Edge Computing is exploding due to the enormous amount of data generated by IoT and IIoT devices. As 5G networks grow and 5G becomes more commonplace, more data will be generated than ever before from new devices coming online. So, many businesses are finding it very effective to use edge computing to perform real-time, low-latency data analysis. Edge computing has enabled local processing of data close to the source of data generation. Experts estimate that edge computing will reach its peak in the very near future. So, you might be wondering, what is edge computing? What are the benefits of edge computing? And what is the edge in edge computing? We will answer all of these questions in much detail below.
What is Edge Computing?
Edge computing is a decentralized computing framework where computing power is brought closer to the source of data generation. Edge computers are like mini data centers processing and storing data, only sending essential data to the cloud for storage or post-processing. For example, edge computing solutions are deployed close to IoT and IIoT devices, delivering real-time data collection, storage, and processing. This reduces the amount of latency involved and reduces the amount of internet bandwidth required by IoT devices.
Edge computing has taken off because sending all of the data generated by IoT devices and IIoT devices to a centralized data center for processing and storage results in latency and bandwidth issues easily solved by edge computing.
Edge computing alleviates the burden placed on data centers by processing and storing IoT and IIoT device data locally at the source where the data is created. Sending less data to data centers saves organizations deploying edge computers a significant amount of money on bandwidth costs. Additionally, processing data locally results in significantly less latency since data does not need to travel long distances from the origin device to a data center and back. As 5G becomes more commonplace, edge computing will only become more common and faster, improving organizations’ experiences depending on edge computing.
Edge computing is essential for organizations and businesses because of the insights generated by collecting, processing, and analyzing the data generated by thousands of sensors and connected devices that are commonplace in industrial settings, such as manufacturing facilities.
Analyzing the data generated by IoT and IIoT devices can provide deep insights into the operations of a business, allowing organizations to act quickly on real-time data. The ability to react to insights in real-time enables businesses and organizations to improve their productivity and the quality of products or services provided by them. That said, to extract invaluable insights from your data, computing power must move to the edge close to the source of data generation.
That said, even though edge computing is gaining massive popularity, cloud computing still has its place in today’s modern world. Edge computing complements cloud computing by enabling applications that require real-time, low-latency data processing.
What is the Edge in Edge Computing?
In the context of edge computing, the edge refers to the source of data generation. For example, if you have IoT devices or sensors deployed to monitor the growth of crops, the edge would be somewhere close to the sensors and IoT devices generating data. The edge is different from the cloud, which is often located thousands of miles away from the devices generating data. That said, the question of where is the edge is different from one application to another because it depends on the topology. But, typically, the edge is usually closer to the data generating devices than the cloud.
What Are the Benefits of Edge Computing?
Edge computing offers several benefits that we will explore in much detail below:
1. Low Latency Computing
One of the main benefits that edge computing offers is that it offers significantly lower latency than cloud computing. Low latency is vital for applications that require real-time data processing and analysis where every millisecond counts. Although some applications may require a latency of 100 milliseconds, there are mission-critical applications that require significantly less latency that can only be achieved by edge computing. Edge computing offers lower latency because edge computers are often deployed close to the source of data generation, reducing the distance that data has to travel for processing and analysis.
2. Lower Bandwidth Utilization
The second benefit of edge computing is that it reduces the amount of internet bandwidth required. Less bandwidth is needed for edge computing because the data is collected, stored, and processed locally on edge computers, negating the need for all raw data to be transferred to data centers for processing and analysis.
That said, processing data locally does not mean that no data has to be sent to the cloud, but that less data must be sent to the cloud. This is so because data that set off specific triggers is sent to the cloud for post-processing and analysis. Doing so reduces the amount of internet bandwidth required. For businesses and organizations that are on metered data plans, this will result in significant cost savings.
3. Alleviates the Burden on Data Centers
With the amount of data growing exponentially, alternatives are being sought to alleviate the stress placed on data centers. Edge computing can lessen the stress placed on data centers by storing and processing data locally on edge computing devices. Edge computers have come a long way and can be configured with powerful processors and large amounts of high-speed data storage, enabling them to process and store data at the edge instead of the cloud.
