Optimal clock synchronization in networks

Lenzen, Christoph; Sommer, Philipp; Wattenhofer, Roger

doi:10.1145/1644038.1644061

Cited by 160 publications

(149 citation statements)

References 29 publications

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“…However, unlike the drift offset which can be measured with bounded error uncertainty [7][20], instant skew estimation is challenging for its dynamic nature [14] [35]. This section presents an instant skew estimator working with the 0-bit drift detection scheme briefed in the overview section.…”

Section: B Drift Detection and Skew Estimationmentioning

confidence: 99%

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PSR: Practical synchronous rendezvous in low-duty-cycle wireless networks

Huang

Yun

Zhong

et al. 2013

2013 Proceedings IEEE INFOCOM

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Abstract-Low-duty-cycle radio operations have been proposed for wireless networks facing severe energy constraints. Despite energy savings, duty-cycling the radio creates transient-available wireless links, making communication rendezvous a challenging task under the practical issue of clock drift. To overcome limitations of prior work, this paper presents PSR, a practical design for synchronous rendezvous in low-duty-cycle wireless networks. The key idea behind PSR is to extract timing information naturally embedded in the pattern of radio duty-cycling, so that normal traffic in the network can be utilized as a "free" input for drift detection, which helps reduce (or even eliminate) the overhead of traditional time-stamp exchange with dedicated packets or bits. To prevent an overuse of such free information, leading to energy waste, an energy-driven adaptive mechanism is developed for clock calibration to balance between energy efficiency and rendezvous accuracy. PSR is evaluated with both test-bed experiments and extensive simulations, by augmenting and comparing with four different MAC protocols. Results show that PSR is practical and effective under different levels of traffic load, and can be fused with those MAC protocols to improve their energy efficiency without major change of the original designs. I. INTRODUCTIONIn wireless networks with severe energy constraints, e.g., wireless sensor networks [1], low-duty-cycle radio operations have been proposed as one of the major techniques to elongate the network lifetime [5], since the radio can be a main source of energy consumption [13]. Basically, the RF module of a node stays active only for a small percentage of time during each duty-cycle period (e.g., 1%), while keeps in low-energy sleep/off mode for the rest of the time [5][28]. Low-duty-cycle radio activity has been favorable in applications such as environment monitoring (e.g., Redwood [3], GreenOrbs [9]), animal observation (e.g., Great Duck Island [10]), civil structure surveillance (e.g., Mine [11]), etc. In all those applications, low-duty-cycle networking provides a nice trade-off between service quality and energy cost; however, it also brings about transient-available radio links that are essentially at odd with highly efficient communication. This is because in low-dutycycle networks, two nodes located within each other's radio range can communicate only when both of them are active simultaneously for transmitting (TX) and receiving (RX) [12]. A problem called communication rendezvous [17].Many smart ideas have been proposed for the rendezvous task in low-duty-cycle wireless networks. They usually function at the MAC layer and can be categorized into two general classes: (i) asynchronous [5]

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Section: B Drift Detection and Skew Estimationmentioning

confidence: 99%

“…We consider the additive results of all delays and noise as a random variable following the normal distribution based on the central limit theorem [37] and empirical results [7][20]. With delay adjustments, time detections in Fig.7 can be written aŝ…”

Section: B Drift Detection and Skew Estimationmentioning

confidence: 99%

PSR: Practical synchronous rendezvous in low-duty-cycle wireless networks

Huang

Yun

Zhong

et al. 2013

2013 Proceedings IEEE INFOCOM

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“…One of the most notable factors contributing to the hardware clock drift is temperature. In Lenzen et al (2009), the hardware clock frequency of a Mica2 node for different ambient temperature is up to one microsecond per second when the temperature of the environment changes no more than 5°. Therefore, the temperature-based drift model can be give as depicted in Huang et al (2014) as follows:…”

Section: Error Analysismentioning

confidence: 99%

Extensible time synchronisation protocol for wireless sensor networks

Wang

et al. 2017

IJSNET

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Abstract:One important aspect in many applications of wireless sensor networks (WSNs) is time synchronisation. There are still some problems to be solved for time synchronisation, such as error and imbalance of time synchronisation precision, causing the fluctuations among nodes' time and being even worse for those with a larger number of hops, producing unstable communication links for the network. In this paper, we introduce an extensible time synchronisation protocol (ETSP) for WSNs and nodes get synchronised through time stamps from the root node directly or indirectly. We improve the least square method for linear regression to get better performance of time drift and spread the time information from the root node to the whole network. The proposed method reduces fluctuations in terms of time among nodes especially for the nodes far from the root, enhancing stability in large-scale networks. Simulation and experimental results show good performance of our method. 30F. Wang et al.

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“…This problem is known as the broadcast problem in wireless networks and has been studied extensively in the literature. For the sake of brevity, we keep the discussion concise and refer to [19] for additional details.…”

Section: Mac Layer Timestampingmentioning

confidence: 99%

PulseSync: An Efficient and Scalable Clock Synchronization Protocol

Lenzen

Sommer

Wattenhofer

2015

IEEE/ACM Trans. Networking

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105

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Abstract-Clock synchronization is an enabling service for a wide range of applications and protocols in both wired and wireless networks. We study the implications of clock drift and communication latency on the accuracy of clock synchronization when scaling the network diameter. Starting with a theoretical analysis of synchronization protocols, we prove tight bounds on the synchronization error in a model that assumes independently and randomly distributed communication delays and slowly changing drifts. While this model is more optimistic than traditional worst-case analysis, it much better captures the nature of real-world systems such as wireless networks.The bound on the synchronization accuracy, which is roughly the square-root of the network diameter, is achieved by the novel PulseSync protocol. Extensive experiments demonstrate that PulseSync is able to meet the predictions from theory and tightly synchronizes large networks. This contrasts against an exponential growth of the skew incurred by the state-of-the-art protocol for wireless sensor networks. Moreover, PulseSync adapts much faster to network dynamics and changing clock drifts than this protocol.

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Optimal clock synchronization in networks

Cited by 160 publications

References 29 publications

PSR: Practical synchronous rendezvous in low-duty-cycle wireless networks

PSR: Practical synchronous rendezvous in low-duty-cycle wireless networks

Extensible time synchronisation protocol for wireless sensor networks

PulseSync: An Efficient and Scalable Clock Synchronization Protocol

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