What is edge computing?
Edge computing represents a developing computational framework that encompasses various networks and devices located at or near the user. This approach focuses on processing data closer to its source, which facilitates quicker data handling and higher volumes, ultimately resulting in immediate, action-oriented outcomes.
This model provides distinct benefits compared to conventional systems that centralize computing resources within on-site data centers. By decentralizing computation, organizations can enhance their management of physical assets and foster innovative, interactive human experiences. Notable applications of edge computing include self-driving vehicles, autonomous robotics, smart equipment analytics, and automated retail systems.
Why is edge computing important?
A significant portion of today’s computing already takes place at the edge, in environments like hospitals, factories, and retail locations, where sensitive data is processed and critical systems are powered, requiring a reliable and safe operation. These settings demand low-latency solutions that function without the need for a constant network connection. The excitement around edge computing stems from its ability to revolutionize businesses across all industries and functions, from customer interaction and marketing to production and back-end processes. In all instances, edge computing makes business operations more proactive and adaptive, often in real-time, leading to enhanced and optimized experiences.
Edge computing bridges the gap between the digital realm and the physical world. It integrates online data and algorithms into traditional retail environments to elevate shopping experiences. It also fosters systems where employees can train alongside machines, creating opportunities for learning and development. Furthermore, it enables the design of intelligent environments that prioritize our safety and comfort. All these scenarios share a common thread: edge computing empowers companies to execute applications with stringent reliability and real-time data demands directly on-site. Ultimately, this capability accelerates innovation, facilitates the rapid launch of new products and services, and creates new avenues for revenue generation.
The transformative potential of edge computing is what makes it so compelling, as it can reshape business operations across every industry and function, enhancing everything from customer interactions to production processes.
What Are the Different Types of Edge Computing?
Edge computing comes in various forms, and organizations can choose one or more based on their specific computational requirements or those of their products. Some types are built for managing simple tasks, while others are designed for more advanced processes. Additionally, edge computing servers are capable of supporting the deployment of entire edge networks.
Edge computing for basic events
Simpler forms of edge computing handle basic tasks and straightforward processes. For instance, a wearable device that monitors vital signs like pulse and blood pressure can transmit data to an edge server. The majority of the data is processed locally within the edge network, with only selected information sent to the cloud.
Edge computing for complex events
In more sophisticated edge environments, edge infrastructures act as intermediaries between local data and external sources. For example, in a vehicle equipped with edge computing, the system can gather data from GPS, traffic lights, and nearby vehicles to improve the driver’s experience, boost safety, and increase fuel efficiency.
Edge computing servers
Edge servers can perform many functions traditionally handled by data centers. These servers are often used in 5G networks, hosting applications and caching content close to where users are computing. This setup ensures that data does not need to travel long distances to a remote data center for the edge device to operate efficiently.
How does edge computing work?
Edge computing fundamentally revolves around the concept of location. In conventional enterprise computing, data originates from a client endpoint, such as a user’s device, and is transmitted over a wide area network (WAN), like the internet, through a corporate local area network (LAN). This data is then stored and processed by enterprise applications before the results are sent back to the originating client. This method has proven effective for standard business applications over time.
However, the rapid increase in internet-connected devices and the vast amounts of data they generate have outpaced the capacity of traditional data center infrastructures. Gartner forecasts that by 2025, 75% of data generated by enterprises will be created outside centralized data centers. The challenge of transferring such large volumes of data—often in time-sensitive situations—places immense pressure on the global internet, which frequently experiences congestion and disruptions.
Consequently, IT architects are now prioritizing the logical edge of the infrastructure, relocating storage and computing resources closer to where data is generated. The guiding principle is simple: if it’s not feasible to bring data closer to the data center, then bring the data center closer to the data itself. Although edge computing is not a new concept, it draws on long-established ideas of remote computing—such as remote and branch offices—where it has historically been more efficient to position computing resources at the location where they are needed rather than relying on a single central hub.