4. Workload Consolidation
Deploying edge computing devices can save businesses and organizations a significant amount of money by consolidating workloads onto fewer devices. This enables organizations to reduce their hardware footprint and reduce failure points since fewer components can fail. Additionally, by consolidating workloads using edge computers, businesses and organizations will have fewer devices to maintain and monitor.
5. Predictive Maintenance
One of the benefits of deploying edge computers is that they enable predictive maintenance. That is, edge PCs can monitor the data collected from various devices and sensors to ensure that machinery and equipment are running normally and optimally. Moreover, edge computers can use AI and Machine Learning (ML) algorithms to detect when a failure is likely to occur, prompting management to perform maintenance or replacement components before a failure occurs. This can save businesses a significant amount of time and money since maintenance can be performed conveniently without abruptly stopping production.
6. Data Security
Edge computing offers data security since fewer data has to travel to the data center, reducing the chances of data being mishandled or misappropriated as it travels to a data center. Additionally, edge computers come equipped with TPM 2.0, which protects devices through authentication and key management. Additionally, distributing processing, storage, and applications across a wide variety of computing devices makes it difficult for a single disruption to take down the entire network.
7. Reliability
Edge computing hardware is ruggedized, making edge computers more reliable than ever before. Rugged edge computers can be deployed in remote and challenging environments while they withstand exposure to harsh environmental factors that servers and regular desktop computers cannot endure. Additionally, edge PCs are equipped with various wired and wireless connectivity options, ensuring that edge devices remain connected to the internet even in remote environments where stable internet connectivity is not always available.
Disadvantages of Edge Computing
Here are some of the disadvantages associated with edge computing:
1. Scalability
Scaling cloud computing is easier than scaling edge computing because more storage and compute power can easily be added via the click of a mouse button with the cloud. This is different from expanding edge computing, where devices must be added or physically upgraded for an organization to achieve more compute power or storage space.
2. Security
Securing a distributed edge computing network can be difficult and often require physical access to each individual deployed device. Additionally, adding several edge computing devices increases the surface area for attacks. Nevertheless, edge computers come equipped with TPM 2.0 that secured devices from physical attacks through authentication and key management.
3. Storage Space
Edge computing requires more storage space than data center servers. However, as the capacity of solid-state data storage increases and SSDs become less expensive, plenty of storage can be had at the edge, alleviating the burden on data centers to store all IoT and IIoT data.
4. Maintenance
Edge computers may necessitate more maintenance than servers, and accessing edge PCs is often more difficult and time-consuming than accessing servers. This is so because edge PCs are distributed, and maintenance may require visiting each location where a device is deployed. This may cost organizations more money than choosing a centralized computing solution.
Why Does Edge Computing Matter?
Edge computing matters because it is necessary to accommodate that significant increase of data generated by IoT and IIoT devices. All of the raw data that’s generated must be processed and stored, necessitating the need for edge computing devices to process and store data locally to ease the burden placed on data centers.
Edge computers are like mini data centers located close to the source of data generation. Edge computers can alleviate the stress on data centers by processing and storing data locally, only pushing specific essential data to the cloud. Edge computing is different from cloud computing in that most data is processed and stored locally, with only some relevant or important data being sent to the cloud. This significantly reduces the amount of data that data centers have to process or store.
Take, for example surveillance systems. In old systems, all raw footage was uploaded to the cloud for remote monitoring. However, intelligent surveillance systems are equipped with edge computers that store, process and analyze video footage, only uploading video footage that sets off specific triggers to the cloud for remote monitoring and control. Only sending some video footage vs. sending the entire video footage significantly reduces the stress placed on data centers. So, there is no doubt that edge computing will play a vital role in the future to alleviate the stress placed on data centers from the explosion of data.
Computing at the Edge: Rugged Edge Computing
Edge computers deployed at the edge are often ruggedized to endure the challenging environments in which they are deployed. Systems deployed in factories, manufacturing facilities, and outdoors must be able to tolerate exposure to harsh environmental conditions that regular, consumer-grade desktop computers are not capable of handling.
