The Need for Real-Time Systems
Growing global connectivity, changing consumer demands for always-available data, and always-on, sensor-enabled enterprise environments are driving the creation, collection, and analysis of exponential amounts of data. By 2025, IDC estimates that there will be 79.41 zettabytes of data created and nearly 30 percent 2 of it will require real-time processing enabled by real-time systems.
The need for real-time processing is especially crucial for businesses in robotics, manufacturing, healthcare, and high-precision industries, such as oil and gas and power, that rely on real-time data for continuous improvement in safety, efficiency, and reliability.
One key factor in ensuring data is processed in real-time for businesses in these types of industries is a system’s ability to prioritize, manage, and execute real-time workloads over non-real-time workloads.
For example, modern automotive manufacturers are highly reliant on robots to work together on a production line to assemble a car. The robots will pass each other parts, drill or weld, or perform safety inspections—all of which require a high level of precision and meticulous timing. In this use case, a real-time system must have the ability to not only process data in a defined, predictable time frame but also ensure that critical tasks, such as safety-related workloads, are completed prior to less critical tasks.
So how can data-driven industries make sure data is processed when and how it should be? Real-time systems.
By 2025, IDC estimates that there will be 79.41 zettabytes of data created and nearly 30 percent 2 of it will require real-time processing enabled by real-time systems.
What Is a Real-Time System?
The term “real-time system” refers to any information processing system with hardware and software components that perform real-time application functions and can respond to events within predictable and specific time constraints. Common examples of real-time systems include air traffic control systems, process control systems, and autonomous driving systems.
Benefits of Real-Time Systems for Applications
Real-time systems offer several benefits:
|More precise timing||Real-time systems are designed to perform tasks that must be executed within precise cycle deadlines (down to microseconds).|
|Higher predictability and reliability||Because real-time systems process data in defined, predictable time frames, execution of tasks or workloads is practically guaranteed, thus improving the reliability of critical systems for business.|
|Prioritization of real-time workloads||When specific real-time workloads must be completed within the set deadline to avoid critical system failure, the ability to prioritize some workloads over others is paramount. Some, but not all, real-time systems have this capability for workload or task prioritization.|
Real-Time System Components
For a real-time system to be capable of real-time computing, it must satisfy two requirements:
- Timeliness: The ability to produce the expected result by a specific deadline.
- Time synchronization: The capability of agents to coordinate independent clocks and operate together in unison.
When evaluating real-time systems, companies can measure the value of any system in how predictable it is in completing events or tasks. Predictability can be further evaluated by examining the system’s:
- Latency: Measurement of time between two events
- Compute jitter: Latency variation between iterations
Another important characteristic in real-time systems is their ability to perform concurrent execution of real-time and non-real-time workloads in order to avoid critical system failure.
Finally, it’s important to understand how real-time systems are typically categorized. They are designated as either a soft real-time system or a hard real-time system based on timing constraints.
Soft Real-Time Systems vs. Hard Real-Time Systems
The concept of real-time can be applied to a variety of use cases. The majority of those use cases, such as web browsing and gaming, fall within the soft real-time classification.
However, there are certain industries, such as robotics, automotive, utilities, and healthcare, where use cases have higher requirements for synchronization, time lines, and worst-case execution time guarantee. Those examples fall within the hard real-time classification.
Applications of Real-Time Systems
Process Control Systems
Process control systems are used in industrial applications where production is continuous and interruptions cannot happen. These systems help businesses maintain quality and improve performance by testing processes, collecting relevant data, and returning that data for monitoring and possible troubleshooting. Companies in the oil and gas sector are key users of process control systems and often realize numerous benefits, from increased efficiency to safer operation of facilities to less downtime and fewer losses.
Machine vision is used to help machines rapidly interpret data so they can see their surroundings and make decisions quickly based on that visual input. These machines are often key to ensuring production keeps flowing or critical processes continue. Real-time systems help ensure machines such as these are able to process that data in near real-time.
Robotics technologies are used for a variety of complex applications, many of which require precise timing constraints to ensure a safe workload execution as well as the ability to continuously function. Real-time systems are a valuable part of robot operating systems because of the need for real-time computing and processing.
Future-focused manufacturers rely on insights gained from real-time applications to avoid product quality issues, improve efficiency and performance, and, ultimately, gain a competitive edge. Embedded real-time systems can help manufacturers maximize productivity, improve product quality and consistency, and enhance safety on the factory floor.
Healthcare and Patient Monitoring
How quickly data is processed in healthcare can often mean the difference between life and death. Real-time systems are key to ensuring data from patient monitoring systems, such as heart rate monitors, is available to clinicians when and where they need it to keep patients safe and healthy.
Intel’s Impact on Real-Time Systems
To support new solutions that require a high degree of real-time requirements, Intel has introduced real-time performance technology, Intel® Time Coordinated Computing (Intel® TCC), to its product line and continues to expand its support for Time-Sensitive Networking (TSN).
Intel® Time Coordinated Computing (Intel® TCC) is a new set of features that augment the compute performance of Intel® processors to address the stringent time constraints required for hard real-time applications. Intel® TCC makes the processors suitable for latency-sensitive applications while staying generally power efficient and leaving sufficient performance for other concurrent tasks. Intel® TCC helps ensure that every element in a workload performs in a reliable and predictable manner within the required time window.
Time-Sensitive Networking (TSN) refers to a collection of IEEE standards, specifications, and capabilities based on standard Ethernet networks to support time-sensitive applications and precision time synchronization, timeliness for data delivery, and traffic scheduling. TSN can be used to optimize performance between systems by leveraging an open, standards-based design. Intel now supports more TSN standards than ever before, including:
- IEEE 802.1AS: Generalized Precision Time Protocol
- IEEE 802.1Qbv: Time-Aware Shaper
- IEEE 802.1Qav: Credit-Based Shaper
- IEEE 802.1Qbu: Frame Preemption
Intel® Solutions Transform Real-Time Systems
The growing need to meet hard-time requirements is not slowing down anytime soon. Intel has the technology and expertise to help companies prepare for this upcoming deluge of data processing with the new Intel® TCC and expanded support of TSN. These solutions take a new combined approach to help address challenges often faced in emerging high-performance real-time solutions.