Edge Computing: What is it, and why is Edge Computing important?
Edge computing is more than a method. It is also a philosophy of networking. The goal is to bring computing devices closer together. The goal is to minimize latency in bandwidth usage.
In layman’s language, edge computing means that fewer processes are executed in the cloud and transferred to a local environment, such as a user’s computer, IoT device, or edge server.
This process reduces long-distance communication between the server and client. A network edge is a location where a device or local network contains it and can communicate with the internet.
The term edge is a popular buzzword and can be interpreted in various ways. Below, we explore what is edge computing and why it is important.
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What is Edge Computing?
Simply described, edge computing relocates a portion of storage and processing resources away from the central data center and closer to the data source.
Instead of transmitting raw data to a central data center for processing and analysis, this work is performed where the data is created, be it a retail store, a factory floor, a large utility, or a smart city.
Only the results of the computing work performed at the edge, such as real-time business insights, equipment maintenance predictions, and other actionable solutions, are sent back to the primary data center for human review and other interactions.
Understanding Edge Computing Architecture
Edge computing is entirely location-dependent. Conventional enterprise computing generates data at a client endpoint, such as a user’s personal computer. This data is transferred over a WAN, from the internet to the corporate LAN and is stored and processed by an enterprise application.
Related: What is a Wide Area Network? Understanding WANs
The results of this effort are then returned to the client endpoint. This remains a tried-and-true client-server computing strategy for most common corporate applications.
However, the number of devices linked to the internet and the volume of data created by these devices and used by organizations are expanding at a rate that traditional data center infrastructures cannot support.
The thought of transferring so much data is frequently time- or disruption-sensitive situations places a tremendous burden on the global internet, which is often susceptible to congestion and outages.
Therefore, IT architects have turned their attention from the central data center to the logical edge of the infrastructure, shifting storage and processing resources from the data center to the location where data is generated. If it is impossible to move the data closer to the data center, then move the data center closer to the data.
The concept of edge computing has its roots in decades-old concepts of remote computing. In this model, it was more dependable and efficient to locate computing resources at the desired location, such as remote offices and branch offices, rather than relying on a single central site.
Edge Computing and Internet of Things (IoT)
Although most Internet of Things devices now rely on cloud computing, many manufacturers and application developers are beginning to see the benefits of computing on the device itself. Edge computing and the IoT meet at the capacity to perform advanced processing and computing on the device itself.
Edge computing also tackles issues such as network congestion and latency that the Internet of Things currently faces.
RELATED: Understanding Internet of Things (IoT): What is IoT?
This new generation of cellular technology would be unable to deliver on its promises without edge computing’s ultra-low latency and high levels of connectivity. As the Internet of Things (IoT) and IoT devices continue to spread, edge computing is rapidly becoming an industry standard.
The requirement to bring data processing closer to the end-user to reduce network latency and enhance user experience has become a pillar of the industrial IoT. Edge computing allows for the expansion of IoT applications, particularly those dependent on AI and machine learning.
The growth and extension of the Internet of Things are directly proportional to the predicted proliferation of edge data centers.
What are the Components of Edge Computing?
Locations are emphasized heavily in edge computing. Accessing in-depth data from numerous locations empowers organizations to meet the wants of future customers. It enables organizations to evaluate crucial data in real-time without sending it thousands of kilometers away.
In addition, it is a key step forward for businesses who wish to develop high-performance applications with low latency.
Edge computing operates in tandem with three fundamental components:
1. Internet of things (IoT)
Internet of Things (IoT) devices have surged in recent years. In parallel, the quantity of bandwidth that they utilize has also increased. The enormous volume of data produced by these devices affects a business’ private cloud or data center, making it challenging to manage and store all data.
Numerous organizations are ecstatic about IoT’s limitless potential applications. IoT has been a driving force for edge computing multiple respects. Edge computing sits predominantly in an IoT setting, where data is stored at a remote place far from the central data server.
RELATED: How the Internet of Things (IoT) is creating opportunities for small business?
When it comes to programming IoT devices efficiently, the requirement for speed is real. IoT and edge computing are, therefore, a perfect combination.
Businesses that implement IoT with edge computing capabilities close to endpoints get the ability to respond to fresh data within seconds. Businesses not adopting edge networks will miss significant cost savings, improved efficiency, and enhanced connectivity.
2. Communication networks
The advent of 5G has paved the way for numerous innovative and progressive advances. However, the emergence of new wireless devices, such as IoT, impedes the network’s capacity, making it challenging to manage the massive influx of virtual data.
5G communication networks and edge computing are improving our lives. Today, the convergence of edge computing and 5G networks drives modern enterprises’ digital transformation.
RELATED: What opportunities does 5G present for small businesses?
