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That the Internet of Things (IoT) is in demand is an understatement. This industry just exploded. According to IDC, the worldwide spending for IoT dropped in 2020 because of the pandemic, but it was still worth more than $740 billion. By 2021, it will increase by double digits and achieve a compound annual growth rate (CAGR) of at least 10% until 2024.
The number of interconnected devices is massive, too. Statista revealed that, by 2021, there will be about 22 billion IoT connections globally for short-range wireless or WLAN devices alone. The popularity of 5G connectivity will only fuel the surge of IoT. It will make devices more accessible, affordable, feasible, and scalable. With these countless devices linked to one another in many different ways, the volume of data being processed is exponential.
The World Economic Forum (WEF) revealed that the digital universe should have gathered at least 44 zettabytes or 44,000,000,000,000,000 megabytes of data by 2020. That’s about 40 times more bytes than the number of stars in the universe.
For users to maximize the information and optimize their applications, they need more than just cloud technology or dozens of worldwide data servers. This is where edge computing comes in handy.
What Is Edge Computing?
Edge computing is a concept, model, or philosophy that aims to bring processing, storing, and analyzing of data closer to the source instead of allowing the information to flow directly to the cloud or distributed to various data centers or servers.
The edge network is often compromised by IoT devices, their applications or platforms, and computers or equipment than run them. At the heart of it is an edge server that works as an intermediary between the cloud and the rest of the terminals or networks.
Also read: SD-WAN is Important for an IoT and AI Future
The Need for Edge Computing
Computing has come a long way since mainframes existed in the 1970s. Back then, the network used “dumb” terminals, which didn’t have any processing capability at all — except to work as output devices. The giant machines, which occupied the entire room, performed much of the work.
In the 1980s and 1990s, computing advanced rapidly that only industrial businesses invested a lot of money on mainframe computers. Homes and offices now shifted to computers. By the 2000s, cloud computing came about. Now, users could store, organize, process, and access data anytime, anywhere. This type of decentralization was important. It made jobs more efficient and users more productive. They can generate and use data extremely fast. Collaboration among teams grew immensely.
However, what most experts failed to consider is the rapid growth of IoT and wireless technology, such as 5G. The volumes of data that need to be processed lead to problems like latency, data loss, and bandwidth issues.
Edge computing helped solve these problems:
1. Because of its location, edge computing can process and analyze data in real-time
Processing at the edge significantly reduces or even eliminates latency, and this is crucial in a variety of commercial and industrial applications:
- Sensors in a pressure-sensitive machine in an industrial plant have to receive the correct readings on time. Otherwise, even a second’s delay can be catastrophic, leading to loss of lives and property.
- Self-driving cars are equipped with dozens of interconnected devices that should communicate and work together harmoniously to avoid problems, including hitting pedestrians or other vehicles.
- Many medical monitoring devices have to feed quick data that could help save lives.
2. Edge computing makes bandwidth use more efficient.
Despite the growth of IoT devices, 5G, and data, the infrastructure gap still exists, according to McKinsey. Spending on public infrastructure fell, while the United States still had a backlog of $2 trillion as of 2017. Granted, these referred to roads, transport, bridges, and railway, but they can also facilitate the growth of other sectors, including telecommunications.
McKinsey further said that broadband access is uneven. The lack of coverage and the high cost of the internet meant that at least 150 million Americans do not have internet at broadband download speed, which is 25 Mbps per second or more.
The solution to this has more to do with changes or upgrading of policies. However, edge computing can help by maximizing and even optimizing the available bandwidth.
Because the network can already process data at the edge, it doesn’t need to send all of its data to the cloud or primary data servers. Take, for example, IoT devices like humidity sensors used in agricultural fields. These nifty devices collect humidity and temperature changes that can help farmers decide what to plant or when to harvest. It can also forecast weather patterns.
Also read: Understanding the Role of Enterprise Data Fabrics
The Primary Challenge of the Edge Network and How to Secure It
Edge computing brings a lot of promise in optimizing, processing, and storing data. But no technology is perfect, especially when it comes to cybersecurity.
According to Kaspersky, one of edge computing’s greatest threats is the presence of many entry points. If a hacker penetrates even just one of the connected platforms or devices, it can go after the rest of the edge network.
It becomes worse if it attacks the local data server, which can serve as an intermediary between the cloud and hundreds of interconnected devices. Adding to the fact that 5G is not the most secured network.
Users can significantly minimize the risks by:
- Investing in tried-and-tested edge computing companies. The likes of IBM, Mutable, ClearBlade, and Cloudflare offer many scalable, secure tools that are constantly upgraded as edge computing evolves.
- Centralizing the operations. While data can be decentralized, the operations of the edge network need to be centralized. This way, regulating, monitoring, and controlling it is easier.
- Limiting access control to users. Now is the best time to implement some of the principles and techniques of zero-trust security. These include using multiple-factor authentication.
- Constantly auditing the system and processes. The problem can arise from any or different points, not only from the systems or a step in the process. All factors involved need regular auditing to know if they need changes or upgrades.
The Future of Edge Computing
Gartner cited that by 2025, the enterprise-generated data by edge computing will reach 75% — a far cry from 10% in 2018. During this period, the global market value of the industry will be over $8 billion with a CAGR of almost 30% (2020 to 2025). But like every other network, edge computing infrastructure deserves effective cybersecurity planning and investment to fully maximize its benefits.
Read next: Approaches to Cybersecurity in 5G-driven Enterprise Networks
