Edge computing is a modern IT architecture to bring data analytics closer to the source of data. It's useful for IoT technology, remote work and transmitting data as efficiently and rapidly as possible. This type of networking is provided by Amazon Web Services, Dell, Cloudflare and other tech giants. Here are important points to know about edge computing for improving your business network.
Data Collection at the Edge Layer
Part of venturing into big data involves managing a high volume of data transmission to prevent or reduce network latency. The more congested a network becomes with data exchanges, the less reliable transmission performance and speed will be. The amount of bandwidth you use plays a major role in how much data you're able to transmit or receive on a network.
A solution to this big data congestion problem is edge computing. The term "edge" may refer to a network hub that collects IoT data from various sensors. It may also refer to gateways and bridges between local infrastructure and the public internet. Edge computing is the second of six layers of IoT architecture. The other layers involve IoT platforms and devices, connectivity, data management and applications.
Components of an app that collect real-time data from IoT sensors can be embedded in edge servers. That was the way edge computing began to evolve commercially earlier this century to make video and web content closer to users. Today, edge computing solutions include online shopping carts and web widgets that present data in real time.
If your goal is to manage big data more efficiently, edge computing might be the solution for you. Not only does it provide cost efficiency, it delivers faster response times.
Watch the replay of our Living on the Edge webinar where our speakers break down the complexities of edge computing and provide strategies for successfully deploying edge solutions.
Who Typically Uses Edge Computing?
Edge computing has been embraced by organizations that regularly transmit a high volume of data. Industrial firms use edge computing for their robust control systems. This architecture has also become common with the telecommunications and media industries. Other industries that use this method to streamline operations include retail, manufacturing, healthcare, construction, transportation and agriculture.
A factory or warehouse is likely to use edge computing as a way to manage daily high volumes of data without sending it to the cloud. Farms are starting to embed sensors in fields to monitor crop development and environmental conditions. Autonomous vehicles that are being developed for industrial use are full of IoT sensors, in which keeping data localized is more practical than cloud computing.
The more a business collects big data without sending it to the cloud, the faster it can learn how to streamline its operations without slowing down the network. Any business using applications that require immediate insights or control based on real-time analytics can be enhanced with edge computing. Collecting high-volume data in multiple remote locations is another scenario in which edge computing is the more effective selection.
How Edge Computing Works
Edge computing has been around for about as long as the web, as it developed throughout the nineties. It started with remote computing, such as branch offices connecting with a central location. Traditionally, data was processed at the user or client-side, then was transmitted over the internet to a LAN, where it was stored. The data could then be processed using an enterprise app. Ultimately, the data was sent back online to a client device.
In a more updated paradigm, IT architects have reimagined how edge computing can be even more efficient. Instead of relying on the centralized data center model, a more modern solution is to design an edge infrastructure. While an edge infrastructure may include cloud solutions, it typically comprises many small data centers.
The focus has sharpened more on building an infrastructure full of business intelligence. Here are some of the most valuable forms of business intelligence associated with IoT sensors:
- Video surveillance systems
- Real-time sales data
- Predictive analytics to trigger automated repair
- Power generation data
- Data for evaluating product quality
Key Applications for Adopting Edge Solutions
The more concern you have for managing quantity of data, the more you should consider edge solutions in your networking. Here are some of the main reasons for adopting the edge that cross all types of business:
- Improve your network performance - Since IoT devices will handle data processing, your network won't be strained with big data. You can cut costs and preserve bandwidth for other business activity. An edge solution gives you greater control for clearing out network congestion. Additionally, edge computing selects a path with the lowest latency and least resistance for data transmission.
- Add IoT devices to your infrastructure - It's important to view IoT and edge as separate, but overlapping concepts, rather than synonyms. IoT devices such as smartphones, smartwatches and smart thermostats connect with the internet using edge computing.
- Use wearable technology - The healthcare industry has helped pioneer wearables as a form of remote monitoring. Now millions of seniors wearing items with embedded sensors can be remotely tracked by their doctors. Wearables allow for continuous connection with patients to monitor heart rate, blood pressure and various other biological activity.
- Track retail sales - Retail stores use edge solutions for sales analysis, inventory, security and surveillance tracking. Sensors can be embedded at point-of-sale stations to track sales as they occur in real time. You can easily access this data on your smartphone. Since you'll be able to track a vast amount of sales data, you'll build a knowledge base for machine learning software to scan historical financial information.
- Improve products based on tracking data - Manufacturers use IoT and edge computing for continuously monitoring system processes. Due to the efficient use of vast data, an edge solution allows manufacturers to quickly detect system flaws, such as in production equipment. Machine learning software can quickly provide problem-solving recommendations.
- Promote sustainable practices - Using edge computing is a step toward sustainability in the sense that it cuts costs, reduces waste and conserves resources.
Main Benefits of Edge Computing
Four top benefits when deploying an edge computing solution are latency reduction, bandwidth conservation, cybersecurity solutions and increased reliability. Big data can eat up limited bandwidth, so the solution is to transmit data more efficiently.
Edge computing is all about reducing the distance data has to travel from point A to point B. It's ideal for organizations that prioritize data speed, as an edge solution reduces network latency. Any business that profits from streaming live data can benefit from edge strategies.
Concerns About Edge Computing
In the process of data transmission, data can get intercepted by third parties without a strong cybersecurity solution. The more IoT devices and data occupy a network, the more you increase risks of a cybersecurity breach. Even the best cybersecurity technology can be compromised if a hacker is persistent. Processing data at network edges is safer than across multiple internet hubs.
Reliability of data transmission is another key concern when using edge computing. If connectivity is lost, do you have a backup plan? Keep in mind, it's possible for data to be corrupted or lost without hackers involved. When network connectivity becomes unreliable, it can be at the expense of profits, such as with trading stocks online. Edge computing improves reliability, as long as you have a backup plan if your main network goes down.
Why Many Businesses Prefer the Cloud
Some of the main reservations business managers have about edge adoption is that its purpose typically is limited, compared with the multi-purpose nature of the cloud. The issue of connectivity is a big factor that drives certain businesses to cloud services that are "always on." A 24-7 online ecommerce site cannot afford much downtime. In that sense, the cloud is usually more reliable.
Even though edge computing provides strong security, the more devices you put on a network, the more vulnerable it becomes. Many businesses don't want the trouble of handling cybersecurity issues with in-house personnel, so they outsource to reputable data centers. IT specialists at the data centers take care of network monitoring, making the cloud a turn-key solution for many companies.
Edge vs. Cloud Comparison
There's no reason to view the edge as competing with the cloud, since both computing solutions have advantages for certain scenarios. You may decide to adopt a hybrid "cloud edge" strategy. FedEx, for example, uses a cloud edge strategy that supports IoT, robotics and automated processing.
While edge computing has storage limitations, cloud computing offers unlimited storage possibilities for websites. At the same time, edge computing provides faster data transmission and greater data protection. Overall, the edge is more efficient for remote tracking, whereas it takes more time to send data to the cloud.
If your goal is to manage big data more efficiently, edge computing might be the solution for you. Not only does it provide cost efficiency, it delivers faster response times.