Measuring real-time (2024)

By John Piekos, Contributor, InfoWorld |

I explore the different types of real-time applications and how real-time is measured based on the application need

Measuring real-time (1)

The term “real-time” is thrown around a lot these days, but it’s a buzzword that is often surrounded by ambiguity. Every day, it seems a new product is announcing its real-time capability. But how is real-time measured? It certainly isn’t measured in days (or even hours)—so is it measured in:

  • Nanoseconds?
  • Microseconds?
  • Milliseconds?
  • Seconds?
  • Minutes?
  • All of the above?

Everyone, from developers to software corporate marketing departments to even consumers, seems to have a slightly different answer. So let’s explore the question “What does ‘real-time’ really mean?”

Let’s begin with the dictionary definition:

Real-time—“of or relating to applications in which the computer must respond as rapidly as required by the user or necessitated by the process being controlled.”

While this definition continues with the subjective theme, it does confirm that the correct answer to how to measure real-time is “All of the above.” The meaning of the term real-time varies based on application need—the amount of time a computer (the application) takes to respond and the acceptable latency is as fast as required by the problem domain.

Rather than look at applications and determine if they are real-time or not, let’s examine various time units and understand the types of real-time applications that require those response rates:

Nanoseconds:A nanosecond (ns) is one billionth of a second. Admiral Grace Hopper famously explained a nanosecond using an 11.8-inch wire, as that is the maximum distance electricity can travel in one nanosecond. This quick video of Hopper is worth watching if you haven’t yet seen it.

With this in mind, it is easy to see why nanoseconds are the unit used to measure the speed of hardware, such as the time it takes to access computer memory. Worrying about nanosecond latency is at the bleeding edge of real-time computing and is primarily driven by innovation with hardware and networking technology.

Microseconds:A microsecond (µs) is one millionth of a second. Real-time applications that worry about microsecond latency are high-frequency trading (HFT) applications. Financial trading firms spend large sums of money investing in the latest networking and computer hardware to eliminate microseconds of latency within their trading platforms. A trading decision has to be made in as few microseconds as possible in order to execute ahead of competition and thus maximize profit.

Milliseconds:A millisecond (ms) is one one-thousandth of a second. To put this in context, the speed of a human eye blink is 100 to 400 milliseconds, or between a 10th and half of a second. Network performance is often measured in milliseconds. Real-time applications that worry about latency in milliseconds include telecom applications, digital ad networks, and self-driving cars. The decision on what optimal ad to display or whether there is enough balance to let a cellphone call proceed must be made on the order of 100 milliseconds.

Seconds:We’re starting slow down here. We’re still in the realm of real-time, but we are now venturing into near real-time. Sub-minute processing time is often more than good enough for applications that process log files, computing analytics on event streams, as well as alerting applications. These real-time applications drive actions and decisions that are made in human-reaction time rather than machine-time. Reducing the response time by one tenth of a second (100ms), which may be costly to implement, has no change in value for the application.

Minutes: Waiting minutes may seem like an eternity to a high-frequency trading application. However, consider package shipment and delivery alerts or ecommerce stock availability notifications. Those applications certainly feel real-time to me—the fact that I receive a “delivery notification” text message within 10 minutes of a delivery made to my home is very satisfying.

Finally, though I discounted it up front, let’s briefly consider hours and days. While this time range is generally not regarded as true real-time, if you’ve been getting finance or sales reports on a monthly, weekly, or daily basis, and now you can get up-to-date reports every hour, that may be as real-time as you need. The modernization of these applications is often termed as upgrading from “batch” to “real-time.”

The old proverb is correct: Time is money. Throughout history, the ability to make real-time decisions has meant the difference between life and death, between profit and loss. The value of time has never been higher and therefore speed has never been more critical to business applications of all kinds.

Luckily, we live in an age where fast computing is very affordable and making decisions in real-time is economically achievable for most applications. The first step is determining the appropriate definition of real-time that aligns with the needs of your business applications.

John Piekos heads up VoltDB’s engineering operations, including product development, QA, technical support, documentation, security and field engineering. He has more than 25 years of experience leading teams and building software, delivering both enterprise and Internet-based solutions.

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Copyright © 2017 IDG Communications, Inc.

As someone deeply immersed in the world of real-time computing, I can attest to the pervasive ambiguity surrounding the term "real-time" in today's technological landscape. My expertise is not merely theoretical but grounded in practical experience, having navigated the intricacies of real-time applications and their diverse measurement metrics.

The article by John Piekos delves into the multifaceted nature of real-time computing, seeking to demystify the varying interpretations of this term. Piekos rightfully asserts that the measurement of real-time is not a one-size-fits-all endeavor but depends on the specific requirements of the application at hand.

To substantiate this, let's dissect the different units of time discussed in the article:

  1. Nanoseconds (ns): At the forefront of real-time computing, nanoseconds are crucial for tasks where speed is paramount. Admiral Grace Hopper's analogy of an 11.8-inch wire representing the maximum distance electricity can travel in one nanosecond underscores the microscopic nature of this unit. It is predominantly relevant in measuring the speed of hardware, particularly in the context of accessing computer memory.

  2. Microseconds (µs): A step above nanoseconds, microseconds are one millionth of a second. High-frequency trading (HFT) applications exemplify the need for microsecond latency. In this realm, financial trading firms invest substantially in cutting-edge networking and computer hardware to gain a competitive edge, as trading decisions must be executed within microseconds to maximize profitability.

  3. Milliseconds (ms): A millisecond is one one-thousandth of a second. This unit becomes pertinent for real-time applications like telecom networks, digital ad platforms, and self-driving cars. Decisions in the order of 100 milliseconds are critical in these scenarios, whether it's determining the optimal ad to display or ensuring seamless cellphone call progression.

  4. Seconds: Venturing into near real-time, seconds are still within the realm of quick response. Applications processing log files, computing analytics on event streams, and alerting systems find sub-minute processing time sufficient for human-reaction time decisions.

  5. Minutes: Although minutes may seem extensive for certain applications, they are considered real-time in specific contexts. Package shipment and delivery alerts or ecommerce stock availability notifications, where receiving updates within 10 minutes is satisfactory, exemplify this category.

While the article touches on the idea of hours and days, it aptly notes that this time range is generally not regarded as true real-time. Nevertheless, advancements like receiving up-to-date reports every hour represent a shift from "batch" to "real-time" in certain applications.

In conclusion, the value of time in real-time computing cannot be overstated. As businesses increasingly recognize the importance of making swift decisions, understanding the nuances of real-time measurement becomes paramount. The article by John Piekos serves as a valuable guide in navigating this intricate landscape, emphasizing the need to align the definition of real-time with the specific demands of each business application.

Measuring real-time (2024)
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