By embracing edge computing’s massively decentralized computer architecture, businesses may harness the power of comprehensive data analysis. But how do these two formidable forces function? The edge computing framework maintains data close to the source, while the lightning-fast speed of 5G technology transports data to its destination as rapidly as feasible.
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Edge computing can maximize 5G’s capabilities. It enables data localization, ultra-low latency, and security and privacy concerns to be addressed, decreasing the network strain. When paired with 5G, edge provides the greatest user experience for rich media, enabling virtual reality/augmented reality (VR/AR), gamification, drone control, linked cars, and real-time collaboration.
3. Cloud computing
Centralized cloud computing has been a norm in the IT sector for a very long time and remains the undisputed leader. However, it is simple to confuse cloud computing and edge computing. Cloud computing is a massive utility for storing and processing computer resources in a centralized data center.
RELATED: Understanding Cloud cloud computing
In contrast, edge computing is a distributed paradigm that will likely be utilized by applications and devices that demand prompt replies, real-time data processing, and critical insights.
Edge computing is fast-becoming the next step in the evolution of cloud computing, despite being touted as the next big thing. Does this imply that edge will eventually replace cloud? That is highly unlikely to occur.
Edge is more comparable to a cloud extension. Edge computing solves the limits of centralized computing (such as latency, bandwidth, data privacy, and autonomy) by shifting processing closer to the source of data generation, things, and people.
They can collaborate to develop productive solutions depending on data collection, organizational objectives, and usage.
Edge can be a valuable complement to the cloud, and together they can deliver real-time knowledge regarding numerous performance efforts. Although IoT and web hosting benefit from edge for faster performance, they still need a dependable cloud backend for centralized storage.
3 Reasons Why Edge Computing is important
The concept of business intelligence is highly variable. Examples include retail settings where video surveillance of the showroom floor could be paired with sales data to determine the most desirable product layout or consumer demand.
Other examples include predictive analytics that can direct equipment maintenance and repair before real problems or breakdowns occur. These are frequently aligned with utilities, such as water treatment or electricity generating, to assure equipment functionality and output quality.
- Bandwidth: Some IoT applications can generate enormous amounts of data, similar to the costs associated with transporting it all to the cloud, making local processing more practical and advantageous.
It is also a limiting constraint for any application that demands streaming massive amounts of content, such as the oil and gas exploration applications that may use high-definition video.
- Latency: Certain applications demand exceptionally low latency. Any safety-related application, such as driverless automobiles, healthcare, or industrial plant floor applications, necessitates near-instantaneous response time.
Due to the inherent delay of the round-trip to a centralized server, cloud services are not optimal in such situations.
- Regulatory requirements: In highly regulated industries and locations (such as Europe with the General Data Protection Regulation, GDPR), the handling of personal information, including where it is stored and communicated, is strictly governed, necessitating localized data centers.
Benefits of Edge Computing
Edge computing places storage and servers close to the data, typically requiring no more than a partial rack of equipment to function on the remote LAN to gather and analyze the data locally. In many instances, computing equipment is placed in shielded or hardened enclosures to protect it from temperature, humidity, and other environmental variables.
Typically, processing entails normalizing and analyzing the data stream in search of business intelligence, and only the analysis findings are returned to the primary data center.
1. Enhanced Velocity
In terms of performance, edge computing can deliver significantly faster response times. Because putting essential processing processes closer to end users reduces latency dramatically. Typically, data is collected at the edge of conventional networking and sent back to centralized servers for processing.
These servers send back instructions to edge devices if a response is required. However, edge computing frameworks perform this processing much closer to the data source.
Due to reduced time spent waiting for data packets to travel the distance from the edge to the core and back, devices can reply significantly more quickly.
2. Bandwidth Relief
By storing more data at the network’s edge, the total traffic volume to central servers is decreased. This frees up much-needed bandwidth across the entire system by reducing problematic bottlenecks and superfluous processing activities.
For an increasing number of enterprises managing data-intensive digital media services, the capacity to cache high-demand material on regional edge servers significantly reduces network load. Since their local network is not competing with other regions for limited bandwidth resources, end users enjoy better performance.
3. Improved Data Management
The data collected at the network’s edge is highly useful since it offers vital user behavior information. Unfortunately, a significant portion of this information is also meaningless “noise”; hence, advanced analytics techniques are required to sift this unstructured data and find substantial trends.
Typically, networks transfer all information gathered at the periphery to centralized servers equipped to filter through vast stores of big data. However, a well-designed edge computing network can use local devices and edge data center capabilities to manage this data more effectively.
RELATED: Big Data Basics: Understanding Big Data
Instead of communicating all of this data back to the network’s core, edge networks can process some of it locally and transmit only specific categories of data. This frees up critical network processing resources and vastly increases the quality of data insights generated by big data applications.
4. Improved Security
Although edge computing increases the total network surface area and the number of endpoints, this does not necessarily imply that there are more exploitable vulnerabilities. Despite the need to adequately secure IoT edge devices, the scattered structure of edge networks makes them considerably harder to hack.
