Recently, the term "edge computing" has garnered considerable attention. While the shift from on-premises to cloud computing has been widely discussed until now, the future may see a distributed architecture combining both cloud and edge computing become the standard.
Edge computing offers significant benefits such as real-time responsiveness, low latency, and enhanced security. It is particularly gaining momentum in businesses centered around data utilization and application.
In this article, we'll clearly outline what edge computing is, its advantages, and practical examples.
Edge computing refers to a network technology where data processing, including data analysis and manipulation, is performed on distributed edge platforms (such as edge servers) placed physically close to the user or IoT devices.
Key characteristics of edge computing are "proximity to users or devices" and "distributed processing." In contrast, traditional cloud computing employs centralized processing, aggregating all data directly from devices to the cloud. Edge computing differs significantly; edge servers located near IoT devices first process the data and then send only essential processed data to the cloud.
Edge computing offers several benefits compared to conventional network architectures or pure cloud computing approaches. Here are the top three advantages:
1. Real-time capabilities and low latency
By processing data at the edge—closer to users and devices—edge computing reduces system loads and communication delays, improving overall real-time responsiveness.
2. Enhanced security
IoT implementations face significant security vulnerabilities. Edge computing processes data locally near devices and sends only aggregated results to the cloud. This reduces the amount of data transmitted over external networks, mitigating the risk of data leaks.
3. Reduction in data transfer costs
As processing occurs on edge servers and only essential data is transmitted to the cloud, edge computing decreases data bandwidth consumption, significantly reducing transfer expenses compared to traditional cloud computing environments.
Edge computing supports numerous practical scenarios. Here are three prevalent examples:
1. IoT implementations
Globally, IoT increasingly relies on edge computing, notably within manufacturing. Factories and production environments produce enormous volumes of data from sensors and measurement devices, making centralized cloud-based aggregation challenging. Edge solutions offer essential benefits like low latency and improved security.
2. Edge AI applications
Edge AI involves implementing artificial intelligence and machine learning models directly within edge devices. Applications range from autonomous driving and smart retail to smartphones and wearables, allowing rapid detection and decision-making at the point of interaction.
3. 5G technology integration
Currently, rising adoption of 5G—with attributes like high-speed, high data capacity, ultra-reliability, low latency, and massive simultaneous connections—is challenged by centralized cloud computing's server load and latency. Edge computing addresses these challenges by reducing latency and server overload through distributed processing, enabling optimal performance under 5G standards.
Edge computing brings numerous benefits but also poses challenges, including:
● Increased costs
As a distributed model, edge computing often results in higher infrastructure costs due to multiple edge servers and complex systems that necessitate higher deployment, maintenance, and management expenditures.
● Need for additional operational personnel
Increasing edge infrastructure inevitably requires more skilled personnel to manage servers. Effective solutions typically involve centralized management platforms that optimize remote control capabilities and minimize the operational workforce required.
Here's an example of employing edge computing: utilizing Volterra, a management tool especially valuable for IoT-focused industries such as manufacturing.
● What is Volterra?
Volterra, provided by the US-based firm Volterra, facilitates application delivery to distributed edge devices and centralized management of edge device connectivity. Its core services consist of "VoltStack," "VoltMesh," and "VoltConsole."
This combined toolset enables secure and centralized management across edge computing environments and has drawn significant interest in data-driven business scenarios involving complex interactions in distributed infrastructures.
● IoT Use Case: "IoT Gateways for Manufacturing and Logistics"
Common industry challenges:
Manufacturing and logistics sectors often need to manage thousands of edge-connected devices, with critical requirements for efficient device, application, and security management.
Solution:
Deploying Volterra as edge gateways streamlines remote management of connected edge devices. By enabling centralized security and application policy distribution, Volterra ensures improved application management, security control, and flexible application infrastructures compared to legacy systems.
Edge computing is gaining market traction due to its inherent advantages: real-time data processing, lower latency, and improved security. Moving forward, edge computing is anticipated to evolve further by effectively integrating with cloud computing solutions.
Critical success factors include addressing core challenges such as high infrastructure costs and operational complexity through efficient centralized management solutions. Developing appropriate knowledge and expertise will be crucial for successfully deploying and implementing edge computing. To learn more, reach us directly through the following link.