Realtime applications provide an action or an answer to an external event in a timely and predictable manner. While many realtime applications require high-speed compute power, realtime applications cover a wide range of tasks with differing time dependencies. Timeliness has a different definition in each realtime application. What may be fast in one application may be slow or late in another. For example, an experimenter in high-energy physics needs to collect data in microseconds while a meteorologist monitoring the environment might need to collect data in intervals of several minutes. However, the success of both applications depends on well-defined time requirements.
The concept of predictability has many connotations, but for realtime applications it generally means that a task or set of tasks can always be completed within a predetermined amount of time. Depending on the situation, an unpredictable realtime application can result in loss of data, loss of deadlines, or loss of plant production. Examples of realtime applications include process control, factory automation robotics, vehicle simulation, scientific data acquisition, image processing, built-in test equipment, music or voice synthesis, and analysis of high-energy physics.
To have control over the predictability of an application, the programmer must understand which time bounds are significant. For example, an understanding of the average time it takes for a context switch does not guarantee task completion within a predictable timeframe. Realtime programmers must know the worst-case time requirements so that they can design an application that will always meet worst-case deadlines.
Realtime systems also use techniques to reduce the hazards associated with a worst-case scenario. In some situations, a worst-case realtime deadline may be significantly faster than the non-realtime, average time.
Realtime applications can be classified as either hard or soft realtime. Hard realtime applications require a response to events within a predetermined amount of time for the application to function properly. If a hard realtime application fails to meet specified deadlines, the application fails. While many hard realtime applications require high-speed responses, the granularity of the timing is not the central issue in a hard realtime application. An example of a hard realtime application is a missile guidance control system where a late response to a needed correction leads to disaster.
Soft realtime applications do not fail if a deadline is missed. Some soft realtime applications can process large amounts of data or require a very fast response time, but the key issue is whether or not meeting timing constraints is a condition for success. An example of a soft realtime application is an airline reservation system where an occasional delay is tolerable.
Many realtime applications require high I/O throughput and fast response time to asynchronous external events. The ability to process and store large amounts of data is a key metric for data collection applications. Realtime applications that require high I/O throughput rely on continuous processing of large amounts of data. The primary requirement of such an application is the acquisition of a number of data points equally spaced in time.
High data throughput requirements are typically found in signal-processing applications such as:
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Sonar and radar analysis
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Telemetry
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Vibration analysis
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Speech analysis
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Music synthesis
Likewise, a continuous stream of data points must be acquired for many of the qualitative and quantitative methods used in the following types of applications:
For some applications, the throughput requirements on any single channel are modest. However, an application may need to handle multiple data channels simultaneously, resulting in a high aggregate throughput. Realtime applications, such as medical diagnosis systems, need a response time of about one second while simultaneously handling data from, perhaps, ten external sources.
High I/O throughput may be important for some realtime control systems, but another key metric is the speed at which the application responds to asynchronous external events and its ability to schedule and provide communication among multiple tasks. Realtime applications must capture input parameters, perform decision-making operations, and compute updated output parameters within a given timeframe.
Some realtime applications, such as flight simulation programs, require a response time of microseconds while simultaneously handling data from a large number of external sources. The application might acquire several hundred input parameters from the cockpit controls, compute updated position, orientation, and speed parameters, and then send several hundred output parameters to the cockpit console and a visual display subsystem.
Realtime applications are usually characterized by a blend of requirements. Some portions of the application may consist of hard, critical tasks, all of which must meet their deadlines. Other parts of the application may require heavy data throughput. Many parts of a realtime application can easily run at a lower priority and require no special realtime functionality. The key to a successful realtime application is the developer's ability to accurately define application requirements at every point in the program. Resource allocation and realtime priorities are used only when necessary so that the application is not overdesigned.
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