The escalation in the use of smart devices is stretching the capacity of the current infrastructure. We expect the previously unmatched generation of already large amounts of data to snowball with the increase in the use of IoT devices and the introduction of 5G networks.
The intricacy and scale of organization-generated data through connected devices have rapidly surpassed cloud-based platforms' capabilities and led to lag and bandwidth issues. Cloud-based platforms have little choice than finding new ways to handle customers' needs.
May I introduce “edge” computing?
A buzzword similar to ‘IoT’ and ‘cloud’ before it, what precisely is edge computing? How does it process data in a manner that benefits businesses? To understand edge computing, how it works, and its importance, let’s explore this fascinating concept together. Shall we?
What is Edge Computing?
Edge computing is an approach that transfers a part of computation resources and storage away from the central data center and takes it closer to the data source. In other words, edge computing executes more processes in local sites (such as IoT devices or user’s pc) than in the cloud. It indicates that the processing and analysis of raw data happen at the locale of data collection rather than the data going to a centralized data center.
The data center only reviews and interacts with the result from the computing done at the edge, such as predictions, real-time insights, or actionable answers. Conducting computation at the network’s edge reduces the volume of long-range communication required between clients and servers, leading to lower latency.
Edge computing is growing because end users expect more cloud-based applications, while more businesses have multiple sites and are rapidly embracing the remote work culture. These compel cloud-based platforms to discover a method to process the swift inflow of data right at its source, away from the data center, while managing it all at one location.
How does Edge Computing Work?
The premise of edge computing is location.
In traditional enterprise computing, data from the end user moves over a WAN like the internet, through a LAN, and to the enterprise data center. Data analysis occurs at this point, and the endpoint user receives the result of the process. Regrettably, the sheer number of internet-enabled devices and the volume of data generated appears to be growing to a stage that the traditional data centers can no longer surmount.
Conversely, edge computing takes storage and servers to the data via hardware that can work on remote LAN to collect and process data. Even though the physical framework of edge computing can be quite complex, the basic idea is to enable user devices to connect to a close edge module for efficient processing and operations.
The edge devices can be IoT sensors, smartphones, CCTVs, PCs, robot arms in a factory, or high-end remote surgical systems. Components of edge are:
Edge Devices
Devices like smartphones and smartwatches already incorporate edge computing for the collection and processing of data. IoT devices, vehicles, and sensors, for instance, are edge devices assuming they can compute locally and interact with the cloud.
On-premises Infrastructure
A framework for handling local systems and connecting to the system is required and can take the form of routers, containers, bridges, or servers.
Network Edge
Network edge refers to the interfacing point between a device or local network and the internet. Edge computing does not need a distinct ‘edge network’ to function, though implementing it alongside network edge amplifies each other’s effect to deliver higher performance.
Importance and Benefits of Edge Computing
Edge computing has recently grown in importance because it presents a solution to surfacing network issues involving the movement of large quantities of data in the current digital world. It is emerging as a practical architecture that supports distributed computing and deploys computing and storage resources near the data source.
Its usefulness is not limited to solving the issue of volume. Edge commuting also tackles the time spent processing and responding to time-sensitive data. Edge computing also gives widespread or industry-based benefits. Benefits of edge computing include:
Reduction of latency
Reduction in the usage of bandwidth and the associated IT cost
Enhancement of functionality
Increase in efficiency of operations
Quicker general response time and, in particular, time-sensitive case
Improvement in safety at workplaces
Data control
Increased security
Challenges of Edge Computing
To successfully implement edge computing, consider the architecture as it presents several challenges without the necessary expertise. Some challenges of edge computing include:
Lack of Standard and Integrated Architectures
Implementing edge needs the correct infrastructure - devices, network, or cloud platforms. In most instances, several mismatched technological stacks are in use that requires a proper alignment for them to work efficiently.
Connectivity
Although edge computing does not suffer from the regular network limitations, it still requires a minimal connection. An edge deployment structure that tolerates poor and unreliable connections should be a crucial consideration during the design stage.
Security Threats
A pressing challenge of edge computing is its vulnerability to malicious attacks. The inclusion of ‘smart’ devices such as edge servers and IoT devices - infamous for their porous security- only creates new opportunities for further compromise of these devices.
Lifecycle of Data
A constant issue with the current data over surplus is that much of these data are irrelevant. Most of the data utilized for real-time analysis are usually not kept for the long term. Determining what data to retain - per standard policies - and which data to discard after the analytic process is vital to prevent an overload and strain.
Local Hardware
Edge computing needs more localized hardware. For instance, some IoT devices have basic in-built systems that can send raw data to web servers. Analyzing these data rather than sending them will need a complex system with higher processing power. The hardware for building these devices may be expensive as well.
Final Thoughts
Highly Dynamic Ecosystem with Multiple Tech Options Innovation is always welcome. But with a system of extensive technological options, growing innovation in network potentials like 5G and MEC (Multi-access Edge Computing) is leading to a complex ecosystem.
Edge computing is a technology with relevance in almost every area. Edge computing offers us great value in today’s ever-dynamic tech world. The possibilities that will emerge due to this technology are worth observing.
Hopefully, you have gotten a concise understanding of the concept of the distributed network that edge computing presents. In another article, we will look at edge computing versus cloud computing, technologies that combine with edge computing, and security concerns.