Hough Transform-Based Clock Skew Measurement Over Network

Saputra, Komang Oka; Teng, Wei-Chung; Chen, Tsung-Han

doi:10.1109/tim.2015.2450293

Cited by 10 publications

(34 citation statements)

References 28 publications

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“…However, the HT-based method is designed to trade off higher computation time for improved robustness in these situations [8], and so be its extension DROML.…”

Section: Evaluation Resultsmentioning

confidence: 99%

“…In this work, a method called dynamic region of offset majority locating (DROML) is developed to detect multi-segment cases, and to precisely estimate the skew. DROML is designed to work in realtime, and it uses a modified version of the HT-based method [8] both to measure the skew of one segment and to detect the break between adjacent segments. In the evaluation section, the modified HT-based method is compared with the original method and with a linear programming algorithm (LPA) on accumulated-time and short-term measurement.…”

Section: Discussionmentioning

confidence: 99%

“…Furthermore, since LocateROM() is able to output a stable ROM with only a few hundred offsets [8], DROML is able to give a reasonable skew estimation soon after the measurement begins. Finally, the inc batch unit used in DROML might cause the segment boundary to be located imprecisely, and one segment might contain a few points which should belong to the adjacent segment.…”

Section: Detecting the Boundaries Of Segmentsmentioning

confidence: 99%

“…Since LPA uses offsets of minimal delay, which are in fact low out- liers, to determine the line, it requires a large amount of time to collect enough low outliers in order to stabilize its estimation. Recently, Oka et al proposed the Hough transform (HT)-based method, which uses the gradient of the ROM's lower boundary line as the estimated clock skew [8]. The HT-based approach provides the same level of precision as LPA, but as the ROM becomes stable with just a few hundred offsets, the measurement time can be reduced to less than 10 minutes.…”

Section: Introductionmentioning

confidence: 99%

“…Finally, DROML is designed to adaptively estimate the global skew such that it is able to provide real-time estimation. As the second contribution, the original HTbased method [8] is also improved in order to locate the most representative ROM for a given number-of-bounded-offsets threshold. The improved version, wrapped as a function called LocateROM(), is able to provide more precise estimation than LPA and the original HT-based method.…”

Section: Introductionmentioning

confidence: 99%

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Hough Transform-Based Clock Skew Measurement by Dynamically Locating the Region of Offset Majority

Saputra

Teng

Nara

2016

IEICE Trans. Inf. & Syst.

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SUMMARYA network-based remote host clock skew measurement involves collecting the offsets, the differences between sending and receiving times, of packets from the host within a period of time. Although the variant and immeasurable delay in each packet prevents the measurer from getting the real clock offset, the local minimum delays and the majority of delays delineate the clock offset shifts, and are used by existing approaches to estimate the skew. However, events during skew measurement like time synchronization and rerouting caused by switching network interface or base transceiver station may break the trend into multi-segment patterns. Although the skew in each segment is theoretically of the same value, the skew derived from the whole offset-set usually differs with an error of unpredictable scale. In this work, a method called dynamic region of offset majority locating (DROML) is developed to detect multi-segment cases, and to precisely estimate the skew. DROML is designed to work in realtime, and it uses a modified version of the HT-based method [8] both to measure the skew of one segment and to detect the break between adjacent segments. In the evaluation section, the modified HT-based method is compared with the original method and with a linear programming algorithm (LPA) on accumulated-time and short-term measurement. The fluctuation of the modified method in the short-term experiment is 0.6 ppm (parts per million), which is obviously less than the 1.23 ppm and 1.45 ppm from the other two methods. DROML, when estimating a four-segment case, is able to output a skew of only 0.22 ppm error, compared with the result of the normal case.

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“…However, the HT-based method is designed to trade off higher computation time for improved robustness in these situations [8], and so be its extension DROML.…”

Section: Evaluation Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Detecting the Boundaries Of Segmentsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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