What is edge computing? It’s an IT architecture in which data is stored and processed close to the source. This reduces the number of processes that slow down data transfer and enables almost real-time processing. It has become increasingly significant and popular with the distribution of IoT devices that collect and store vast amounts of information. If you wish to learn more about edge computing, see some examples, and discover how it can be used to improve sustainability, read this article – we will discuss all these matters here.
What Is Edge Computing? Definition.
Firstly we shall take a look at the definitions of edge computing provided by scientists and tech companies:
“Edge computing refers to leveraging computation-enabled devices located at the edge of network. Devices can be conventional computer servers or sensor/actuator IoT devices augmented with computations such as Single Board Computers (SBCs), deemed as edge nodes, or a hybrid of both. Although in its infancy, as one of its ultimate goals, edge computing is intended to enable computing on resource-limited devices and to reduce latency and bandwidth for IoT applications as the biggest stakeholders.” (Fraga-Lamas et al., 2016 & Mahmud et al., 2020 via Aslanpour et al., 2021).
“Edge computing is a distributed computing framework that allows IoT devices to quickly process and act on data at the edge of the network.” (Microsoft, n.d.)
As we can see, edge computing is all about IoT devices and making data processing quicker by reducing latencies and storing the most important data close to its source. Therefore, it is also crucial for embedded systems.
What Is Edge Computing in Practice? The Advantages and Challenges.
Edge computing offers a lot of benefits, examples of which we present below.
- Operations efficiency – Quicker, optimized, and efficient operations are the result of introducing edge computing – without the need to exchange information with a centralized database, the processes are much faster, especially if the central cloud or data center is located far away from the source(s).
- Faster response times – Additionally, apart from improving the overall efficiency, edge computing offers faster, near-real-time response times. This is essential for sensors, cameras, or other smart devices that need to provide information immediately.
- Security – Edge-computing-based devices are also much more secure. It is so because data is stored offline, so it eliminates the vulnerabilities connected to transmitting it to the data center and storing it in one place.
- Legal compliance – The EU has different regulations regarding data than the US or China. But, with a centralized data center, you need to adhere to all of them. With edge computing, this no longer has to be a problem – the data is stored in the device locally, so you need to be compliant only with the regulations in the particular country.
- Lower expenses – With no need for a data center, or the need for a smaller one, edge computing helps businesses cut down their IT costs.
Despite these advantages, edge computing faces some challenges. This is exactly why it’s still not chosen as the best option in every case. The reason behind this is simple: it’s a relatively new architecture. Therefore, we may expect many of these challenges to be overcome in the future. But, for now, edge computing services need to battle:
- Lack of complexity – As most edge computing base stations are based on DSPs, it’s difficult to handle complex tasks within this architecture. Some companies are actively putting efforts to change that, take Nokia or Cisco, for example, but right now, it is challenging and expensive.
- Finding nodes – Discovering the nodes within the edge of a network is still difficult, and doing it manually is simply impossible (or ineffective) due to the number of devices that operate within a network.
- Finding the golden means between workloads and efficiency – Another problem for decentralized edge computing networks is to leverage the number of workloads imposed on the edge nodes to such a level that they would achieve high output while remaining reliable. Ensuring that overloading doesn’t occur requires gathering information on the way edge nodes are used and constant monitoring.
Edge Computing Examples
We know the theory, now let’s leave it behind. Instead, we can look at the examples of edge computing in real life. How is it used? Check it out below.
- Autonomous vehicles – Many embedded systems in automobiles run on edge computing. This is because the information about the road conditions needs to be processed as quickly as possible.
- Patient monitoring – Glucose monitors, or, in fact, any other type of health monitoring devices, also use edge computing. If it were done otherwise, sensitive data would need to be transferred to a central cloud storage – this would be too much of a security risk.
- Cloud gaming – This fairly new concept requires the lowest possible latency to improve the experience. Therefore, cloud gaming companies employ edge-computing servers.
How Can Edge Computing Be Used to Improve Sustainability?
Finally, let’s look at how edge computing can be used to improve sustainability. Why exactly do we want to focus on that so closely? Because it’s one of the most critical challenges that humanity faces right now and this is an example of how technology, even the digital one, can make a positive impact.
First of all, edge computing is the perfect solution for sensors and monitors, including environmental ones. Air quality, energy consumption, or resource efficiency – all of these can be monitored with the use of edge computing and adjusted on-the-go to achieve the most environmentally friendly results.
Secondly, edge computing reduces the demand for data centers, which consume a lot of electrical energy. So, simply introducing this technology already has a positive impact on our planet.
Edge computing offers a cutting-edge (pun intended) solution for businesses that wish to reduce latency to a minimum. By storing data near its source rather than in a centralized base, it improves the efficiency and security of many devices. This is why we can find examples of edge computing in hospitals or autonomous cars. It might face challenges right now, but with further development, it shall become a dominant solution.
You may also read: Edge Computing vs. Cloud Computing.
Aslanpour, M. S., Toosi, A., Cicconetti, C., Javadi, B., Sbarski, P., Taibi, D., Assuncao, M., Gill, S. S., Gaire, R., & Dustdar, S. (2021). Serverless Edge Computing: Vision and Challenges. DOI: 10.1145/3437378.3444367.
Microsoft. (n.d.). What is Edge Computing? Azure Cloud Computing Dictionary. Retrieved from https://azure.microsoft.com/en-us/resources/cloud-computing-dictionary/what-is-edge-computing