Unsynchronized Clocks Research Articles

Grouping Time Series for Efficient Columnar Storage

Columnar storage is now an industry standard design in most open-source or commercial time series database products, making them HTAP systems. The time column of a time series serves as the key for identifying the other value column, namely single-column storage scheme. When multiple time series share a similar set of timestamps, very likely in a module of multiple sensors, it is natural to group them together, i.e., one time column identifies multiple value columns in a single-group storage scheme. While multiple value columns sharing the same time column reduce the space cost of repeating timestamps, it may introduce extra space cost for recording null values. The reason is that time series may not be exactly aligned on each timestamp, owing to missing values, distinct data collection frequencies, unsynchronized clocks and so on. The columngroups storage scheme is thus to divide columns into multiple groups, within which the value columns share the same time column. Unfortunately, the problem of finding the optimal column groups for the minimum space cost is highly challenging, NP-hard according to our analysis. Thereby, we propose a heuristic algorithm for automatically grouping time series for efficient columnar storage. The column groups storage has been deployed in Apache IoTDB, an open-source time series database. The extensive performance analysis, over real-world data from our industrial partners, demonstrates that the proposed column groups achieve near optimal storage, more concise than the storage of single-column or single-group schemes. Interestingly, both the flushing and querying time costs of column groups are comparable to those of single-column or singlegroup, i.e., without incurring extra time cost.

Data synchronization for gas emission measurements from dairy cattle: A matched filter approach

Methane emissions from enteric fermentation in dairy cows make a substantial contribution to the greenhouse gas problem. Sniffer approaches represent a popular low-cost, mobile technology for cow gas emission measurement in industrial installations owing to their providing reliable emission estimates. Despite its advantages, the sniffer approach often yields data inconsistencies during automated acquisition due to unsynchronized clocks between sniffers and associated automatic milking machines, leading to uncertainty in the linking of each animal’s data with methane emission records. Given the constantly growing demand for large-scale methane emission measurements for genetic studies, sniffer installations are expected to increase, making the need for an efficient solution to the data synchronization issue prescient. A novel approach for handling the synchronization problem was developed in this study based on matched filter theory. The approach was verified on gas emission data from multiple commercial dairy farms in Denmark. The results were analyzed and discussed in terms of accuracy and general characteristics of computational performance irrespective of a specific software implementation. The present findings support the conclusion that the presented matched filter-based approach is robust, applicable to the problem of cattle gas emission data synchronization, and convenient for automated data processing.

Timing errors and temporal uncertainty in clinical databases-A narrative review.

A firm concept of time is essential for establishing causality in a clinical setting. Review of critical incidents and generation of study hypotheses require a robust understanding of the sequence of events but conducting such work can be problematic when timestamps are recorded by independent and unsynchronized clocks. Most clinical models implicitly assume that timestamps have been measured accurately and precisely, but this custom will need to be re-evaluated if our algorithms and models are to make meaningful use of higher frequency physiological data sources. In this narrative review we explore factors that can result in timestamps being erroneously recorded in a clinical setting, with particular focus on systems that may be present in a critical care unit. We discuss how clocks, medical devices, data storage systems, algorithmic effects, human factors, and other external systems may affect the accuracy and precision of recorded timestamps. The concept of temporal uncertainty is introduced, and a holistic approach to timing accuracy, precision, and uncertainty is proposed. This quantitative approach to modeling temporal uncertainty provides a basis to achieve enhanced model generalizability and improved analytical outcomes.

Information Fusion Strategies for Collaborative Inertial Radio SLAM

Information fusion strategies for vehicles navigating while aiding their inertial navigation systems (INSs) with terrestrial signals of opportunity (SOPs) are developed and studied. The following problem is considered. Multiple navigating vehicles with access to global navigation satellite system (GNSS) signals are aiding their on-board INSs with GNSS pseudoranges. While navigating, vehicle-mounted receivers draw pseudorange measurements from terrestrial SOPs (e.g., AM/FM radio, digital television, cellular) with unknown emitter positions and unknown and unsynchronized clocks. The vehicles share INS data and SOP pseudoranges to collaboratively estimate the SOPs’ states through an extended Kalman filter using tight coupling. After some time, GNSS signals become unavailable, at which point the navigating vehicles use shared INS and SOP information to continue navigating in a collaborative inertial radio simultaneous localization and mapping (CIRSLAM) framework. This paper develops such CIRSLAM framework and synthesizes what SOP and INS information should be shared between collaborators. Two information fusion strategies are compared: 1) sharing time-of-arrival (TOA) measurements from SOPs; 2) sharing time-difference-of-arrival (TDOA) measurements taken with reference to an SOP. Next, a strategy to efficiently share INS information along with SOP information is discussed. Monte Carlo simulation results are presented that support the analytical findings that vehicles navigating in a CIRSLAM framework, while sharing and fusing SOP TOA measurements, produce a smaller or equal estimation error covariance compared to fusing SOP TDOA measurements. Experimental results are presented demonstrating two unmanned aerial vehicles (UAVs) navigating in a CIRSLAM framework with SOP TOA measurements from terrestrial cellular towers. The final UAVs’ localization error after 30 seconds of GPS unavailability were reduced compared to using an INS alone from around 55 m to around 6 m.