Edge computing strategically places storage and servers at the site of data generation, often requiring just a small amount of equipment to function effectively on a remote LAN for local data collection and processing. Frequently, this equipment is housed in protective enclosures to safeguard against extreme temperatures, moisture, and other environmental factors. The processing typically involves normalizing and analyzing data streams to extract business intelligence, with only the outcomes of this analysis sent back to the main data center.
The interpretation of business intelligence can vary widely. For instance, in retail settings, video surveillance footage might be analyzed alongside sales data to identify popular product configurations or consumer trends. Other applications include predictive analytics for preemptive maintenance of equipment before failures occur. Additionally, in utility sectors like water treatment or electricity generation, edge computing ensures that equipment operates efficiently while maintaining output quality.
What is Edge Cloud used for?
The adoption of edge cloud across various use cases has steadily risen over the past decade and is projected to grow further in the coming years. According to a 2022 ReportLinker study, the edge computing market is expected to expand at a compound annual growth rate of 21.6% until 2028.
Key industries and applications utilizing edge cloud include:
- IoT applications and deployments: As IoT technology grows and smart devices generate vast amounts of data, edge cloud enables localized data processing, allowing for real-time insights and faster decision-making.
- 5G network expansion: Edge cloud enhances data transfer speeds and reduces latency, making it possible to process information closer to the source. Edge computing and 5G work hand in hand to boost application performance, allowing massive data sets to be processed in real-time. With 5G capable of speeds over 20 times faster than 4G, its success may depend on edge computing to store data locally, improving bandwidth and reducing reliance on centralized cloud systems.
- Real-time and near-real-time services: When milliseconds matter, edge cloud offers higher reliability. Autonomous vehicles depend on edge cloud to process sensor data instantly, ensuring quick decisions that keep passengers and pedestrians safe. Augmented reality and telemedicine also leverage edge cloud for real-time interactions and feedback.
- Smart cities: Edge cloud plays a pivotal role in smart cities, where numerous sensors collect data to enhance urban living. These cities rely on low latency and high connectivity, and depending on a central cloud system can cause delays in data processing. Edge computing mitigates this issue by processing data locally, improving uptime and performance. It also makes 5G and IoT deployments more efficient, boosting the effectiveness of smart city initiatives.
Benefits of Edge Computing
Edge computing has become a highly effective solution for addressing network challenges related to the transfer of large amounts of data generated in today’s digital landscape. Here are some key advantages of edge computing:
- Eliminates Latency
Latency is the delay experienced when transferring data between two points on a network. Factors such as significant physical distances and network congestion can lead to increased delays. By positioning processing closer to the data source, edge computing virtually eliminates latency issues. - Conserves Bandwidth
Bandwidth refers to the amount of data that can be transmitted over a network at any given time. Since all networks have finite bandwidth, the volume of data transferred and the number of devices that can connect are limited. Edge computing addresses this by placing data servers at the locations where data is generated, allowing numerous devices to function efficiently within a smaller bandwidth footprint. - Alleviates Congestion
Despite advancements in internet technology, the sheer volume of data produced daily by billions of devices can lead to significant congestion. Edge computing mitigates this issue by utilizing local storage and servers that can perform essential analytics even during network outages, thus maintaining functionality and reducing strain on the broader internet infrastructure.
Challenges of edge computing
While edge computing offers significant advantages across various applications, it is not without its challenges. In addition to traditional network limitations, several critical factors can influence the adoption of edge computing:
- Limited Capabilities: One of the appealing aspects of cloud computing is the extensive range of resources and services it provides. Although establishing an edge infrastructure can be beneficial, it is essential to clearly define the objectives and scope of the deployment. Even a large-scale edge computing setup serves specific functions at a predetermined capacity, utilizing limited resources and services.
- Connectivity Requirements: Edge computing addresses many typical network issues, but even the most robust edge setups require a baseline level of connectivity. It is crucial to design edge deployments that can handle poor or inconsistent connections and to have contingency plans for scenarios where connectivity is lost. Incorporating autonomy, AI, and strategies for graceful failure is vital for effective edge computing.
