Clock Synchronization of Wireless Sensor Networks

Wu, Yik-Chung; Chaudhari, Qasim M.; Serpedin, Erchin

doi:10.1109/msp.2010.938757

Cited by 554 publications

(355 citation statements)

References 36 publications

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“…The worst case synchronization error of TPSN is about 45.2 µs at 4 MHz clock [6]. But a typical quartz crystal sourced clock varies by 40 ppm [7]. Thus two quartz crystal sourced clocks can drift by 40 µs in 1 s i.e.…”

Section: Methodsologymentioning

confidence: 99%

A Time Synchronized Wireless Sensor Tree Network using SimpliciTI

Singh¹,

Chandrachoodan²,

Prabhakar³

2013

IJCCE

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Abstract-SimpliciTI TM is a low power radio frequency protocol from Texas Instruments (TI), which supports peer to peer and star topologies. The system uses Access point (AP) as data hubs, and end devices (ED) to realize the sensor functionality. APs need to be always ON to ensure they can respond to join requests from new EDs and collect data from existing EDs in the network. This is not practical with long-running battery operated APs. We can reduce the energy requirements in the network by putting APs to sleep, but this requires careful synchronization so that the APs will be ready to receive data when the EDs transmit. We implement a time synchronization algorithm to ensure that APs are awake whenever an ED sends data. We also propose a simpliciTI based tree topology where one ED (named PCED, personal computer end device) is made common to the network of multiple APs and now PCED acts as the data hub. To manage the data traffic at the PCED we implement time division multiplexing along with store and forward function on EDs and APs.Index Terms-Star and tree topology, time division multiplexing in wireless sensor networks, time synchronization in SimplicTI, wireless sensor networks. I. INTRODUCTIONSimpliciTI, a radio frequency (RF) protocol by TI, is used to setup wireless sensor networks [1]. It is suitable for battery operated devices working at low data rates of up to 250 kbps [2]. It supports peer to peer and star topologies [2]. The basic device types available in the protocol are access point (AP), range extender (RE) & end device (ED) [2]. A. End Device D. SimpliciTI ArchitectureIt has three layers as shown in Fig. 1, the minimal RF interface layer (MRFI), the network layer and the application layer. The transceiver frames the data and thus functions as the physical and data link layer. SimpliciTI has a set of application programmable interfaces (APIs) at the application layer which allow the user to setup bidirectional links, send messages from one device to another etc [4]. The application layer is blind to the transceiver and network configurations. All this makes it very easy for the user to setup a network and modify its operation according to the application. The supported frequencies are 480, 868, 915, 955 MHz and 2.4 GHz [2].The protocol runs on Texas Instruments' ultra-low power microcontrollers (µC) and transceivers. One such device is the eZ430-RF2500. It is shown in Fig. 2. It has a MSP430F2274 µC interfaced to the CC2500, RF transceiver (TxRx, 2.4 GHz), through a serial peripheral interface (SPI) [3]. Both the µC and transceiver have sleep modes which reduce power consumption.TI describes a "wireless sensor monitor" application using the eZ430-RF2500 [1]. The application uses the SimpliciTI based star topology to setup the network as shown in Fig. 3. In the application the EDs act as the sensor terminals (field devices) and send the battery voltages and temperature readings to the AP and go to sleep. AP sends this data to the PC com port over universal asynchronous receiver transmitter (...

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Section: Methodsologymentioning

confidence: 99%

A Time Synchronized Wireless Sensor Tree Network using SimpliciTI

Singh¹,

Chandrachoodan²,

Prabhakar³

2013

IJCCE

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“…Wu et al in [4] proposed an approach which uses time stamps for receiver synchronization. Even though it is quite simple, it does not suit our problem because we would need specialized hardware for it.…”

Section: Review Of Current Approaches In A/d Converter Synchronizmentioning

confidence: 99%

Investigation of electric network frequency for synchronization of low cost and wireless sound cards

Golokolenko

Schuller

2017

2017 25th European Signal Processing Conference (EUSIPCO)

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Abstract-An electric network frequency (ENF) signal can be found in multimedia recordings due to propagation from the power grid. There a variety of applications based on ENF signal use, such as video and audio stream synchronization, and origin determination of multimedia recordings. In this paper, we propose the use of ENF to synchronize real-time audio streams from different, non-synchronized sound devices, for instance from wireless sound cards or low cost USB sound cards. Synchronization of separate audio streams can be achieved by aligning their embedded ENF signals. Our goal is to find out how accurate a synchronization using ENF at different SNR levels can be. We show simulation and real-time experimental results of audio stream synchronization. We found that with sufficient ENF level we can achieve an accuracy of the estimated delay difference of four samples at 44.1 kHz sampling rate.

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“…In order to perform clock synchronization and ranging, the pairwise exchange of time stamps is applied across the network [7]. If (i, j) ∈ C, node i transmits Kij ≥ 1 packets to node j and receives Kji ≥ 1 packets from node j.…”

Section: System Modelmentioning

confidence: 99%

“…Clock synchronization can be seen as the key to achieving a shared notion of time. Considering that neighboring nodes of a WN share timing information by a two-way packet exchange mechanism [7], a relationship exists between the line-ofsight propagation delay of packets and internode distances.…”

Section: Introductionmentioning

confidence: 99%

Distributed clock synchronization and ranging in time-variant wireless networks

Bartel

Etzlinger

Springer

2014

2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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Clock synchronization and ranging are important topics in the field of wireless networks, where internode time measurement allows both tasks to be completed in one. Such networks are generally time-variant due to possible changes in environmental conditions and mobility of network nodes. We present a fully distributed filtering algorithm for combined clock synchronization and ranging based on message passing by belief propagation on a factor graph representation of a time-variant wireless network. The resulting message passing equations can be interpreted as a variant of Kalman filtering locally on each network node. Simulation results show that tracking estimation parameters improves estimation accuracy significantly without additional communication effort.

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Clock Synchronization of Wireless Sensor Networks

Cited by 554 publications

References 36 publications

A Time Synchronized Wireless Sensor Tree Network using SimpliciTI

A Time Synchronized Wireless Sensor Tree Network using SimpliciTI

Investigation of electric network frequency for synchronization of low cost and wireless sound cards

Distributed clock synchronization and ranging in time-variant wireless networks

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