Estimation and removal of clock skew from network delay measurements
21 Mar 1999-Vol. 1, pp 227-234
TL;DR: A linear programming-based algorithm is introduced to estimate the clock skew in network delay measurements and its performance is compared to that of three other algorithms to show that the algorithm is unbiased, and that the sample variance of the skew estimate is better than existing algorithms.
Abstract: Packet delay and loss traces are frequently used by network engineers, as well as network applications, to analyze network performance. The clocks on the end-systems used to measure the delays, however, are not always synchronized, and this lack of synchronization reduces the accuracy of these measurements. Therefore, estimating and removing relative skews and offsets from delay measurements between sender and receiver clocks are critical to the accurate assessment and analysis of network performance. We introduce a linear programming-based algorithm to estimate the clock skew in network delay measurements and compare it with three other algorithms. We show that our algorithm has a time complexity of O(N), leaves the delay after the skew removal positive, and is robust in the sense that the error margin of the skew estimate is independent of the magnitude of the skew. We use traces of real Internet delay measurements to assess the algorithm, and compare its performance to that of three other algorithms. Furthermore, we show through simulation that our algorithm is unbiased, and that the sample variance of the skew estimate is better (smaller) than existing algorithms.
Citations
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01 May 2005
TL;DR: In this paper, a survey and evaluation of clock synchronization protocols based on a palette of factors such as precision, accuracy, cost, and complexity is presented, which can help developers either in choosing an existing synchronization protocol or in defining a new protocol that is best suited to the specific needs of a sensor network application.
Abstract: Recent advances in micro-electromechanical (MEMS) technology have led to the development of small, low-cost, and low-power sensors Wireless sensor networks (WSNs) are large-scale networks of such sensors, dedicated to observing and monitoring various aspects of the physical world In such networks, data from each sensor is agglomerated using data fusion to form a single meaningful result, which makes time synchronization between sensors highly desirable This paper surveys and evaluates existing clock synchronization protocols based on a palette of factors like precision, accuracy, cost, and complexity The design considerations presented here can help developers either in choosing an existing synchronization protocol or in defining a new protocol that is best suited to the specific needs of a sensor-network application Finally, the survey provides a valuable framework by which designers can compare new and existing synchronization protocols
1,018 citations
TL;DR: Remote physical device fingerprinting is introduced, or fingerprinting a physical device, as opposed to an operating system or class of devices, remotely, and without the fingerprinted device's known cooperation, by exploiting small, microscopic deviations in device hardware: clock skews.
Abstract: We introduce the area of remote physical device fingerprinting, or fingerprinting a physical device, as opposed to an operating system or class of devices, remotely, and without the fingerprinted device's known cooperation. We accomplish this goal by exploiting small, microscopic deviations in device hardware: clock skews. Our techniques do not require any modification to the fingerprinted devices. Our techniques report consistent measurements when the measurer is thousands of miles, multiple hops, and tens of milliseconds away from the fingerprinted device and when the fingerprinted device is connected to the Internet from different locations and via different access technologies. Further, one can apply our passive and semipassive techniques when the fingerprinted device is behind a NAT or firewall, and. also when the device's system time is maintained via NTP or SNTP. One can use our techniques to obtain information about whether two devices on the Internet, possibly shifted in time or IP addresses, are actually the same physical device. Example applications include: computer forensics; tracking, with some probability, a physical device as it connects to the Internet from different public access points; counting the number of devices behind a NAT even when the devices use constant or random IP IDs; remotely probing a block of addresses to determine if the addresses correspond to virtual hosts, e.g., as part of a virtual honeynet; and unanonymizing anonymized network traces.
770 citations
01 Nov 2013
TL;DR: A novel framework for jointly estimating the temporal offset between measurements of different sensors and their spatial displacements with respect to each other is presented, enabled by continuous-time batch estimation and extends previous work by seamlessly incorporating time offsets within the rigorous theoretical framework of maximum likelihood estimation.
Abstract: In order to increase accuracy and robustness in state estimation for robotics, a growing number of applications rely on data from multiple complementary sensors. For the best performance in sensor fusion, these different sensors must be spatially and temporally registered with respect to each other. To this end, a number of approaches have been developed to estimate these system parameters in a two stage process, first estimating the time offset and subsequently solving for the spatial transformation between sensors. In this work, we present on a novel framework for jointly estimating the temporal offset between measurements of different sensors and their spatial displacements with respect to each other. The approach is enabled by continuous-time batch estimation and extends previous work by seamlessly incorporating time offsets within the rigorous theoretical framework of maximum likelihood estimation. Experimental results for a camera to inertial measurement unit (IMU) calibration prove the ability of this framework to accurately estimate time offsets up to a fraction of the smallest measurement period.
626 citations
Cites methods from "Estimation and removal of clock ske..."
...After removing stochastic effects on these fixed rate measurements using the approach of Moon et al. [4], it is sometimes possible to infer the delay from sensor data....
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TL;DR: This article illustrates that many of the proposed clock synchronization protocols can be interpreted and their performance assessed using common statistical signal processing methods, and shows that advanced signal processing techniques enable the derivation of optimal clock synchronization algorithms under challenging scenarios.
