. Today, most edges function as local clouds to process, rout, and store the data generated by users, so that latency is minimized as data can be processed locally. In near future, when more 5G-driven applications, such as self-driving bus and AR/VR, are deployed, service providers may incorporate intelligence and analytics into edges, like machine learning or even deep learning to improve QoS, application performance and services, so that the edge will become an edge data center.
Security at the Network Edge
When services and applications move to the edge, security will be the next challenge as hackers tend to intrude the nodes with high volume of confidential data and users. This challenge is particularly serious in FinTech (financial technology), as the financial industry has been deeply involved in the edge computing to offer low-latency digitalized services for their customers. Therefore, we will soon observe edge-based cybersecurity measures with end-to-end visibility and virtualized firewall.