The Drivers and Benefits of Edge Computing
The term bandwidth refers to the data transfer capacity of a computer network. It is a value that is expressed in bits per second (Bps). The higher the Bps the more data can be transferred over the network each second. Increasingly, internet use is moving towards content that requires high bandwidth. For example, bandwidth-intensive content like high-quality video streaming, web tools for photo editing, cloud-based apps for file sharing and collaboration, etc. At the same time, both telecom networks and data networks are converging into a cloud computing architecture. To support the need for content and applications that require high bandwidth, computing power and storage are being inserted into the network edge. This helps lower data transport time and increases availability. Edge computing brings users or data sources closer to bandwidth-intensive content and latency-sensitive applications. Download this white paper to learn more about the drivers for edge computing and the different types of edge computing currently available.
What is edge computing?
Edge computing is the practice of capturing, storing, and processing data near the client or user where it is generated, instead of transporting and it to a central data processing warehouse. These days data storage is also taking place at the network edge to make it easier for users to access bandwidth-intensive content. Edge computing enables mobile computing for data that is created locally.
Application for edge computingThere are three primary applications of Edge Computing:
- A tool to gather massive information from local “things” as an aggregation and control point.
- A local storage and delivery provider of bandwidth-intensive content as part of a content distribution network.
- An on-premise application and process tool to replicate cloud services and isolate the data center from the public cloud.
Edge computing can solve latency challenges and enable companies to take better advantage of opportunities by leveraging a cloud computing architecture. Workloads generated from the bandwidth-intensive streaming video are causing network congestion and latency. Edge data centers bring bandwidth-intensive content closer to the end-user and latency-sensitive applications closer to the data. Computing power and storage capabilities are inserted directly on the edge of the network to lower transport time and improve availability. Types of edge computing include local devices, localized data centers, and regional data centers. The one that provides the deployment speed and capacity in line with future IoT application demands is the localized 1-10 rack versions. These can be designed and deployed quickly and easily with either configured-to-order or prefabricated variants.