Event-Based Communication Strategies for Collaborative Inertial Radio SLAM

Event-based communication strategies for vehicles navigating by aiding their inertial navigation systems (INSs) with terrestrial signals of opportunity (SOPs) are developed. The following problem is considered. Multiple navigating vehicles with access to global navigation satellite system (GNSS) signals are aiding their on-board INSs with GNSS pseudoranges. While navigating, vehicle-mounted receivers draw pseudorange measurements from terrestrial SOPs with unknown emitter positions and unknown and unsynchronized clocks. The vehicles share INS data and SOP pseudoranges to collaboratively estimate the SOPs' states through an extended Kalman filter. After some time, GNSS signals become unavailable, at which point the navigating vehicles use shared INS and SOP information to continue navigating in a collaborative inertial radio simultaneous localization and mapping (CIRSLAM) framework. Two eventbased communication strategies to share this information are developed, where instead of sharing information at a fixedrate when measurements become available, information is only shared whenever any vehicle's position error could violate a userspecified position error threshold with some desired probability. Simulation results are presented demonstrating the tradeoff between localization performance and the accumulated transmitted data when the event-based transmission scheme is employed versus sharing data at the fixed-rate. Experimental results are presented demonstrating two unmanned aerial vehicles (UAVs) navigating in a CIRSLAM framework with SOP pseudoranges drawn from terrestrial cellular towers. The event-based communication scheme reduced the cumulative communicated data by 86.6% compared to a fixed-rate scheme, while maintaining the specified error constraint.

Detection of Node Capture under Asynchronous Sleep Mode Based on Recurrent Neural Network

In recent years, wireless sensor networks (WSNs) have found numerousapplications in industrial manufacturing and people’s daily lives. However, security risks associated with the use of WSNs have also become increasingly pronounced. An attacker launching an internal attack on a WSNmust first physically capture several nodes, i.e., take control of the target nodes by acquiring, cracking, and analyzing important information carried by the target nodes, thus laying the groundwork for subsequent attack steps. Therefore, physical node capture is a critical step in an internal attack on aWSN. Detecting behaviorsthat indicatephysical capture of nodes provides an early warning of anetwork attack, allowing steps to be taken to prevent further attacks from being launched from the captured nodes. This paper proposes an RNN (recurrent neural network)-based detection method that can be used to detect node capture in WSNs with asynchronous sleep mode at an early stage (i.e., before captured nodes rejoin the network).Thus, the methodenables early detection of network attacks. During the decision-making process, a common monitoring mechanism that relies on cooperation between neighboring nodes is employed to improve detection accuracy. The proposed method obtains the sensor nodes’ states and makes a judgment with the help of RNN, achieving accurate detection of node capture under the condition of unsynchronized clocks. Simulation results demonstrate the proposed method’s capability to achieve high detection accuracy.

Preventing time synchronization in NTP broadcast mode

Network Time Protocol (NTP) is used by millions of hosts on the Internet today to synchronize their clocks. The clock synchronization is necessary for many network applications to function correctly. An unsynchronized clock may lead to the failure of various core Internet services including DNS and RPKI based interdomain routing and opens the path for more sophisticated attacks. In this paper, we describe a new attack that can prevent a client configured in NTP broadcast mode from synchronizing its clock with the server. We test the attack in real networks and show that it is effective in both authenticated and unauthenticated broadcast/multicast modes of NTP. We also perform experiments to measure the overall attack surface by scanning the entire IPv4 address space and show that the NTP broadcast mode is being used in the wild by several low stratum (highly accurate) hosts. We also suggest a few countermeasures to mitigate the proposed attack.

