Timestamping Error Research Articles

Everything at the proper time: Repairing identical timestamp errors in event logs with Generative Adversarial Networks

Process mining generates valuable insights into business processes through the analysis of event logs. However, event logs are commonly subject to various data quality issues which hinder the success of process mining initiatives in organizations. Identical timestamp errors, for example, occur when multiple events of a process instance mistakenly share the same timestamp. This error causes discovered process models to be unrepresentative and process performance analysis results to be misleading. To address this problem, we propose a method for automatically repairing identical timestamp errors in event logs. To that end, we combine existing method components for error detection and reordering of erroneous events with a novel approach for repairing timestamps based on Generative Adversarial Networks. To allow for a rigorous evaluation, we instantiate our approach as a software prototype, and use it to repair a total of six real-life and artificial event logs with overall 30 variations. Thereby, we show that the proposed method shows improved results compared to alternative approaches for repairing identical timestamp errors in event logs.

Energy-Efficient Time Synchronization Based on Nonlinear Clock Skew Tracking for Underwater Acoustic Networks

Time synchronization plays an important role in the scheduling and position technologies of sensor nodes in underwater acoustic networks (UANs). The time synchronization (TS) algorithms face challenges such as high requirements of energy efficiency, the estimation accuracy of the time-varying clock skew and the suppression of the impulsive noise. To achieve accurate time synchronization for UANs, an energy-efficient TS method based on nonlinear clock skew tracking (NCST) is proposed. First, based on the sea trial temperature data and the crystal oscillators’ temperature–frequency characteristics, a nonlinear model is established to characterize the dynamic of clock skews. Second, a single-way communication scheme based on a receiver-only (RO) paradigm is used in the NCST-TS to save limited energy. Meanwhile, impulsive noises are considered during the communication process and the Gaussian mixture model (GMM) is employed to fit receiving timestamp errors caused by non-Gaussian noise. To combat the nonlinear and non-Gaussian problem, the particle filter (PF)-based algorithm is used to track the time-varying clock state and an accurate posterior probability density function under the GMM error model is also given in PF. The simulation results show that under the GMM error model, the accumulative Root Mean Square Errors (RMSE) of NCST-TS can be reduced from 10−4 s to 10−5 s compared with existing protocols. It also outperforms the other TS algorithms in the aspect of energy efficiency.

Synchronization in 5G networks: a hybrid Bayesian approach toward clock offset/skew estimation and its impact on localization

Clock synchronization has always been a major challenge when designing wireless networks. This work focuses on tackling the time synchronization problem in 5G networks by adopting a hybrid Bayesian approach for clock offset and skew estimation. Furthermore, we provide an in-depth analysis of the impact of the proposed approach on a synchronization-sensitive service, i.e., localization. Specifically, we expose the substantial benefit of belief propagation (BP) running on factor graphs (FGs) in achieving precise network-wide synchronization. Moreover, we take advantage of Bayesian recursive filtering (BRF) to mitigate the time-stamping error in pairwise synchronization. Finally, we reveal the merit of hybrid synchronization by dividing a large-scale network into local synchronization domains and applying the most suitable synchronization algorithm (BP- or BRF-based) on each domain. The performance of the hybrid approach is then evaluated in terms of the root mean square errors (RMSEs) of the clock offset, clock skew, and the position estimation. According to the simulations, in spite of the simplifications in the hybrid approach, RMSEs of clock offset, clock skew, and position estimation remain below 10 ns, 1 ppm, and 1.5 m, respectively.

NLOS Identification for Localization Based on the Application of UWB

Ultra-wide bandwidth (UWB) transmission is a promising technology for localization systems, due to its power efficiency, strong penetrability, and robust operation in severe multipath environments. As we know, the large time stamp errors result in significant localization errors. The time stamp errors will be large if the direct path (DP) signal that is between the transmitting node and the receiving node is not detected correctly at the receiving node. It always happens in non-line-of-sight (NLOS) conditions. So it is very important to identify NLOS, because we want to mitigate the significant localization errors in NLOS conditions. The existing techniques based on machine learning techniques have not discussed the problem that the features used to represent the propagation conditions are affected by the transmission distance of the signal, the transmitted power, the transmitted preamble length and other factors (related-factors-of-features, RFOF), which seriously affect the accuracy of the classifier that is trained by the features. So a practical NLOS identification (PNI) technique is proposed in this paper. PNI includes reduce-effect-of-related-factors (REORF) for reducing the serious effect and a set of appropriate features for improving speed of NLOS identification. Experimental results show that PNI have better performance in various system environment and real-world environment than the existing techniques.

