Our fast-approaching future of driverless cars and “smart” electrical grids will depend on billions of linked devices making decisions and communicating with split-second precision to prevent highway collisions and power outages. But a new report released by the National Institute of Standards and Technology (NIST) warns that this future could be stalled by our lack of effective methods to marry computers and networks with timing systems.
The authors, who include NIST’s Marc Weiss and seven experts from academia and industry, are concerned about the way most modern data systems are designed to process and exchange data with one another and what that could mean for a world of discrete processors and mechanical devices linked by an information network—the “Internet of Things” (IoT). In addition to giving you access to the status of your home appliances anywhere, anytime, the IoT encompasses many potentially important but delicate applications such as cars that drive themselves and telemedicine surgical suites that allow doctors to operate on patients from remote locations. People are still imagining applications for the IoT, but GE predicts that nearly half the global economy can benefit from it.
We stand at the advent of a revolutionary new economy fueled by the global Internet of Everything, IoE, a combination of the traditional telecom system with its growing need for wireless technology, and the emerging Internet of Things, IoT, including Machine-to-Machine (M2M) technology. Cisco, among others, predicts that there will be a trillion endpoints connected to the internet by 2022, with $14.4 trillion in value at stake. General Electric, GE, says “about 46% of the global economy or $32.3 trillion in global output can benefit from the Industrial Internet”. The National Institute of Standards and Technology (NIST) has formed a Cyber-Physical Sytems (CPS) Public Working Group to bring together experts to help define and shape key aspects of CPS, and to create a framework and reference architectures to encourage interoperability and appropriate designs. One fundamental enabler of this revolution will be a marriage of timing signals and data that breaks through the existing barriers. Currently, optimal use of data in computing and networking is anathema to optimal use of timing signals. Computer hardware, software and networking all isolate timing processes, allowing the data to be processed with maximum efficiency due in part to asynchrony. Yet, coordination of processes, timestamping of events, latency measurement and optimal use of precious spectrum are enabled by timing.
Timing is critical for the future development and improvements to several current high value applications. For example, smart transportation where the exchange of information between vehicles, highways, and perhaps civil authorities will depend on a robust ubiquitous timing system to ensure the availability and integrity of the data. Similar requirements are found in the operation of the power grid, especially now that wind farms, solar arrays and the like, which will require different control strategies, are becoming an important part of the system. Medical applications such as tele-surgery, and applications in financial systems are other important examples.
There are three different types of timing signals for synchronization:
Frequency can be supplied by an individual clock, such as a commercial cesium standard, though pragmatism drives the use of oscillators that require calibration and active reference signals. By contrast, phase and time synchronization always require transport of signals plus data, the transfer of timing signals. Timing signals are physical; they occur on the physical layer of networks. The IoT will have many devices and applications that require frequency, time or phase synchronization. Frequency, time, and phase will all need to cross layers, boundaries, and networks from their sources in accurate clocks. Requirements for these transfer systems will include parameters that can create different, perhaps orthogonal, demands on systems. Accuracy, stability, integrity and security requirements are realized with different demands on systems. Timing is generally regarded today as a performance metric, not as a correctness criterion. Timing accuracy emerges from the details of the implementation: the system topology and the specific equipment used. To facilitate the massive growth of the IoE, data processing and networking will need to converge with timing, making integration of cyber and physical seamless. However, this requires new research at fundamental levels, allowing precise and verifiable timing signals to be designed with correctness criteria.
They propose a layered model for time-aware applications, computers, and communications systems (TAACCS) starting with the bottom layer of oscillators and clocks and proceeding up- time transfer, timeaware networks and communication systems, hardware and software timing support for applications, design environments, and finally applications that exploit timing
ABSTRACT Time-Aware Applications, Computers, and Communication Systems (TAACCS)
A new economy built on the massive growth of endpoints on the internet will require precise and verifiable timing in ways that current systems do not support. Applications, computers, and communications systems have been developed with modules and layers that optimize data processing but degrade accurate timing. State-of-the-art systems now use timing only as a performance metric. Correctness of timing as a metric cannot currently be designed into systems independent of hardware and/or software implementations. To enable the massive growth predicted, accurate timing needs cross-disciplinary research to be integrated into these existing systems. This paper reviews the state of the art in six crucial areas central to the use of timing signals in these systems. Each area is shown to have critical issues requiring accuracy or integrity levels of timing, that need research contributions from a range of disciplines to solve.
Brian Wang is a Futurist Thought Leader and a popular Science blogger with 1 million readers per month. His blog Nextbigfuture.com is ranked #1 Science News Blog. It covers many disruptive technology and trends including Space, Robotics, Artificial Intelligence, Medicine, Anti-aging Biotechnology, and Nanotechnology.
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