Even though edge computing hasn’t gained as much popularity as cloud computing, it’s gradually gaining more traction. The industry predicts that the market revenue will increase from $2.8 billion in 2023 to an impressive $9 billion in 2024. This boom can be largely attributed to the rapid growth of the Internet of Things (IoT), which is predicted to grow explosively in the near future. Thanks to edge computing, the IoT can achieve the necessary level of power it needs to operate effectively.
Edge computing is a technology that allows for data processing to occur at the network’s edge instead of being processed in a remote data centre or cloud. This is especially useful feature when it comes to the processing of data for the Internet of Things (IoT), as it reduces the amount of time needed for data to be processed and ensures that it is processed securely. Both businesses and consumers can take advantage of these benefits. For instance, companies can streamline their data management and quickly respond to customer requests while consumers can enjoy higher levels of security and less latency. In this blog post, we’ll delve deeper into the subject of edge computing and how it can bring advantages to both businesses and consumers.
When Asked, “What is Meant by Edge Computing?”
Edge computing is a technology that allows data processing to occur closer to the end user and their devices, in contrast to remote cloud computing solutions like online backup services. For instance, a small business might have security cameras that previously sent data to the cloud for analysis and storage purposes. However, with the aid of edge computing, the data processing can be done on-site, resulting in quicker analysis and real-time alerts.
According to Network World, edge computing can take many forms, including work laptops used by employees, state-of-the-art smartphones, or even internet-connected microwaves.
Edge computing and cloud computing can work together harmoniously when data is processed at the source instead of being sent to the cloud for further processing. Edge computing helps address issues associated with cloud computing, such as slow processing speeds and high costs. For a more comprehensive overview of edge computing, take a look at the video below.
Advantages and Drawbacks of Edge Computing
Businesses can benefit from cost savings through edge computing, as they do not have to process large amounts of data at each cloud site. This can be advantageous for organisations as it reduces expenditures on cloud services. However, it’s important to evaluate the potential drawbacks of edge computing alongside its benefits.
Edge computing provides a significant advantage in terms of quickly gathering, transferring, analysing, and retrieving data with minimal latency. Additionally, connection stability is a crucial consideration, as a growing number of mission-critical infrastructures adopt edge computing. As a result, this element is integral to the technology.
However, as the number of devices integrating edge-computing systems rises, so does the associated set of issues. This could possibly result in broadcast delays, as well as an increase in bandwidth costs. Moreover, physical and digital security concerns, as well as excessively complex and difficult-to-manage system configurations, are other possible disadvantages.
Internet-Connected Devices at the Edge
While the Internet of Things (IoT) relies on cloud computing for data processing, this approach may not be appropriate in certain circumstances. For instance, in a manufacturing plant, if a device records a temperature reading that is unusually high, the machine must be shut down promptly. As noted by IoT For All, this can be accomplished more quickly if the data does not need to be sent to a centralised cloud server for processing first.
The opportunity to save both time and money is significant, as a portion of the manufacturing line would not need to be shut down for repairs or maintenance, resulting in a faster process.
Edge technology can be employed to great effect in a range of settings, from areas near the ‘edge’ of a network to remote locales. Research sites can range from underground to jungle locations, or even satellite offices of retail and financial companies requiring fast and essential processing capabilities in far-flung regions.
Intelligent Devices and Networked Edge Applications
The above text highlights some of the several potential applications of the Internet of Things and edge computing. Here are a few more examples:
Agriculture.The use of Internet of Things (IoT) sensors can be advantageous in monitoring plant growth and soil quality on farms. Edge computing can be used to determine if the plants are receiving the appropriate amount of water and nutrients.
Autonomous vehicles.To make informed decisions, such as stopping at a pedestrian crossing, self-driving cars and trucks use sensors to gather information on surrounding traffic conditions and receive feedback from them, potentially saving lives.
Residences.In the contemporary ‘Smart Home’ setting, advanced technology and high-speed processors enable devices to detect any unauthorized entry or system malfunctions in the home and quickly notify the homeowner.
Healthcare.Mobile apps and wearables can be used to promptly record and send patient data to doctors.
Electricity.Power companies can install sensors on their equipment to allow maintenance staff to monitor wear and tear. This enables them to detect and fix minor issues before they escalate and require extensive repairs.
The performance of various applications can be significantly improved by edge computing, which reduces the volume of data that must be transmitted to the cloud and/or increases the pace at which it is processed in the local environment. Follow this link to learn more about edge computing.
The protection of this data is crucial, just like any other digital information. The greater the number of endpoints that can access an edge computing environment, the greater the chance of disruption. Cybercriminals frequently target Internet of Things (IoT) devices because they frequently lack adequate security protocols. Furthermore, the physical location may not have the same level of security as a cloud hosting provider, increasing the risk of intrusion.
Ensuring the physical and cyber security of edge assets is a complex and critical issue, as noted by Deloitte. To address these challenges, robust security protocols for edge security systems should be established, data should be encrypted, and robust access-control methods should be used. Additionally, Artificial Intelligence (AI) algorithms can be utilized to monitor edge systems and respond promptly to any security concerns.
In addition, edge computing systems may provide more secure data storage since data travels a shorter distance for processing. Localized environments with larger amounts of data may be less appealing to cybercriminals than cloud-based systems.
The integration of edge computing with the Internet of Things is a game-changing advancement that has the potential to considerably improve the efficiency, productivity, and security of all sectors. We can anticipate an increase in the adoption and complexity of Artificial Intelligence and Machine Learning enabled technologies, such as autonomous vehicles and drones.
Faster communication of malfunction and disruption information is likely to result in improved security for electricity and telecommunications networks. This could also lead to more user-friendly innovations, such as facial recognition technology for boarding aircraft.
It is certain that as technology evolves and advances, existing problems will be resolved and numerous innovative solutions will emerge. This will create a multitude of opportunities for people to explore and utilize.