What Is Edge Computing Used For? Everything You Need to Know

The exponential growth and increasing computing power of IoT devices have resulted in unprecedented volumes of data. As a consequence, the impact of this increase in data has resulted in reduced processing power and transmission speed, as data collected by IoT devices have to be sent to a central server in the cloud for processing before being transmitted back to the intended data destination. This has resulted in reduced throughput capacity of all IoT devices, until edge computing came into the picture!

The use of edge computing is revolutionizing data processing, accelerating response times, and solving connectivity, scalability, and security problems associated with remote servers, becoming a great solution for more and more industries and companies all over the world. But… What is edge computing? What is this technology used for? How can businesses benefit from it? Here you will find everything you need to know about the world of edge computing and its recommended hardware.

What Is Edge Computing?

Edge Computing is a technology in which processing and computing are performed at the edge of the network and closer to the source of the data, mainly on smart devices or edge devices as opposed to processed in centralized cloud-based systems or data centers. In simple words, its overall purpose is to process and store data all the way to the devices that generate it, eliminating the dependence on servers in the cloud or in data centers located thousands of miles away. Unlike the cloud, which requires high bandwidth-intensive IoT integration data transfer, edge computing increases bandwidth utilization efficiency by analyzing data at the edges themselves, making it suitable for use in remote locations at minimum cost.

How does edge computing work?

The volume of data being generated at the edge is growing exponentially faster than the ability of networks to process it. Edge computing captures and processes information as close to the data source as possible. Contrary to traditional computing, edge computing was conceived as a way to enable data to be delivered to a specific edge computing device that can process and analyze the information with greater agility and lower latency. Edge computing not only maximizes the company’s operational possibilities but also contributes to solving the problem of data accumulation, especially in closed IoT systems.

Why is edge computing important?

Edge computing is not only important for one or another aspect of organizational structures. It is a technology with the potential to revolutionize the way companies operate. The importance of edge computing lies in its capacity to capture and analyze data, which enables virtually immediate decision-making. Furthermore, this technology minimizes the risk of data leakage since data is stored locally according to processing capacity. Implementing edge computing can help reduce the time lag between data transmission, processing, and the final action required.  Event analysis and processing can be carried out faster and more cost-effectively since most of the raw data does not need to be transmitted to the cloud for processing and analysis.

Unlike cloud data centers, which can be located thousands of miles away from the connected device and take tens to hundreds of milliseconds to process data, edge computing has the power to reduce this cycle to a few milliseconds. The ultimate goal of edge computing is to serve as a reliable and scalable solution to ensure data, especially real-time data, does not suffer from latency issues that can affect the purpose or performance of an application.

Edge Computing Use Cases and Examples

Edge computing is widely used in all industries and across organizations.  The most common industries that implement edge computing solutions include:

• Manufacturing Industry: In a manufacturing plant, sensors and control devices can accumulate operational data, feeding the processing systems at the edge to organize the operational routine, create customized preventive maintenance programs, or make decisions without human intervention, reducing unnecessary time and costs.
• Healthcare Software: the healthcare field, telehealth technology is necessary to process data in real-time, regardless of the quality of the Internet connection device, to access the patient’s history immediately and without errors. Plus, with edge computing, machine learning, and AI applications can be used to identify patterns and improve healthcare.
• Security Solutions: Emergencies happen unexpectedly and responding to threats within seconds is necessary. Security surveillance systems can benefit from edge computing technology to identify potential threats and alert users to unusual activity in real time.
• Retail Advertising: Retail information and targeted ads are based on important criteria, such as demographic information, set on field devices. Edge computing can help preserve user privacy in this scenario by encrypting the data and maintaining the source instead of transmitting unprotected data to the cloud.
• Smart Cities: Edge computing plays a key role in traffic control, with various applications, such as optimizing the frequency of public transport according to demand and managing the opening or closing of lanes and bridges.
• Self-Driving Vehicles: Autonomous vehicles need to make decisions incredibly fast so edge computing IoT provides a real-time data stream even if the vehicle is offline, key for the safety and overall operation of the machine.

What are the benefits of edge computing?

The deployment of edge computing technologies can bring a lot of benefits to companies as it possesses several advantages. Among the most significant are the following:

• Reliability: Using IoT edge computing devices and edge data centers located closer to end users, there is less chance of a network problem occurring on a local client in a distant location.
• Data security and privacy: Privacy is increased as the raw data needed for deep learning services is stored locally and not in the cloud. This means that fewer data will be transmitted over the Internet, which could help increase security by reducing the risk of interception.
• Lower latency: Deep learning services are deployed close to the requesting users without the need to send information to the Cloud. Therefore, an edge application shortens distance to merely tens of kilometers away or on-site, thus reducing latency.
• Reduces operational costs: Reduction in operational costs allows a decrease in data transmission prices because the infrastructure for centralized points is larger and more expensive compared to what would be spent when implementing an edge computing device.

Challenges of edge computing

Successful operation of edge computing can pose some challenges. Before using this technology, several considerations must be taken into account:

• Control and management: Although the location of the edge may be flexible, management and control should adhere to the same procedures wherever, regardless if the edge is physically located. To assist manage and control applications effectively, organizations should adopt new monitoring tools, to make sure everything is working properly, regardless of their location.
• Network bandwidth: As businesses send data and computing to the endpoints, network bandwidth fluctuates. Typically, enterprises allocate data centers more bandwidth and endpoints less, but edge computing is increasing the demand for higher network bandwidth.
• Scale: Adding more connected devices at the edge increases the overall scale of everything the IT teams work on. Edge computing is not simply more servers at the edge, but an increase in scale across all IT disciplines: computing, network, storage, management, security, licensing, etc.

Conclusion

As IoT continues to grow and develop, the number of businesses with multiple sites increases. As more and more data is being generated outside the data center, it becomes necessary to deploy computing systems at the edge. These systems must be cost-effective and lightweight to be deployed in many small locations and managed, ideally, from one central location. With that in mind, Azulle has designed reliable, customizable, and cost-effective hardware specifically engineered to keep your company’s data protected and serve as the ideal solution for edge computing.

Thinking about deploying edge computing hardware across your company?

Learn more about Azulle hardware for edge computing by visiting https://azulle.com/edge-computing/ or by contacting us at sales@azulle.com. Our team of technology experts will be happy to help you choose the right technology solution and facilitate the possibility of edge computing for your business.