Online Temporal Calibration Based on Modified Projection Model for Visual-Inertial Odometry

Due to the sensors’ latency, unsynchronized clocks, triggering, and data jams, there usually exists an inevitable time offset between image streams and inertial measurement unit (IMU) data sequences in visual-inertial systems. Such a time offset has a significant effect on the robustness and accuracy of the system. In this article, an online temporal calibration algorithm is proposed based on a modified projection model. In particular, we introduce the time offset as an estimated state variable in an extended Kalman filter (EKF)-based visual-inertial odometry (VIO). In addition, in order to align camera and IMU measurements in the time domain, the projection model is sophisticatedly given, and we propose a systematic method to obtain features’ virtual observations with respect to the time offset. Our approach is general and can be easily applied to different EKF-based VIO frameworks. Experimental results demonstrate that the time offset is calibrated quickly and accurately even compared with other existing offline tools, and the proposed online temporal calibration method significantly improves the performance of VIO.

DProf: distributed profiler with strong guarantees

Performance analysis of a distributed system is typically achieved by collecting profiles whose underlying events are timestamped with unsynchronized clocks of multiple machines in the system. To allow comparison of timestamps taken at different machines, several timestamp synchronization algorithms have been developed. However, the inaccuracies associated with these algorithms can lead to inaccuracies in the final results of performance analysis. To address this problem, in this paper, we develop a system for constructing distributed performance profiles called DProf. At the core of DProf is a new timestamp synchronization algorithm, FreeZer, that tightly bounds the inaccuracy in a converted timestamp to a time interval. This not only allows timestamps from different machines to be compared, it also enables maintaining strong guarantees throughout the comparison which can be carefully transformed into guarantees for analysis results. To demonstrate the utility of DProf, we use it to implement dCSP and dCOZ that are accuracy bounded distributed versions of Context Sensitive Profiles and Causal Profiles developed for shared memory systems. While dCSP enables user to ascertain existence of a performance bottleneck, dCOZ estimates the expected performance benefit from eliminating that bottleneck. Experiments with three distributed applications on a cluster of heterogeneous machines validate that inferences via dCSP and dCOZ are highly accurate. Moreover, if FreeZer is replaced by two existing timestamp algorithms (linear regression & convex hull), the inferences provided by dCSP and dCOZ are severely degraded.

A high-precision and fast-sampling frequency measurement method based on FPGA carry chain for airborne optically pumped cesium magnetometer.

Improving the precision and sampling rate of the resonance frequency of cesium atoms is the key to enhancing the same factors of an airborne optically pumped cesium magnetometer (AOPCM). Aiming at the existed problems of AOPCM and characteristics of resonance signal, this paper proposes a high-precision and fast-sampling frequency measurement method based on carry chains of Field-Programmable Gate Array (FPGA). In order to achieve a fast-sampling rate, an improved equal precision frequency measurement method is proposed to measure the standard signal and the resonance signal continuously. Besides, by using the serial full adder to connect FPGA carry chains to a delay line, the delay line is used to compensate the unsynchronized clock edge, so the counting error can be reduced, and the precision of frequency measurement can be improved greatly. Experiments show that the frequency resolution is 0.014 nT and the relative error is lower than 2 × 10-6 when the sampling rate is 500 Hz. The experimental result indicates that the proposed method improves the precision and sampling rate of resonance frequency measurement greatly. Consequently, the precision and sampling rate of AOPCM can be improved.

Valproic acid disrupts the oscillatory expression of core circadian rhythm transcription factors

Valproic acid (VPA) is a well-established therapeutic used in treatment of seizure and mood disorders as well as migraines and a known hepatotoxicant. About 50% of VPA users experience metabolic disruptions, including weight gain, hyperlipidemia, and hyperinsulinemia, among others. Several of these metabolic abnormalities are similar to the effects of circadian rhythm disruption. In the current study, we examine the effect of VPA exposure on the expression of core circadian transcription factors that drive the circadian clock via a transcription-translation feedback loop. In cells with an unsynchronized clock, VPA simultaneously upregulated the expression of genes encoding core circadian transcription factors that regulate the positive and negative limbs of the feedback loop. Using low dose glucocorticoid, we synchronized cultured fibroblast cells to a circadian oscillatory pattern. Whether VPA was added at the time of synchronization or 12h later at CT12, we found that VPA disrupted the oscillatory expression of multiple genes encoding essential transcription factors that regulate circadian rhythm. Therefore, we conclude that VPA has a potent effect on the circadian rhythm transcription-translation feedback loop that may be linked to negative VPA side effects in humans. Furthermore, our study suggests potential chronopharmacology implications of VPA usage.

