In this special guest feature, Wayne Carter, VP Engineering of Couchbase, discusses the current state of edge computing, while digging into the different types of edge (including micro edge, mini edge, medium edge, heavy edge and multi-access) and when it makes sense to use them. Wayne is an innovative technology leader driving the creation of large-scale applications and technologies spanning mobile, IoT, edge computing, database, middleware, security, cloud and SaaS.
Fueled by the proliferation of AI, 5G, networking and IoT technologies, investment in edge solutions is projected to rise to around $274 billion through 2025, according to research by IDC. By moving compute closer to where the data is created, organizations experience enhanced efficiency, reduced latency and increased uptime – ultimately improving the customer experience.
However, in order to make the most of edge computing, it’s important to understand the various types of edge solutions and when it makes sense to use them.
- Micro Edge refers to edge computing devices deployed at the very edge of the network, such as on a phone or embedded system. These devices have limited processing power and storage capacity and are designed to handle simple tasks such as data collection, pre-processing and basic analytics.
- Mini Edge refers to edge computing devices deployed at the edge of the network, such as at the building or campus level. These devices have more processing power and storage capacity than Micro Edge devices, and are designed to handle more complex tasks such as data processing, analytics and machine learning.
- Medium Edge devices are deployed at the edge of the network, but at the city or regional level. These devices have even more processing power and storage capacity than Mini Edge devices, and are designed to handle even more complex tasks such as data processing, analytics and machine learning, in addition to more advanced applications such as augmented reality and virtual reality.
- Heavy Edge devices are deployed at the edge of the network at the data center or cloud level. These devices have the most processing power and storage capacity of all edge computing devices, and are designed to handle the most complex tasks such as data processing, analytics and machine learning, as well as advanced applications such as artificial intelligence and deep learning.
- Multi-Access Edge (MEC) is a type of edge computing deployment where devices are deployed at multiple levels of the network, such as at the device, building, city and data center levels. These devices work together to provide a seamless and efficient edge computing experience, with each level of device providing different capabilities and resources.
The Current State of Edge Adoption
In general, Mini Edge and Medium Edge are currently the most widely adopted types of edge computing solutions. These devices offer a balance of computing power and storage capacity, making them suitable for handling complex tasks such as data processing, analytics and machine learning. Micro Edge devices, such as phones and tablets, are also popular for specific use cases, particularly in industries where employees need access to business-critical data and processing capabilities while on-the-go, regardless of internet connectivity or speed.
Additionally, there is an increasing trend of MEC adoption, particularly in the airline and cruise line industries, as they take advantage of new public and private 5G networking solutions, and satellite networks like SpaceX Starlink to provide seamless connectivity.
The combination of MEC, next-gen networking and distributed database tech delivers improved performance, enhanced security, cost savings, scalability and increased availability beyond what cloud computing and centralized databases can deliver alone. More specifically, this includes:
- Improved Latency: MEC reduces latency by processing data closer to the end-users, resulting in faster response time and improved user experience.
- Increased Network Capacity: MEC enables processing at the edge, freeing up bandwidth and reducing strain on the centralized network.
- Enhanced Security: MEC provides increased security as data is processed and stored close to the source, reducing the risk of cyber attacks.
- Cost Savings: by processing data closer to the source, MEC reduces the amount of data transmitted over the centralized network, leading to cost savings on network infrastructure and bandwidth.
- Scalability: MEC enables processing at the edge, freeing up resources on centralized systems.
- Availability: by storing and processing data on devices, MEC can continue to operate even when it is disconnected from the rest of the system.
Classifying Popular Edge Computing Industry Use Cases
Edge computing continues to gain momentum across industries, especially those that require agile applications that deliver premium experiences to end-users. These include:
- Industrial Internet of Things (IIoT), whichtypically falls in the category of Mini Edge or Medium Edge, where edge computing devices are used to collect, process and analyze data from industrial machines and equipment, allowing for real-time monitoring and control of the manufacturing process.
- Autonomous vehicles fall in the category of Medium Edge or Heavy Edge, where edge computing devices are used to process and analyze sensor data from autonomous vehicles, allowing for real-time decision-making and navigation.
- Medium Edge comprises smart cities, where edge computing devices are used to collect and process data from smart city infrastructure, such as traffic lights, cameras and sensors, allowing for real-time monitoring and management of the city’s infrastructure.
- Healthcare use cases typically fall in the category of Medium Edge or Heavy Edge. Devices are used to collect, process and analyze data from medical devices, such as wearables and diagnostic equipment, allowing for real-time monitoring and analysis of patient health data.
- Retail typically falls in the category of Medium Edge, where edge computing devices are used to analyze data from in-store cameras, sensors and other devices, allowing for real-time monitoring of customer behavior and inventory management.
As more and more organizations adopt edge computing strategies, making sense of the various types of edge computing and knowing when to use them will be a critical component to succeeding in today’s competitive business landscape.
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