Rugged edge computing solutions are fan-less, meaning they are passively cooled via the use of heatsinks. Passively cooling edge computers allow system manufacturers to eliminates all openings, makes it difficult for dust and small particles to enter the system and damage the sensitive internal components.
Additionally, edge computers are equipped with a wide operating temperature range, ranging from -40°C to 85°C. Having a wide operating temperature permits deployers to deploy them in extremely cold or scorching environments.
Furthermore, rugged edge PCs are equipped with shock and vibration resistance. Systems are capable of withstanding 5Gs of shock and 50GRMs of vibration in compliance with the MIL-STD-810G. This allows organizations to deploy systems in environments where the industrial PC will be exposed to frequent and continuous shock and vibration.
Moreover, systems can be configured with SSDs for additional shock and vibration resistance. SSDs (solid-state drives) can handle exposure to shock and vibration better than HDDs (hard disk drives) because they store on solid silicon NAND chips that are more durable than the spinning metals platters that HDDs use to store data.
Rugged edge PCs are made using industrial-grade components tested and validated to endure deployment in harsh environmental conditions that regular, consumer-grade desktop PCs cannot handle.
Also, rugged edge computing solutions are equipped with rich connectivity features that keep rugged industrial PCs connected to the internet no matter how remote the deployment environment. Systems are equipped with Wi-Fi 6 for ultra-fast, low latency connectivity, and dual SIM sockets, enabling users to install two SIM carriers for redundant 4G, LTE, or 5G connectivity.
What is the Difference Between Cloud Computing vs. Edge Computing?
Cloud computing is a centralized computing framework that offers unlimited computing power and storage. With cloud computing, users connect to data center computers over the internet and pay for the resources (compute power & storage) they use. Cloud computing is used for various use cases, such as storing backups, email, virtual desktops, big data analytics, and a variety of other use cases. Cloud computing is often used because it provides businesses and organizations with a way to obtain quick access to compute power, storage, and databases without investing in the underlying infrastructure.
On the other hand, edge computing is a decentralized computing framework where many industrial-grade PCs are deployed at the edge close to the source of data generation to process sensitive data in real-time. Edge computing is preferred over cloud computing in some cases because it provides ultra-low latency and saves businesses a ton of money on internet bandwidth.
Edge computing is akin to bringing the cloud to you. It offers lower latency than the cloud because data is processed close to the source of generation, eliminating the need for data to travel thousands of miles to a data center for processing. It has the potential to save businesses a ton of money on internet bandwidth because data is processed locally, eliminating the need to send all raw data to the cloud to the cloud. Instead, only critical data is sent to the cloud for remote monitoring.
For example, suppose an organization is developing an autonomous vehicle. In that case, it needs rugged, industrial-grade computers to capture data from sensors, high-resolution camera, and other devices deployed in the vehicle. The amount of data generated from sensors and cameras is too large to wirelessly upload to the cloud, necessitating deploying rugged edge computers equipped with ultra-fast NVMe storage and powerful processing power to collect and store the data in real-time.
Also, edge computing solutions are excellent for remote deployments where there is limited or no wireless connectivity. Edge computers can function without the internet, uploading critical information to the cloud when internet connectivity is available. Furthermore, edge computers are equipped with wireless connectivity features that include the latest Wi-Fi 6 and cellular connectivity thanks to the availability of Dual SIM sockets, enabling the addition of dual SIM cards for redundancy. Systems can be programmed to connect to a second carrier if the primary carrier does not offer connectivity.
Although edge computing has some advantages over cloud computing, it is not replacing cloud computing but merely an additional computing framework that complements cloud computing by enabling additional applications at the edge.
What Are Some Examples of Edge Computing?
Let’s explore some common examples of edge computing.