Time Synchronization for Wireless Sensors Using Low-Cost GPS Module and Arduino

Time synchronisation for wireless sensors is important for a proper interpretation of measurements, particularly for acceleration measurements to estimate mode-shapes correctly. This paper presents a new time synchronisation method working independently on each node without exchanging time-sync packets among nodes. This stand-along operation can make field measurement campaigns very time-efficient without a need of constructing and validating the wireless sensor network. The proposed method firstly time-stamps measurements using the accurate time-source from a GPS module on each node, and secondly re-samples the time-stamped data to get time-synchronised data. The time-stamping method proposed in the study utilises Pulse-Per-Second (PPS) signals and NMEA (National Marine Electronics Association) sentences generated by a low-cost GPS module, and the internal timer/counter unit of Arduino. Error analysis on the proposed time-stamping method was carried out and derived an analytical expression for the maximum variance of time-stamping error of the proposed method. Four experiments have been carried out to observe 1) the long-term operational stability of the GPS module, 2) the accuracy of the PPS signals, 3) the accuracy of the proposed time-stamping method, and 4) the validity of the proposed time-synchronisation method for output-only modal analysis on a laboratory floor structure. The GPS module was found to operate or to resume operating stably for the entire test period of seven days even with the limited field of view to the sky. The relative time errors of two PPS signals from four GPS modules were found to be within +/-400 nsec. The time-stamping error measured by two identical time-stamping Arduinos for common trigger signals was found to have a standard deviation of 40.8 nsec, which agreed well with the maximum value of 42.0 nsec predicted by the error analysis. From the output-only modal analysis, the estimated modal parameters were found to agree well with that from the wired acceleration sensors. The phase angle of the cross spectral density of the two wireless accelerations showed that there was no apparent time-synchronisation error observable. These observations indicated a successful operation of the proposed time-synchronisation method.

An Analytic Model for Fault Diagnosis in Power Systems Utilizing Redundancy and Temporal Information of Alarm Messages

In modern transmission systems, duplicated protections are widely employed to enhance reliability, and global positioning system (GPS) substation clocks are set up to deliver a higher degree of synchronization. Thus, redundant alarms tagged with synchronized timestamps would be received during a fault. Both redundancy and timestamps of alarms consist of rich and useful information. Given this background, an effort is made to develop a novel analytic model for power system fault diagnosis so as to well utilize redundancy and temporal information of alarms. An alarm preprocessing procedure is proposed to preserve such properties without impairing diagnosis accuracy and efficiency. A new fault hypothesis is established to systematically take account of malfunctions of protective devices, missing and distorted alarm messages, and timestamp errors in the proposed model. An objective function is developed for fault diagnosis, and could accommodate various protection schemes and bus configurations. Based on the presented fault diagnosis method, a software package is developed. Several fault scenarios occurred in an actual power system in China are served for demonstrating the correctness and efficiency of the developed software package.

Time Stamp Errors and the Stock Price Reaction to Analyst Recommendation and Forecast Revisions

This paper investigates the problem of time stamp errors in the IBES database, the most important data provider of analyst recommendations and forecasts currently. We compare IBES to alternative data sources and show that IBES announcement dates of both recommendations and forecasts are systematically delayed. As a consequence, announcement returns in IBES are significantly underestimated while the pre-announcement effect, which often includes the effective announcement date, is overestimated. We also show that time stamp errors in IBES differ significantly in the cross-section, driving some of the cross-sectional differences in announcement returns. Finally, we discuss how existing research is affected by time stamp errors.

Adding accurate timestamping capability to wireless networks for smart grids

Smart grids rely on bi-directional communications between energy production sites and utilization sites. Usually, different approaches are used for implementing the required Wide, Field, and Home Area Networks (WAN, FAN and HAN, respectively). These networks are realized using very different (hybrid) technologies, for instance wired for WAN and wireless for FAN and HAN. However, an accurate common sense of time must be guaranteed among all smart grid participants, as it happens in any other distributed systems. Satisfying this need is challenging for wireless networks, while mature time distribution technologies are available for wired networks. The major issue for wireless devices is to provide accurate timestamping of network events, the key element of any time synchronization protocol. The objective of this paper is to propose low-cost and low-complexity timestamping techniques that also maintain full compatibility with already existing (unlicensed) communication standard for wireless nodes used in smart grids. In addition, a suitable platform exploiting the Software Defined Radio paradigm for comparative evaluation of these techniques is also discussed. Simulation and experimental results confirm the feasibility of the proposed approach, with the standard deviation of the timestamping error scalable down to 5ns.