Abstract: Clock synchronization is a critical component in the operation of wireless sensor networks (WSNs), as it provides a common time frame to different nodes. It supports functions such as fusing voice and video data from different sensor nodes, time-based channel sharing, and coordinated sleep wake-up node scheduling mechanisms. Early studies on clock synchronization for WSNs mainly focused on protocol design. However, the clock synchronization problem is inherently related to parameter estimation, and, recently, studies on clock synchronization began to emerge by adopting a statistical signal processing framework. In this article, a survey on the latest advances in the field of clock synchronization of WSNs is provided by following a signal processing viewpoint. This article illustrates that many of the proposed clock synchronization protocols can be interpreted and their performance assessed using common statistical signal processing methods. It is also shown that advanced signal processing techniques enable the derivation of optimal clock synchronization algorithms under challenging scenarios.
571 citations
Cites methods from "Estimation and removal of clock ske..."
...Even if the delay distribution is not exponential, it is quite logical to use a linear program to estimate the clock parameters, and, hence, this approach was elegantly put forward in [11]....
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...The exponential delay model is also supported by experimental measurements [11], [12]....
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Proceedings Article•
10 Aug 2016TL;DR: An anomaly-based intrusion detection system (IDS), called Clock-based IDS (CIDS), which measures and then exploits the intervals of periodic in-vehicle messages for fingerprinting ECUs and facilitates a rootcause analysis; identifying which ECU mounted the attack.
Abstract: As more software modules and external interfaces are getting added on vehicles, new attacks and vulnerabilities are emerging. Researchers have demonstrated how to compromise in-vehicle Electronic Control Units (ECUs) and control the vehicle maneuver. To counter these vulnerabilities, various types of defense mechanisms have been proposed, but they have not been able to meet the need of strong protection for safety-critical ECUs against in-vehicle network attacks. To mitigate this deficiency, we propose an anomaly-based intrusion detection system (IDS), called Clock-based IDS (CIDS). It measures and then exploits the intervals of periodic in-vehicle messages for fingerprinting ECUs. The thus-derived fingerprints are then used for constructing a baseline of ECUs' clock behaviors with the Recursive Least Squares (RLS) algorithm. Based on this baseline, CIDS uses Cumulative Sum (CUSUM) to detect any abnormal shifts in the identification errors - a clear sign of intrusion. This allows quick identification of in-vehicle network intrusions with a low false-positive rate of 0.055%. Unlike state-of-the-art IDSs, if an attack is detected, CIDS's fingerprinting of ECUs also facilitates a rootcause analysis; identifying which ECU mounted the attack. Our experiments on a CAN bus prototype and on real vehicles have shown CIDS to be able to detect a wide range of in-vehicle network attacks.
412 citations
References
More filters
01 Jul 2003
TL;DR: RTP provides end-to-end network transport functions suitable for applications transmitting real-time data over multicast or unicast network services and is augmented by a control protocol (RTCP) to allow monitoring of the data delivery in a manner scalable to large multicast networks.
Abstract: This memorandum describes RTP, the real-time transport protocol. RTP provides end-to-end network transport functions suitable for applications transmitting real-time data, such as audio, video or simulation data, over multicast or unicast network services. RTP does not address resource reservation and does not guarantee quality-of-service for real-time services. The data transport is augmented by a control protocol (RTCP) to allow monitoring of the data delivery in a manner scalable to large multicast networks, and to provide minimal control and identification functionality. RTP and RTCP are designed to be independent of the underlying transport and network layers. The protocol supports the use of RTP-level translators and mixers.
7,183 citations
Book•
01 Jan 1983
TL;DR: Estimators of Location: An Outline of the Theory (C. Goodall).
Abstract: Stem-and-Leaf Displays (J. Emerson & D. Hoaglin). Letter Values: A Set of Selected Order Statistics (D. Hoaglin). Boxplots and Batch Comparison (J. Emerson & J. Strenio). Transforming Data (J. Emerson & M. Stoto). Resistant Lines for y Versus x (J. Emerson & D. Hoaglin). Analysis of Two-Way Tables by Medians (J. Emerson & D. Hoaglin). Examining Residuals (C. Goodall). Mathematical Aspects of Transformation (J. Emerson). Introduction to More Refined Estimators (D. Hoaglin, et al.). Comparing Location Estimators: Trimmed Means, Medians, and Trimean (J. Rosenberger & M. Gasko). M-Estimators of Location: An Outline of the Theory (C. Goodall). Robust Scale Estimators and Confidence Intervals for Location (B. Iglewicz). Index.
2,179 citations
01 Dec 1995
TL;DR: In this paper, the authors specify version 6 of the Internet Protocol (IPv6), also referred to as IP Next Generation or IPng, and propose a new protocol called IPng.
Abstract: This document specifies version 6 of the Internet Protocol (IPv6), also sometimes referred to as IP Next Generation or IPng.
2,112 citations
01 Jan 1998
TL;DR: This document specifies version 6 of the Internet Protocol (IPv6), also sometimes referred to as IP Next Generation or IPng.
1,886 citations
01 Mar 1992
TL;DR: This document describes the Network Time Protocol (NTP), specifies its formal structure and summarizes information useful for its implementation and describes the methods used for their implementation.
Abstract: This document describes the Network Time Protocol (NTP), specifies its
formal structure and summarizes information useful for its
implementation. [STANDARDS-TRACK]
1,057 citations