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A glossary of key edge computing architecture terms

Bolster your networking vocabulary and get to know the various features and technologies that constitute edge computing in this comprehensive glossary of key terms and phrases.

No matter how simple a term may seem, that term typically has various parts that make it what it is.

This is the case for edge computing architecture. The term edge computing may sound simple, as the two words separately seem self-explanatory. Edge computing involves computing at a network's edge, which is frequently defined as the boundary between two networks. However, edge computing architecture has multitudes of technologies, features and functions that make the architecture more advanced than simply computing at the edge.

This glossary dives into the key terms and phrases for an essential edge computing vocabulary. Discover important features and other types of computing to which edge computing relates.

Key terms for edge computing architecture

Cloud computing. The term cloud computing encompasses the delivery of hosted cloud services over the internet. Those service categories are IaaS, PaaS and SaaS, which enterprises select based on their workload and business requirements. Cloud and edge computing differ because the latter results in fewer delays as data moves across a network and stores data more securely away from distributed sites, where cloud computing stores data.

Cloud radio access network. A C-RAN is a cloud computing architecture for RANs. As the name suggests, C-RANs run in cloud environments with centralized management of baseband units (BBUs). Traditionally, C-RANs connect wireless end users to BBUs. C-RANS typically run on cloud computing. However, the use of edge computing architecture can help C-RANs alleviate the latency issues cloud computing can face when the BBUs are relocated to centralized processing stations.

Cloud services. The term cloud services comprises services provided over the internet that service providers deliver to customers. These services include data storage, processing and analytics for applications and other resources. Providers deliver these services through cloud computing, although edge computing can also deliver or replicate an organization's cloud services to remote workers or offices.

Data center. A data center facility hosts an organization's networked computers that handle and maintain large data amounts. Many organizations implement private cloud software in their data centers so users can more easily access resources and services. Edge computing can benefit this move to cloud, as the architecture can transfer crucial information to data centers from various points.

Edge computing. Edge computing architecture processes data at a network's edge, which is closer than cloud or fog computing processes can get to various data sources, such as applications or IoT devices. This architecture minimizes the distance between users and applications, as well as common network issues around bandwidth, latency and throughput.

edge computing
Edge computing architecture can alleviate latency issues and ease potential network congestion.

Edge device. An edge device is hardware that manages data flows at a network's edge. These devices essentially serve as entrance and exit points for networks. Common functions include data transmission, processing, filtering, storage and more. Edge devices can be edge routers, routing switches, gateways, IoT devices or firewalls.

Fog computing. Fog computing, like edge computing, processes data close to the data source, though this processing occurs between the source and cloud environments -- not at a network edge. Some pundits use fog and edge computing interchangeably, while others believe the architectures are either separate yet related or critically different.

High availability. To achieve HA in a system, that service must be regularly operational for extended periods of time. HA requires proper system design and test processes before use. Data centers have historically maintained HA, so this capability is critical for remote workers that access resources through edge computing as well.

Internet of things. IoT is a system of linked computing machines, devices or objects that can transfer data across networks without human interaction. IoT devices are anything -- or anyone -- that can have an IP address and transfer data over networks. IoT contributed to edge computing's popularity, and together, these technologies force organizations to reevaluate traditional network structures.

Latency. Network latency refers to the time packets take to traverse a network from one point to another. Edge computing architecture can reduce latency for time-sensitive resources, as well as the potential for bottlenecks.

Remote office/branch office. ROBO is an office located at a distance from its organization's headquarters. Edge computing architecture can benefit ROBO workers and users, as the architecture can replicate relevant and necessary cloud services locally.

This was last published in October 2019

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