Intervehicle Range Estimation From Periodic Broadcasts

Dedicated short-range communications enables vehicular communication using periodic broadcast messages. We propose to use these periodic broadcasts to perform intervehicle ranging. Motivated by this scenario, we study the general problem of range estimation between pairs of moving vehicles using periodic broadcasts. Each vehicle has its own independent and unsynchronized clock, which can exhibit significant drift between consecutive periodic broadcast transmissions. Consequently, both the clock offsets and drifts need to be taken into account in addition to the vehicle motion to accurately estimate the vehicle ranges. We develop a range estimation algorithm using local polynomial smoothing of the vehicle motion. The proposed algorithm can be applied to networks with arbitrary number of vehicles and requires no additional message exchanges apart from the periodic broadcasts. We experimentally validate our algorithm and show that its performance is close to that of unicast round-trip time ranging. In particular, we are able to achieve submeter ranging accuracies in vehicular scenarios. Our scheme requires additional timestamp information to be transmitted as part of the broadcast messages, and we develop a novel timestamp compression algorithm to minimize the resulting overhead.

An Algorithm for Accurate Distributed Time Synchronization in Mobile Wireless Sensor Networks from Noisy Difference Measurements

AbstractWe propose a distributed algorithm for time synchronization in mobile wireless sensor networks. The problem of time synchronization is formulated as nodes estimating their skews and offsets from noisy difference measurements of offsets and logarithm of skews; the measurements acquired by time‐stamped message exchanges between neighbors. The algorithm ensures that the estimation error is mean square convergent (variance converging to 0) under certain conditions. A sequence of scheduled update instants is used to meet the requirement of decreasing time‐varying gains that need to be synchronized across nodes with unsynchronized clocks. Moreover, a modification on the algorithm is also presented to improve the initial convergence speed. Simulations indicate that highly accurate global time estimates can be achieved with the proposed algorithm for long time durations, while the errors in competing algorithms increase over time.

Joint Ranging and Synchronization for an Anchorless Network of Mobile Nodes

Synchronization and localization are critical challenges for the coherent functioning of a wireless network, which are conventionally solved independently. Recently, various estimators have been proposed for pairwise synchronization between immobile nodes, based on time stamp exchanges via two-way communication. In this paper, we consider a network of mobile nodes for which a novel joint time-range model is presented, treating both unsynchronized clocks and the pairwise distances as a polynomial functions of true time. For a pair of nodes, a least squares solution is proposed for estimating the pairwise range parameters between the nodes, in addition to estimating the clock offsets and clock skews. Extending these pairwise solutions to network-wide ranging and clock synchronization, we present a central data fusion based global least squares algorithm. A unique solution is nonexistent without a constraint on the cost function e.g., a clock reference node. Ergo, a constrained framework is proposed and a new Constrained Cramér-Rao Bound (CCRB) is derived for the joint time-range model. In addition, to alleviate the need for a single clock reference, various clock constraints are presented and their benefits are investigated using the proposed solutions. Simulations are conducted and the algorithms are shown to approach the theoretical limits.

Cooperative localization of underwater robots with unsynchronized clocks

AbstractThis paper proposes an interval based approach for localizing a group of underwater robots with unsynchronized clocks. We use sonar communication and consider that the travel time of the sonar waves cannot be neglected, e.g. when the robots are fast and far-spaced. Therefore we cannot suppose that we measure a true distance between robots at the same time, but between robots at di􀉼erent times. Moreover, as the clocks of the robots are unsynchronized, the emitting and receiving times of the sonar waves are uncertain. To solve this problem, we cast the state equations of our robots as a constraint satisfaction problem and consider the sonar measurements as intertemporal constraints on uncertain times. We introduce the notion of interval of function to encompass the robots trajectory and clock with their uncertainty. We then use interval propagation to successively contract these intervals around the true position and clock of the robots. Several test cases are provided, with both simulated and experimental results.

