With the rise of the Internet of Things (IoT), Artificial Intelligence (AI), and software services providers, we're reaching a point where—if companies don't collect data—they're likely falling behind. The more data you collect, the more personalized services you can offer.
There's just one problem: Where's all this data going?
Despite data centers being the pioneering solution for data storage, the fact they contribute to 2% of global greenhouse gas (GHG) emissions doesn't make them a desirable solution anymore. To put it into perspective, data centers have a bigger ecological footprint than the entire aviation industry.
The good news is that edge computing has surged as a more sustainable way of transmitting and processing data. Compared with the centralized data centers, the local architecture offered by edge computing is a viable remedy for the excessive use of energy.
Here's how edge computing can be used to improve sustainability.
Data travel efficiency
When discussing edge computing and sustainability, the focus immediately shifts to energy use. This emphasis on energy use isn't surprising, considering that edge computing can reduce energy consumption by as much as 55%.
IoT devices collect data from industrial processes and then transmit this data to strategically placed edge devices. As edge devices have different levels of intelligence, some of them can:
- Process and filter data locally.
- Perform data analysis.
- Run machine learning algorithms.
- Collaborate with other edge devices.
- Enable semi-autonomous operations.
With this wide range of options, there's no need to transmit raw data to data centers for analysis. As a result, there's less energy consumption in data transmission and processing.
If your edge devices don't include data analysis, you can send only the data that needs processing to data centers—not all of it.
Reduced network congestion edge computing can be used to improve sustainability due to the efficiency of its architecture when it comes to communication systems and network capacity.
The main feature that makes this possible is edge computing’s low latency. Low latency implies a faster transmission of data. As a result, switches, servers, access points and other communication systems operate more efficiently.
The faster data transmission also reduces network congestion. When data spends less time in transit, you can mitigate the risk of data volume exceeding the network capacity. And with less network capacity use, you'll reduce energy use and, consequently, carbon emissions.
Optimized resource allocation edge computing improves your facility's sustainability by leveraging the various resources used in its decentralized architecture. Besides reducing the strain on data centers, edge devices can optimize resource allocation by:
- Handling computing tasks distributed by the edge to leverage the capabilities of multiple devices simultaneously.
- Optimizing capabilities for specific tasks and functions to use applications for different use cases.
- Increasing the reliability of your system. If one device experiences issues, other nearby devices can handle the workload.
Using edge devices as a minimal version of data centers can enhance the responsiveness of your systems.
Management of expenses
Here are some expenses you can save on by using edge computing:
- Cloud services costs reduce as you use fewer resources in centralized cloud environments because you’re processing part of the data at the edge.
- Low-power devices will save more energy, reducing your utility bills.
- Edge computing provides a scalable and cost-effective expansion, as you can add edge resources as needed.
- Eco-conscious applications in edge computing, like smart grids, optimize energy distribution to reduce waste and expenses.
The implementation costs may be an initial challenge, but as your facility grows, you can find a balance between cost-effectiveness and sustainability.
Conscious computing power
Sustainability is often linked to tangible assets that people encounter daily. For example, machines, computers, and heating and cooling systems. However, the underlying applications and technology infrastructure that shape your operations consume significant energy.
Depending on the servers, programming and language frameworks you use, the bandwidth usage of applications increases, along with energy use, which ultimately impacts your sustainability goals.
This is why developers need to consider not just the function of the software they build (i.e., how it will be applied) but also the hardware on which it will run (i.e., where it will be applied). Limited computing power is one of the major challenges in edge computing, but it can be addressed by developing computing power-conscious applications.
This can be achieved by:
- Optimizing algorithms
- Choosing the right application technologies
- Optimizing networking
The bottom line here is that by making thoughtful choices in software design and embracing computing power-conscious practices, you can address limited computing power challenges (in edge computing) and achieve your sustainability goals.
Gene Oon is practice manager at CSE Icon a certified member of the Control System Integrators Association (CSIA). For more information about CSE Icon, visit its profile on the CSIA Industrial Automation Exchange.
