General Analytics

Edge Computing – The Working and Benefits

In order to minimise latency and bandwidth consumption, edge computing is a networking architecture that focuses on locating processing as close as possible to the data source.

To put it simply, edge computing is the practise of moving fewer operations from the cloud to local sites, like an edge server, an IoT device, or a user’s PC.

A distributed IT architecture known as “edge computing” puts processing power from data centres and clouds as close to the source as feasible. Its main goal is to process data at a lower latency and spend less on the network.

Being physically close to the device is the most crucial aspect of this network edge.

Working of Edge Computing

In conventional computer technologies, data is transferred to the server via the internet, intranet, LAN, etc. after first being seen on the user’s screen. The data is processed and saved here, on the server.

However, as the internet and the number of devices connected to it grew, so did the amount of data, and these data storage infrastructures began to appear incapable of holding so much data.

A Gartner report projects that 75% of corporate data would be created outside of centralised data centres by 2025. The internet is under extreme strain from this amount of data, which leads to interruptions and congestion.

In order to address this, the idea of “Edge Computing” was presented.

The concept of edge computing is simple: instead of moving the data centre closer to the data, the data is pushed closer to the data centre. The processing and storage resources of the data centre are situated as close as feasible to the data generation location (ideally in the same location).

An edge gateway, for instance, can minimise bandwidth requirements by processing data from an edge device, or the device that manages data flow between two networks, and then sending back to the cloud only the data that is required. It is also capable of returning data to the edge device in the event that real-time application requirements are met.

Examples of edge devices include the security camera, the IoT sensor, the employee’s notebook computer, their newest smartphone, and even the internet-connected microwave oven in the office break room. Edge gateways are regarded as edge devices inside an edge computing infrastructure.

Uses of Edge Computing

  • Security system monitoring: This task is carried out with the aid of edge computing.
  • Internet of Things (IoT) devices: Code running on the device itself, as opposed to on the cloud, can improve user interactions on smart devices that connect to the internet.
  • Self-driving cars: Instead of waiting for instructions from a server, self-driving cars need to respond instantly.
  • More efficient caching: By executing code on a CDN edge network, an application can modify the way material is cached to more effectively serve information to users.
  • Medical monitoring devices: They should be able to respond instantly, without waiting for a cloud service to respond.
  • Video conferencing: Placing backend services closer to the video source can minimise lag and latency because interactive live video uses a lot of bandwidth.
  • Cloud gaming: This new kind of gaming, which delivers a live feed of the game directly to devices, requires low latency.

Cloud gaming companies are exploring the possibility of placing edge servers as close to players as they can in order to minimise latency and offer a fully responsive and immersive gaming experience.

Advantages and Disadvantages of Edge Computing

  • There is No Latency

Latency is the length of time it takes for data to travel between two locations on a network. Large physical separations between these two locations as well as network congestion can create delays. Edge computing makes latency issues virtually nonexistent by bringing the points closer together.

  • Saved Bandwidth

Bandwidth is the term used to describe the speed at which data is transferred over a network. The quantity of data that can be transported and the number of devices that can handle it are limited since all networks have a limited amount of bandwidth.

Edge computing installs data servers where data is created, enabling multiple devices to operate over a much smaller and more efficient network.

  • Less Congestion Occurs

Even though the Internet has evolved throughout time, the sheer amount of data produced daily by billions of devices can lead to serious congestion. In edge computing, local computers can perform crucial edge analytics in the case of a network outage, and local storage is available.

There are also some disadvantages. The following are a few of the main disadvantages of Edge computing:

  • Implementation Costs

Putting in place an edge infrastructure in a business can be expensive and difficult. Prior to deployment, it needs additional tools and resources in addition to a well-defined scope and objective.

  • Partially Incomplete Data

Only some data subsets can be processed by edge computing; they should be decided upon before deployment. As a result, businesses could lose important information and data.

  • Safety Comes First

As a distributed system, edge computing may make it challenging to maintain adequate security. There are many risks when processing data outside of the network’s edge.

A new era of data analytics has begun with the deployment of edge computing. A growing number of companies are utilising this technology for data-driven processes that demand instantaneous outcomes.

Edge Computing is still in its infancy, but it has a bright future. Setting aside the disadvantages, Edge appears to be a great substitute for data centres, which is a crucial consideration. Thus, let us observe and wait to see what Edge Computing has in store for the future.


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