Cloud computing is a type of computing that relies on shared computing resources rather than having local servers or personal devices to handle applications. The term is generally used to describe the large data centres available to many users over the Internet (public cloud) or on a private network (private cloud).
Edge computing [R1] is the delivery of computing capabilities to the logical extremes of a network to improve the performance, operating cost and reliability of applications and services. By shortening the distance between devices and the resources that serve them, and also reducing network hops, it mitigates the latency and bandwidth constraints of today’s Internet, ushering in new classes of applications.
The combination of edge and cloud computing in a single continuum is part of the ‘fog computing’ paradigm [ R2 ] and includes a common management of every computing resource. Computer and data storage resource, as well as applications and their data, are positioned in the most optimal place between the user and Cloud. In practical terms, this means distributing new resources and software stacks along the path between today’s centralised datacentres and the increasingly large number of devices in the field, concentrated, in particular but not exclusively, in close proximity to the last mile network, on both the infrastructure and device sides.
Edge computing can either use existing devices (routers, servers, gateways, switches,…), telecom base stations or dedicated physical components known as cloudlets (‘data centre in a box’) with the extensive use of virtualisation techniques.
Components & enablers
A good infrastructure is required, such as high-bandwidth telecommunications, ICT infrastructure in the substation or existing telecom equipment (i.e. routers).
Digital substation automation maximises the capabilities of edge computing through direct connection.
Micro-services architectures, virtualisation, containerisation and orchestration tools are the key to achieving a smooth operation.
Advantages & field of application
Edge computing facilitates the processing of delay-sensitive and bandwidth-hungry applications near the data source by pre-processing data. Cloud computing provides scalable computing and storage resources. The right combination of cloud- and edge-based applications is key to maximum performance.
Technology Readiness Level
2020: TRL 6-7 (higher in Telcos)
Research & Development
Current fields of research:
Fault tolerant architectures; distributed storage; hierarchical data mining, seamless management and configuration of heterogeneous components; automatic resource allocation between cloud and edge.
Innovation priority to increase overall TRL:
Adapt existing framework to TSO-specific protocols (61850, 60870-5-104, …) to implement demonstrators’ experiment with a large-scale management system.
Best practice performance
- Dedicated cloud operating system (potentially OpenStack, EdgeXFoundry)
- Separation of control and data planes
- APIs to support interoperability
Best Practice Application
Numerous TSO functions can benefit from edge / cloud computing:
- Data collection for asset monitoring (local treatment and high level indicators sent to cloud), especially from IoT captors.
- Automatic flow control for DER integration (in association with batteries or Dynamic Line Rating), distributed voltage control, faster automatic service restoration.
- HD video surveillance for intrusion detection.
For each function, real time data are treated at the edge and complex data such as topology, forecast are sent by the cloud.
Best practice application
[R1] Open Glossary of Edge Computing. [Link]
[R2] Fog Computing Conceptual Model NIST Special Publication 500-325. [Link]