Edge Intelligence: The Central Cloud is Dead – Long Live the Edge Cloud!
management through less interdependency and complexity.
An exception to this Linux predominance is found in the manufacturing industry, where various versions of the Windows operating system and Microsoft’ s. NET framework make up the majority of implementations.
Containerization and Micro-services
A key architectural goal for edge computing should be to isolate services that can be deployed anywhere. In this case,“ anywhere” can be on a smart device, on an IoT gateway, in a micro data center, inside a telecommunications network, in a data center, or in a public or private cloud. This isolation can be achieved through self-contained micro services or pods( a group of services sharing resources, e. g. a database).
With the expansion of end and edge devices, deploying and maintaining code bases will become more difficult. Containers can help mitigate this additional overhead by providing virtualization on the operating system level..
Unlike virtual machines, containers impose little or no overhead. However, containers are less flexible than virtualization, only one operating system is used, Linux being the most popular one.
Docker has been the most popular container technology, but more recently“ rkt” and Rocket have become widely used. The Open Container Initiative( OCI), a Linux Foundation project, aims to bring the competing container technologies together.
Kubernetes also introduces the concept of pods, which is a group of services deployed in containers that share certain resources, e. g. a data base, and interact via inter-process communication. Pods are an interesting concept for edge computing as they allow services to share scarce resources. Kubernetes, another open source project, is an opensource project by the Cloud Native Computing Foundation( CNCF) for automating deployment, scaling and management of containerized applications.
While containers are the preferred technology for deploying pods and micro-services in the cloud, they are also very applicable to edge computing and early adopters are already using containers or container-like technology on the edge. This allows the deployment of the same micro-services in the cloud, on premise and on the edge without touching the code.
It would be beneficial to edge computing to provide a uniform runtime infrastructure to deploy services both in the cloud and the edge. By deploying containers at the edge, one can optimize applications and services for bandwidth, storage, and compute power to meet the latency, scale, reliability, and ultimately cost requirements.
A commonly accepted open source platform would reduce total cost of ownership for customers and would allow solution providers to focus on
IIC Journal of Innovation- 21-