A low-profile high-performance crystal oscillator for timekeeping applications

Karlquist, R.K.; Cutler, L.S.; Ingman, E.M.; Johnson, Jason L.; Parisek, T.

doi:10.1109/freq.1997.639205

Cited by 11 publications

(2 citation statements)

References 2 publications

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“…Table 1 illustrates that the CPU frequency diminishes at the rate of approximately 150 Hz per degree Celsius. This is consistent with other studies [17,18] showing a linear relation between the frequency and the temperature, with a positive or negative slope depending on the specific circuit used as clock driver.…”

Section: Effect Of Temperature On Clock Frequencysupporting

confidence: 93%

Internal Clock Drift Estimation in Computer Clusters

Marouani

Dagenais

2008

Journal of Computer Networks and Communications

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Most computers have several high-resolution timing sources, from the programmable interrupt timer to the cycle counter. Yet, even at a precision of one cycle in ten millions, clocks may drift significantly in a single second at a clock frequency of several GHz. When tracing the low-level system events in computer clusters, such as packet sending or reception, each computer system records its own events using an internal clock. In order to properly understand the global system behavior and performance, as reported by the events recorded on each computer, it is important to estimate precisely the clock differences and drift between the different computers in the system. This article studies the clock precision and stability of several computer systems, with different architectures. It also studies the typical network delay characteristics, since time synchronization algorithms rely on the exchange of network packets and are dependent on the symmetry of the delays. A very precise clock, based on the atomic time provided by the GPS satellite network, was used as a reference to measure clock drifts and network delays. The results obtained are of immediate use to all applications which depend on computer clocks or network time synchronization accuracy.

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Section: Effect Of Temperature On Clock Frequencysupporting

confidence: 93%

Internal Clock Drift Estimation in Computer Clusters

Marouani

Dagenais

2008

Journal of Computer Networks and Communications

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“…However, these techniques are used to generate a stable clock frequency signal and cannot be used to obtain the characteristics of the computer. Other studies have shown the relationship between temperature, PC CPU clock frequency, and clock drift [16], [17], and Marouani et al reported that the clock frequency varied by approximately 150 hertz per Celsius degree for the PC CPUs in their study [18]. However, they did not mention any individual clock characteristics of the computer.…”

Section: B Contribution Of This Researchmentioning

confidence: 86%

Extraction of Computer-Inherent Characteristics Based on Time Drift and CPU Core Temperature

et al. 2020

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The number of computers that provide information services via the Internet is constantly increasing, particularly for IoT applications. Compared to the servers in managed data centers, IoT computers have an increased risk of contamination from unidentified computers. It is therefore important for applications that utilize IoT to identify the appropriate computers to use. However, it is difficult to assign digital identifiers with adequate protection to a huge number of IoT computers. In this work, we have devised a method to extract computer-specific features from the characteristics of the CPU core temperature and the drift of the time information. This feature data can be treated as computer-specific information, just like human biometric information. We performed experiments on two types of computer (three of each) with the same software settings and obtained a regression linear equation for each that represents the time deviation per temperature. The correlation coefficients of these equations were greater than 0.9 for all, and a strong positive correlation was obtained. From the equation and the temperature values, we found that it is possible to estimate the computer-specific time deviation. Our method does not require the implementation of a special temperature sensor. Therefore, it shows good potential for future applications.

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