1. Vehicle Fleet Management
Rugged edge computing devices are often deployed in vehicle fleets to intelligently manage fleets because they can tap into a vehicle’s CANBus network, collecting and relaying a variety of rich information, such as vehicle speed, engine speed, steering angle, miles driven, maintenance needs to the cloud. Once information is relayed to the cloud, fleet managers can monitor the performance of their fleets and improve them using the valuable insights gleaned from the massive amount of data collected from fleet vehicles. Fleet managers can use the data to optimize routes, optimizes schedules, and perform predictive maintenance on fleet vehicles. This improves the performance of the fleet and reduces operational costs.
2. Industrial Automation & Control
Edge computers are also often used in product manufacturing facilities for industrial automation and control purposes. For example, edge computers enable communication between factors machines, sensors, and equipment. Also, they allow communication between such devices and the internet, allowing them to offload critical information to the cloud for remote monitoring and control. Additionally, edge computers are capable of consolidating workloads by grouping multiple operations onto a single system. This simplifies the system and results in better efficiency.
3. Remote Monitoring of Oil & Gas Assets
Edge computing solutions are often deployed in oil and gas fields to monitor and control the enormous amounts of assets deployed in oil and gas fields. For example, edge PCs are used to monitor the flow of fuel in pipelines, providing gas and oil production facilities with invaluable insights into their operations. This allows them to uncover critical issues and respond to them quickly.
4. Smart Agriculture
Edge PCs are also often deployed as IoT gateways for smart agriculture applications. For example, edge computing solutions are often used to gather, process, and analyze weather conditions, soil moisture, sunlight, and other variables to improve the growth of crops. Additionally, the insights brought by data gathered from IoT edge computers can be used by farmers to predict the crop output, allowing farmers to plan the distribution of their crops better once they’re ready to be cultivated and sold.
5. Intelligent Surveillance Systems
Edge computing solutions are also deployed as part of intelligent surveillance systems thanks to the ability to deploy them indoors and outdoors in harsh environmental conditions. Rugged edge computers are used to gather, process, and analyze video footage, only sending footage that sets off specific triggers to the cloud for remote monitoring and control. This is different from non-intelligent surveillance systems that upload all video footage to the cloud. Intelligent surveillance systems powered by edge PCs reduce the amount of internet bandwidth required by the system since only some footage is sent to the cloud.
6. Kiosk Machines
Rugged edge computing solutions are often deployed in kiosk machines like the ones that you walk past in grocery stores, airports, and other public locations. Edge PCs are often used because they are equipped with a rich I/O that allows them to connect to the variety of peripherals usually found on kiosk machines. Peripherals include bill readers, barcode scanners, fingerprint scanners, cameras, monitors, receipt printers, and other peripherals commonly found on kiosk machines. Additionally, kiosk PCs are hardened to endure the challenging environmental conditions of kiosk machines, making them the ideal solution for deployment in kiosks. Additionally, they are equipped with rich wireless connectivity, keeping kiosk machines connected to the internet to serve customers.
How Will 5G Boost Edge Computing?
5G offers improved latency that is far superior to the outgoing 4G technology and offers 10x more speed than 4G closer to the end-user, significantly improving the performance of applications and enabling systems to process huge amounts of data in real-time to provide improved customer service. 5G facilitates bringing cloud-like processing power, storage, and networking closer to the edge where end-users are located.
Additionally, edge computing combined with 5G enables artificial intelligence, machine learning, IoT processing, and decision making at the edge, which was previously difficult to do at the edge. This is so because 5G and edge computing enable ultra-fast processing of information. This is so because processing information at the edge, close to 5G antennas, reduces the distance and time for data transmission, enabling real-time processing and decision making. Low latency is a determining factor for many advanced applications. 5G enables such applications because it promises a latency of 1 to 2 milliseconds, improving the performance of applications.
Premio’s Edge Computing Solutions
Premio has been designing and manufacturing edge computing solutions in the United States for over 30 years. Premio offers a wide variety of edge PCs, ranging from entry-level systems ideal for IoT processing and more advanced AI edge computers capable of performing GPU accelerated inference analysis at the edge. If you need assistance finding an edge computing solution, please contact us. One of our edge computing professionals will assist you with finding a solution that meets your specific requirements.