Rambo: a robust, reconfigurable atomic memory service for dynamic networks

In this paper, we present Rambo, an algorithm for emulating a read/write distributed shared memory in a dynamic, rapidly changing environment. Rambo provides a highly reliable, highly available service, even as participants join, leave, and fail. In fact, the entire set of participants may change during an execution, as the initial devices depart and are replaced by a new set of devices. Even so, Rambo ensures that data stored in the distributed shared memory remains available and consistent. There are two basic techniques used by Rambo to tolerate dynamic changes. Over short intervals of time, replication suffices to provide fault-tolerance. While some devices may fail and leave, the data remains available at other replicas. Over longer intervals of time, Rambo copes with changing participants via reconfiguration, which incorporates newly joined devices while excluding devices that have departed or failed. The main novelty of Rambo lies in the combination of an efficient reconfiguration mechanism with a quorum-based replication strategy for read/write shared memory. The Rambo algorithm can tolerate a wide variety of aberrant behavior, including lost and delayed messages, participants with unsynchronized clocks, and, more generally, arbitrary asynchrony. Despite such behavior, Rambo guarantees that its data is stored consistency. We analyze the performance of Rambo during periods when the system is relatively well-behaved: messages are delivered in a timely fashion, reconfiguration is not too frequent, etc. We show that in these circumstances, read and write operations are efficient, completing in at most eight message delays.

Randomly Ranked Mini Slots for Fair and Efficient Medium Access Control in Ad Hoc Networks

Ad hoc networks offer infrastructure-free operation, where no entity can provide reliable coordination among nodes. Medium Access Control (MAC) protocols in such a network must overcome the inherent unreliability of the network and provide high throughput and adequate fairness to the different flows of traffic. In this paper, we propose a MAC protocol that can achieve an excellent balance between throughput and fairness. Our protocol has two versions: Randomly Ranked Mini Slots (RRMS) utilizes control-message handshakes similar to IEEE 802.11. Randomly Ranked Mini Slots with Busy Tone (RRMS-BT) is the better performer of the two, but requires a receiver busy tone. The protocol makes use of granule time slots and sequences of pseudorandom numbers to maximize spatial reuse and divide the throughput fairly among nodes. We demonstrate the performance of this protocol using simulation with fixed and random topologies and show that these results are robust to difficult network configurations and unsynchronized clocks. We further develop novel metrics of long-term and short-term fairness for rigorous performance evaluation. Our simulation results include a detailed comparison between the proposed protocol and existing protocols that have been shown to excel in terms of throughput or fairness.

Location Tracking Using Differential Range Measurements

Automatic vehicle location and automatic vehicle monitoring systems were developed originally to track fleet vehicles such as bus lines, truck lines, taxicabs, police patrol cars, and delivery vehicles. In a bus system, individuals known as “point men” were situated at certain places in the bus route to monitor the flow. In police work, a jurisdiction was subdivided into sectors to help dispatchers identify patrol vehicles in particular geographic areas. The widespread acceptance of wireless cellular and personal communication systems by the public has lead to an exponential growth in the industry. Each mobile telephone or pager is connected electronically to a fix radio infrastructure, which provides an opportunity for applying an automatic monitoring system. Thus, the potential and opportunity to automatically track a mobile station are unlimited. A major driving force behind geolocation tracking is emergency calls, E-911. A large number of emergency calls are place from mobile telephones, so it is important that one is able to achieve a position fix on these calls. Thus, there is a need to develop accurate and efficient algorithms for locating a mobile user. In this article we propose an algorithm using differential range measurements to determine a mobile's location. A differential range measurement is defined as the difference between two range measurements. A closed-form location algorithm based on the least-squares solution was developed. This estimation algorithm was shown to be tolerant to measurement errors caused by unsynchronized base station clocks.

A timeout-based message ordering protocol for a lightweight software implementation of tmr systems

Replicated processing with majority voting is a well-known method for achieving reliability and availability. Triple modular redundant (TMR) processing is the most commonly used version of that method. Replicated processing requires that the replicas reach agreement on the order in which input requests are to be processed. Almost all synchronous and deterministic ordering protocols published in the literature are time-based in the sense that they require replicas' clocks to be kept synchronized within some known bound. We present a protocol for TMR systems that is based on timeouts and does not require clocks to be kept in bounded synchronism. Our design efforts focus on keeping the ordering delays small, without an unnecessary increase in message overhead. Consequently, we are able to show that no symmetric protocol that works only with unsynchronized clocks can provide a smaller worst-case delay. We also demonstrate through analysis and experiments that our protocol is faster than a time-based one of identical message complexity in certain situations which can prevail in many application settings.

Point algebras for temporal reasoning: Algorithms and complexity

We investigate the computational complexity of temporal reasoning in different time models such as totally-ordered, partially-ordered and branching time. Our main result concerns the satisfiability problem for point algebras and point algebras extended with disjunctions—for these problems, we identify all tractable subclasses. We also provide a number of additional results; for instance, we present a new time model suitable for reasoning about systems with a bounded number of unsynchronized clocks, we investigate connections with spatial reasoning and we present improved algorithms for deciding satisfiability of the tractable point algebras.