real-time application (RTA)

What is a real-time application?

A real-time application, or RTA, is an application that functions within a time frame that the user senses as immediate or current. The latency must be less than a defined value, usually measured in seconds. The use of real-time applications is part of real-time computing.

To determine if a specific application qualifies as Real Time is a function of its worst-case execution time. WCET is the maximum amount of time a defined task or set of tasks requires on a given hardware platform.

Real-time applications are often used to process streaming data. Real-time software should have the ability to sense, analyze and act on streaming data as it comes in without ingesting and storing the data in a back-end database. Real-time applications often rely on event-driven architecture to process streaming data asynchronously.

Types of real-time applications

A defining feature of a real-time application is that it must complete real-time tasks within a particular time constraint. Real-time applications are categorized according to the severity of the consequence of failing to operate within a given time constraint.

Real-time application classifications include the following:

  • Hard real-time apps. A hard real-time system causes an entire system to fail if it misses its deadline or time constraint. For example, an industrial safety system with an unacceptable latency may cause the industrial equipment to physically break.
  • Firm real-time apps. With this type of app, a missed deadline is tolerable but causes significant degradation in quality. For example, in video conferencing, latency may degrade the quality of a call, but the computer system is still usable.
  • Soft real-time apps. With these apps, results degrade after their deadline, whether the deadline is met or not. A video game is an example of a soft real-time system. Video games rely on user input and have limited time to process; degradation is sometimes expected for this reason.

Features and benefits of real-time applications

Key features and benefits of real-time applications include the following:

  • Engagement. Real-time applications offer an immediacy that engages users in a way that traditional applications cannot. This enables businesses to connect with their customers in more meaningful ways.
  • Communication. These applications enable two-way communication that is more efficient than the one-way communication that is typical of nonreal-time applications. This improves collaborations and overall communication within businesses.
  • Response time. Real-time apps can respond faster to user input than traditional ones. This enables real-time programs to respond to user needs faster and more efficiently.
  • Workflow. Real-time applications provide more streamlined workflows because workflow tasks are scheduled and completed in coordination with real-time data. As data comes in, tasks can be structured around it. This approach benefits businesses because it increases efficiency and productivity.
list of real-time analytics benefits
Real-time analytics applications are a type of real-time app that enables businesses to process business intelligence data under a time constraint.

Examples of real-time applications

Real-time applications are used when it is imperative that data is processed without lag time. They are often used to avoid causing a system to stop functioning or endanger a user.

Examples of applications that often function in real time include the following:

Real estate applications might use geolocation to continually modify the listings of available properties as properties are bought and sold in real time.

Similarly, real-time technology in an industrial or medical setting might transmit sensor data and notifications about the surrounding environment to a back-end system for managers to make decisions. For example, sensors measuring the temperature or other critical data on a factory floor help determine if conditions are safe for people and equipment. In a medical setting, monitors provide real-time data about a patient's symptoms.

In an IM application, real-time data is used to record the date and time of message exchanges, as well as other metadata about the messages exchanged.

Software developers use model-driven development (MDD) to obtain real-time performance information using Unified Modeling Language (UML). MDD enables people to work together on a project even if their experience levels vary. UML is a standard notation for the modeling of real-world objects in object-oriented design.

Real-time vs. traditional applications: What's the difference?

Traditional applications, or batch applications as they are sometimes called, do not process data in real time. They often send data to a central cloud repository for processing.

Real-time application process data as it is received. These applications usually process data according to a specific time constraint -- every minute or every hour, for example.

Real-time applications often function in settings where there are automation capabilities. They are generally more predictable than traditional apps because there is less margin for error than with traditional apps. Real-time functions have a smaller window of time to fix errors, and the consequences can be more severe. For the same reason, real-time apps must be more accurate.

Challenges of real-time applications

Challenges associated with real-time applications include the following:

  • Processing. Applications operating in real time must integrate large quantities of data fast and accurately. They must maintain this real-time processing speed and central processing unit power without latency.
  • Responsiveness. These applications must respond fast to changes in the data to provide timely results and ensure smooth interaction with users.
  • Scalability. Real-time data workloads are often volatile, reflecting the nature of the data stream. Applications must be able to expand and contract their capabilities to meet changing demand.
  • Failure tolerance. Real-time apps have to handle failures gracefully so that the overall system continues to operate even when individual components fail. Failures will occur as app updates are made and as performance requirements fluctuate with traffic volume.

Many real-time applications work at the network edge, where they process streaming data in real time, far from a central data repository. Learn the five steps to implementing IoT edge computing.

This was last updated in May 2022

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