If a security breach happens in one region, the vulnerable components of the network can be isolated without shutting down the entire system. Additionally, organizations can use the added processing capacity of the edge network to enhance their threat analysis data, enabling them to identify and respond to possible cybersecurity attacks much more swiftly.
RELATED: Big Data Privacy and Security Challenges: What you need to know
5. Increased Dependability
Distributing processing duties around the network, edge computing architecture is typically more resilient than centralized systems. In a conventional network, all services and applications are rendered inoperable if the primary servers are unavailable, as they handle all instructions and processing.
In contrast, edge computing frameworks are significantly less consolidated. Due to a combination of local processing and regional edge data centers, many vital services can continue to be provided at the edge even if the core servers are taken offline temporarily.
This is of the utmost importance for healthcare and autonomous vehicle use cases when even a few seconds of downtime could cost lives.
Examples of Edge Computing
We inhabit a world brimming with intelligent devices and rapidly developing technology. As such, many people are unaware of the existence of edge computing in our daily lives. Edge enables anything from remote office work to surgery, mobile phones to smart cities, autonomous vehicles to voice-controlled devices.
Computing at the edge is essential because it enables organizations to operate with optimal operational efficiency, increased safety, and enhanced enterprise and industrial performance. Edge computing applies to all industry verticals, including the financial, healthcare, retail, and mining industries.
There may be dozens of instances and use cases for edge computing, but we will focus on essential ones here.
Edge computing supports continuous monitoring in industrial units by providing real-time analytics and machine learning. This aids in gaining insights into product quality through additional sensors in manufacturing facilities.
The ultimate objectives include accelerating factory facilities and manufacturing operations decision-making, capitalizing on underused data, and eliminating safety hazards on the production floor.
2. Commodities & Utilities
Infrastructure such as oil rigs, mines, and gas units must be continuously monitored to prevent hazardous incidents. Edge computing guarantees that proper maintenance procedures be followed even in faraway places.
It enables real-time analytics processing and optimal data distribution, decreasing reliance on the cloud. Edge-collected data may optimize operations, boost productivity, ensure worker safety, and reduce energy consumption.
3. Financial services
Edge computing could transform the banking and finance industry. It is well-known that banks store vast quantities of personal information, which necessitates increased bandwidth capacity and storage space for security.
Bringing data processing closer to banks could result in more efficient and safe banking for clients. In addition, banks can use edge computing to examine ATM video feeds in real-time and enhance ATM security.
Computing at the edge of the healthcare system offers a great deal of potential and prospects for the healthcare industry, including medical monitoring equipment. It can facilitate the transformation of inpatient-outpatient record services.
Edge computing, combined with automation and machine learning, could immediately identify patients with problematic symptoms and take immediate action to assist them.
In addition to sales data, surveillance footage, inventory IDs, and other business-related information, retail establishments generate vast data. Edge computing can appropriately steer this data by personalizing customers’ purchasing experiences, anticipating sales and customer preferences, outlining specifics for new campaigns and specialized offers, and optimizing vendor purchases.
6. Autonomous vehicles
The emerging era of autonomous vehicles requires a prompt response. Receiving information on speed, traffic conditions, traffic lights, pedestrians, vehicle speculations, road conditions, and other vehicles in real-time while in motion is required to take autonomous vehicles to the limit.
Edge computing drives the development of autonomous vehicles because it guarantees minimal latency. Delays in this information could mean the difference between jeopardizing and saving a life.
High-speed functionality is a crucial requirement for online and cloud gaming (a sort of gaming that broadcasts the live feed of the game straight to devices). Frequently, these suffer from significant lag and latency issues, significantly delaying the gamers’ reactions.
Edge computing can enhance gaming by creating edge servers closer to the players, thereby reducing latency and delivering a more immersive and rich gaming experience.
8. Smart cities
Massive volumes of data are crucial to the operation of smart cities. All of the features of a smart city, such as autonomous vehicles, smart street lighting, smart manufacturing, smart power grids, and public transportation that can be monitored for increased efficiency, can be powered by edge computing.
9. Video streaming
Content consumption methods have evolved rapidly, from cable to streaming. While HD video streaming needs a significant amount of bandwidth, consumers want a seamless streaming experience.
Content delivery can be considerably enhanced by relocating the load close to the edge and caching content there.
Edge computing is a viable option for enterprises of all sizes attempting to keep up with the growing demand for data processing and storage. Small and medium-sized businesses (SMBs) are increasingly relying on edge computing and Internet of Things (IoT) technology due to the reliability of their interconnections and to increase their productivity.
Building an edge computing infrastructure can be difficult and expensive for SMBs. Using a managed service provider for your edge computing can minimize infrastructure costs and necessary supply storage and improve data security.