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What Is Edge Computing? Everything You Need to Know

If we look at the below image, it is a standard IOT implementation where everything is centralized. While Edge Computing philosophy talks about decentralizing the architecture. An enterprise application platform with a unified set of tested services for bringing apps to market on your choice of infrastructure. IoT sensors can be added to parts of the machinery that are most prone to breaking or overuse.

Edge Computing explained

Outage reduction and intermittent connectivity are also improved with edge computing because it doesn’t solely rely on the cloud for processing. This can aid in avoiding server downtime, ensuring reliable operations in remote locations and avoiding unplanned downtime. Edge computing enables a company to expand its capacity through a combination of IoT devices and edge servers.

How Is Edge Computing Revolutionizing Mobile Experiences?

This amount of data puts an incredible strain on the internet, which in turn causes congestion and disruption. In an industrial setting, the edge device can be an autonomous mobile robot, a robot arm in an automotive factory. In health care, it can be a high-end surgical system that provides doctors with the ability to perform surgery from remote locations.

  • Edge computing speeds up this process by enabling cameras to perform initial video analytics and recognize events of interest.
  • Virtualization is a vital element of a large-scale edge computing setup.
  • On the consumer front, it might be helpful to think of IoT devices performing certain tasks, like facial recognition, with their own local computing resources, rather than farming it out to a cloud service.
  • In addition, companies can save money by having the processing done locally, reducing the amount of data that needs to be sent to a centralized or cloud-based location.
  • In smart homes, a number of IoT devices collect data from around the house.
  • Edge devices are already intelligent enough to handle AI and machine learning and other highly sophisticated functions on their own.

Combined with cloud, edge will enable businesses to reimagine experiences. The potential applications of edge have expanded far beyond just manufacturing and IoT. Edge can be incorporated to drive rapid decision-making and improve user experiences by increasing relevance at each touchpoint.

Bonus tip: The edge computing pizza place analogy

We’re going to explain edge computing as it relates to cloud computing, as well as the similar fog computing, and give a few examples. For example, if a fire breaks out in a building with edge cameras, the devices can distinguish humans within the flame. Once the camera notices a person in danger, the footage goes to the local edge without latency. The local edge can then contact the authorities instead of sending the footage to the data center and losing valuable time. Unfortunately, setting up adequate security is difficult in a distributed environment.

Edge Computing explained

Less data in the cloud means there is less data to be in a breach or leak. Like the metaphorical cloud and the Internet of Things, the edge is a buzzword meaning everything and nothing. Over the years, we’ve seen paradigm shifts in computing workloads, going from data centers to the cloud and from the cloud to the logical edge of networks.

The Fusion of 5G, Edge Computing, and AI

The advent of 5G promises data speeds of over 20 Gbps and delay-free connections of over a million devices per square mile. This emerging technology pushes edge computing to a new level, enabling even lower latency, higher speeds, and enhanced efficiency. Edge computing in upstream use cases focuses on distinguishing between these three types of data sources, then only transmitting critical information to the data center. Enterprises improve operational and employee productivity by responding more quickly to information.

Edge Computing explained

Now with that flood of data, the time of transmission will go substantially up. In cases of self-driving cars, real-time or quick decisions are an essential need. These self-driving cars need to take decisions is split of a second whether to stop or not else consequences can be disastrous. Imagine a case of a self-driving car where the car is sending a live stream continuously to the central servers.

Edge Computing vs. Cloud Computing

Examples include oil rigs, ships at sea, remote farms or other remote locations, such as a rainforest or desert. Edge computing does the compute work on site — sometimes on the edge device itself — such as water quality sensors on water purifiers in remote villages, and can save data to transmit to a central point only when connectivity is available. By processing data locally, the amount of data to be sent can be vastly reduced, requiring far less bandwidth or connectivity time than might otherwise be necessary.

Edge computing is not a replacement for, or alternative to, traditional cloud computing, but rather an extension of it. The costs of implementing an edge infrastructure in an organization can be both complex and expensive. It requires a clear scope and purpose before deployment as well as additional equipment and resources to function. For many companies, cost savings alone can be a driver to deploy edge-computing. Companies that initially embraced the cloud for many of their applications may have discovered that the costs in bandwidth were higher than expected, and are looking to find a less expensive alternative. Edge computing is transforming how data generated by billions of IoT and other devices  is stored, processed, analyzed and transported.

Drawbacks of Edge Computing

The consequences can be disastrous if the car waits for the central servers to process the data and respond back to it. Although algorithms like YOLO_v2 have sped up the process of object detection the latency is at that part of the system when the car has to send terabytes to the central server and then receive the response and then act! Hence, we need the basic processing like when to stop or decelerate, to be done in the car itself.

Edge Computing explained

Network modernization can yield greater business resiliency and cost efficiency, creating a ripple effect of innovation. Well, arguably, the answer lies in history repeating itself, and bringing the servers closer to the people who are using them. This benefit is vital for industries that require quick expansions into regions with limited connectivity.

A Technology on the Rise

Specifically, AWS Greengrass provides cloud-based management of applications that can be deployed for local execution. Locally deployed Lambda functions are triggered by edge computing definition local events, messages from the cloud, or other sources. The goal of Edge Computing is to minimize the latency by bringing the public cloud capabilities to the edge.