Nowadays, cloud computing becomes a mainstream domain and the market is dominated by Google Cloud Platform (GCP), Amazon Web Services (AWS), and Microsoft Azure because of their major contribution to the market. As the quantity of data organizations, they are dealing with the increase of situations presented in cloud computing. Edge computing is a source where networks focused on running processes in the cloud on a user’s computer or IoT devices and arrange the data in order so that it will reduce latency and bandwidth. Telcom operator is an example of edge computing that is based on the edge of the computing networks. It can be used widely with a variety of applications, products, and services which includes:
- Security system monitoring
- IoT devices
- Self-driving cars
- More efficient caching
- Medical monitoring devices
- Video conferencing
Data is the main source of modern business which provides value to the business and supports the protocols over critical business processes and operations. At its basic level, it brings the data storage for the devices where it can store rather than providing on a central location that can be far away. It believes in the hybrid computing model that have can be used for compute-intensive workloads especially when it helps address the requirements of workloads that require processing the real-time control and design to solve that problems can bypass the latency caused by cloud computing and getting data to data centers for further processing. This is good for data-sensitive applications and also for those which are generating huge data volumes like in the industrial Internet of Things (IIoT) etc.
The architecture that suits one type of computing task, doesn’t mean, it is a necessity to fit all types of computing tasks. It supports the distribution of computing that can deploy to storage resources that have a long and proven track record. The benefit of edge computing is the ability to process and store data faster. It enables more efficient real-time applications when facial recognition would need to run the algorithm through cloud-based services which took a lot of time to process. The benefits of edge computing are performance, cost savings, functionality, security, and productivity.
Edge computing — IOT and 5G
New technologies and practices help to enhance the capabilities and performance where the technology is expected to become more important and shifted to the internet and brings more potential while using edge technology. 5G will help in deploying the capabilities of the networks in the form of distributed cellular towers and will be capable processing of huge data while maintaining high-speed data transmission between vehicles and communication towers. Moreover, AI will make it possible for decision-making capabilities in real-time which allows the cars to work faster than humans in response to immediate changes in traffic and accident cases. This results in the growth of computing, storage, and network appliance products specifically designed for edge computing which makes interoperability and flexibility products at their edge. The massive evolution of IoT devices will also have an impact on the future development of edge computing. But still, there are some challenges for 5G, which will deploy gradually at first and focus on a major part of the world.
Edge computing is an exciting area. That is why Telcos and vendors are considering it in their business models. They are also monetizing the opportunities and apply the best edge solutions for their company. Another significant benefit of moving processes to the edge is to reduce latency. Development in AI and 5G connectivity and the rising of smart IIOT applications, Edge Computing may reach maturity faster than expected.
Hope you all like this article. Thank you!