Edge computing represents a significant shift from traditional centralized data processing. It brings computation and data storage closer to where they’re needed, enhancing response times and saving bandwidth. By embracing edge computing, Cleveland Clinic and IBM have created an on-site Discovery Accelerator to “improve the quality, cost, and equity of care.” Meanwhile, General Electric recently introduced Edison Digital Healthcare, which will help healthcare providers “to effectively deploy clinical, workflow, analytics and AI tools.”
In addition to its impact on the healthcare industry, edge computing benefits everything from the automotive sector to the cruise industry, heavy machinery, urban development, and much more. The proliferation of the Internet of Things (IoT) devices, the rapid deployment of 5G networks, and the improvement of edge servers, graphics processing units (GPUs), and other hardware have created a technological revolution. Companies that aren’t quick to embrace these technologies risk becoming afterthoughts in a competitive marketplace. It’s critical that companies today know how to overcome edge computing’s most common challenges and understand what is coming next so that they can stay ahead of the competition.
Staying On The Cutting Edge
Edge computing’s origins can be traced back to the 1990s when the first content delivery network (CDN) was developed. That network moved data-collecting nodes from centralized servers and put them closer to end users. From that starting point, edge computing continued to grow, particularly as advancements were made in fifth-generation microprocessors and then as the IoT expanded into the industrial marketplace in approximately 2010 and began to go mobile in 2015.
More recently, the arrival of cloud computing has increased demand for at-the-source data processing, which, in turn, has unleashed true mobile edge computing that gives end users greater data-processing flexibility and scalability while also opening up the ability to collaborate from practically anywhere in the world.
Today, companies as diverse as Siemens, Royal Caribbean, and Caterpillar all use edge computing to improve efficiency and productivity. For instance, Siemens uses edge computing within its MindSphere platform to connect machines and physical infrastructure to the digital world. This connection has boosted operational efficiency and enhanced decision-making. Royal Caribbean says it deploys edge computing on its cruise ships to improve guest experiences and operational efficiency. Caterpillar takes advantage of edge computing to monitor and manage heavy construction and mining machinery. Businesses of all types are reporting three main benefits of using edge computing:
- More Efficient Data Processing. Moving computation and data storage close to the point of data generation reduces latency and bandwidth usage and allows for real-time data processing.
- Cost Savings. Edge computing can produce cost savings in several ways, including predictive maintenance, improved resource allocation and usage, and reduced downtime.
- Increased Innovation. Edge computing improves the scalability and efficiency of IoT deployments, allows for better utilization of 5G networks, and makes it easier to take advantage of new AI applications. These factors open new possibilities for innovation.
The Journey To The Edge Isn’t Always Smooth
There are three main challenges organizations face when attempting to maximize the benefits of edge computing:
- Security/Privacy. Edge devices may be more vulnerable to cyberattacks such as surface or entry-point attacks, physical attacks, or unauthorized attacks. Strong encryption, strict access control, and regular security updates are the best approaches for mitigating these risks.
- Scalability. This becomes an issue when businesses have multiple sites with multiple edge devices. Possible solutions include using edge orchestration frameworks to distribute workload across devices and improve resource utilization and load balancing. Cloud integration and fog computing can also offload intensive edge device processing tasks.
- Data Management. Edge devices can produce so much data that managing it becomes an issue. The situation gets even more complicated when compliance requirements are involved. Companies can utilize data aggregation, data compression, and intelligent data filtering to reduce the amount of data while preserving the most critical information. Edge-to-cloud or edge-to-data center architectures may also help with data transfer and storage.
Another issue that companies tend to run into is effectively tracking the success of their edge computing initiatives. Here are four key performance indicators (KPIs) they can use to stay on top of edge computing performance:
- Latency. This KPI is crucial as it measures the efficiency of local data processing compared to cloud-based approaches and shows its direct impact on user experience and system responsiveness.
- Bandwidth Usage. Use this to track reductions in data transfer volumes through central servers.
- Operational Efficiency. Evaluate process efficiency and cost-saving improvements for greater operational productivity.
- Uptime. Use uptime to track system reliability (failure resistance).
The reward for overcoming the challenges of adopting edge computing is a system that produces faster response times, increased operation efficiency, and an ability to act on data immediately.
On The Edge Of Tomorrow
Data experts at Gartner’s 2023 IT Infrastructure Operations & Cloud Strategies Conference predicted that by 2025, 50 percent of enterprises will create and process data “on the edge,” away from centralized servers and data centers. By investing in edge infrastructure now and developing edge expertise, organizations will be better prepared as edge computing becomes more deeply integrated with advancing artificial intelligence (AI), 5G and 6G, and blockchain technology.
Barcelona, Spain, is an example of what is already possible with edge computing and an indication of what lies ahead. Barcelona is one of Europe’s great ancient cities with a history dating back to 5,000 BCE. Now, thanks to edge computing, this ancient city is transforming into a city of the future. Barcelona’s leaders entered into an agreement with Lenovo to utilize its 5G and other edge computing technologies to better manage and optimize urban services. Resource usage was optimized to save money and enhance sustainability. Traffic congestion was reduced, and city transportation was made more efficient through the real-time management offered by edge computing. Similar benefits, including lowered expenses and improved efficiency, await fast-acting companies that capitalize on advanced edge computing technology to create specialized solutions that meet today’s challenges and open new possibilities for tomorrow.
About the Author:
Kiran Chintagumpula is a lead engineer at College Board with 15 years of experience specializing in data warehousing and cloud computing. The author of “The Future of Data: Trends and Predictions,” Kiran is a recognized expert in integrating AI, ML, and cloud technologies. He holds a master’s degree in computer science from Texas A&M University and has been featured in Tech Times and Digital Journal. Kiran is a gold-level award winner with the 2024 TITAN Business Awards in the business technology solutions/big data solution category. Connect with Kiran on LinkedIn.
Disclaimer: The author is completely responsible for the content of this article. The opinions expressed are their own and do not represent IEEE’s position nor that of the Computer Society nor its Leadership.