- Security Concerns: IoT devices often have vulnerabilities, making it imperative to implement a secure edge computing framework. This includes robust device management practices, such as enforcing policy-driven configurations and ensuring security for both computing and storage resources. Regular software updates and patches are necessary, along with strong encryption for data both at rest and in transit. While major cloud providers offer secure communication services, these protections must be deliberately integrated when creating an edge environment from scratch.
- Data Lifecycle Management: The ongoing challenge of excessive data generation means that much of this information may be superfluous. For instance, in medical monitoring scenarios, only critical data is essential; retaining extensive records of normal readings serves little purpose. Most data involved in real-time analytics is short-lived and not intended for long-term storage. Organizations must determine which data to retain and which to discard after analysis, ensuring that any retained data complies with business and regulatory standards.
Applications of Edge Computing
The possibilities for edge computing are extensive and continually advancing. Here are a few key examples across different sectors:
- Manufacturing: Edge computing is transforming industrial automation by allowing real-time production line monitoring and control, predictive maintenance of machinery, and on-site data analysis to streamline operations and improve efficiency.
- Retail: Retailers use edge computing to deliver personalized shopping experiences, conduct real-time customer behavior analysis, and enhance inventory management through localized data processing.
- Healthcare: Edge computing supports remote patient monitoring, enables real-time medical data analysis for diagnostics, and ensures faster healthcare delivery in areas with limited resources.
- Media and Entertainment: Edge computing empowers content delivery networks (CDNs) to provide high-quality video streaming and interactive experiences with minimal delay, even in widely dispersed locations.
Security Concerns with Edge Computing
Edge computing presents notable security challenges, primarily due to the new attack surfaces created by its topology. In a cloud-based architecture, although response times may be slower, the attack surface is largely confined to the data centers that constitute the cloud. However, with edge computing, each connected edge device becomes an additional potential target for attacks.
For instance, consider an edge device located in a factory. A worker must log in to access it, and once logged in, they transmit data to a local server that then communicates with the device. If the device utilizes a weak password, it becomes vulnerable to exploitation by hackers, disgruntled employees, or other malicious entities who could inject harmful code into the supporting server of the edge network. Moreover, without adequate security measures for each device, unauthorized individuals could easily monitor network activity and intercept data being transferred.
Additionally, edge computing environments are at risk of distributed denial-of-service (DDoS) attacks, especially when connected to the internet. Since many edge networks maintain internet connectivity, a DDoS attack could incapacitate the devices on the edge. Therefore, it is crucial to ensure robust security measures are implemented within your edge network to protect against such threats.
Your journey to edge computing: Things to consider
Edge computing enables businesses to tap into the vast amounts of data generated by connected devices, unlocking new opportunities, improving operational efficiency, and delivering faster, more reliable experiences for customers. By processing data locally, the best edge computing models boost performance and responsiveness. A well-planned edge computing strategy ensures that workloads are updated in line with predefined policies, maintains data privacy, and complies with local data residency regulations.
However, implementing edge computing is not without its challenges. A successful edge model must address security vulnerabilities, manage complex infrastructures, and navigate latency and bandwidth limitations. An effective edge solution should:
- Seamlessly manage workloads across multiple clouds and devices
- Reliably deploy applications to all edge locations
- Remain adaptable and flexible to accommodate changing requirements
- Enhance security and ensure consistent, confident operations
The future of edge computing in your industry
Industries such as banking, mining, and retail are increasingly developing strategies aimed at personalizing customer experiences, accelerating insights and actions, and ensuring uninterrupted operations. This can be accomplished through the implementation of a highly decentralized computing framework known as edge computing. However, each sector has specific use cases that highlight the necessity for edge IT.
In banking, edge computing can be utilized to analyze ATM video feeds in real time to enhance customer safety. In the mining sector, companies can leverage data to streamline operations, boost worker safety, minimize energy usage, and enhance productivity. Retailers can tailor shopping experiences for their customers while quickly communicating targeted promotions. Additionally, businesses that operate kiosks can automate the remote management and distribution of their kiosk applications, ensuring they remain functional even during connectivity issues or poor network conditions.
