Abstract:Precise timing over timestamped packet exchange communication is an enabling technology in the mission-critical industrial Internet of Things, particularly when satellite-based timing is unavailable. The main challenge is to ensure timing accuracy when the clock synchronisation system is subject to disturbances caused by the drifting frequency, time-varying delay, jitter, and timestamping uncertainty. In this work, a Robust Packet-Coupled Oscillators (R-PkCOs) protocol is proposed to reduce the effects of pert… Show more
“…Even though the standard deviation of MAC-level timestamp accuracy is around 1 µs [16], within the progress of sending and receiving a packet, the use of two timestamps for calculating clock offset 1 still lets the one-way synchronisation protocol [on the high-frequency (e.g. 32.768 MHz) embedded clock] suffer from the timestamp accuracy.…”
Section: A Related Workmentioning
confidence: 99%
“…no varying and low-resolution correction value) limits synchronisation performance [12], [23]. Hence, a Proportional (P) controller [16] is utilised to solve the above issue. In [21], the moving average solution is adopted for clock skew estimation, and a Proportional-Integral (PI) controller is used in [12] for eliminating the impacts of drifting clock skew.…”
Section: A Related Workmentioning
confidence: 99%
“…Hence, we use a dynamic controller (which is an advanced version of the PI controller and moving average methods) to adjust both the clock offset and skew, thereby extending previous works (i.e. [16], [24], [25]). This recursive controlling strategy possesses the features of compensating for the impacts of drifting clock frequency, and naturally removing the effects of varying processing delay.…”
Section: A Related Workmentioning
confidence: 99%
“…of the PI controller and moving average solutions) are determined empirically [12], [21]. In [16], the H ∞ method is used to design the P controller parameters in a pairwise network. Nevertheless, this work utilises the H ∞ solution for networked dynamic controller parameters' selection.…”
Section: A Related Workmentioning
confidence: 99%
“…In practice, as a result of the manufacturing tolerance and operating temperatures, P i [n] of the i-th regular node cannot be equal to P 0 [n]. Based on [16], P i [n] is given by…”
Owing to its unique, concealment and easy customisation by combining different wrist and hand gestures, High-Density surface electromyogram (HD-sEMG) is recognised as a potential solution to the next generation biometric authentication, which usually adopts a wireless Body Sensor Network (BSN) to acquire the multi-channel HD-sEMG biosignals from distributed electrode arrays. For more accurate and reliable classification, biometric authentication requires the distributed biosignals to be sampled simultaneously and be well-aligned, which means that the sampling jitters among the arrays need to be tiny. To synchronise data sampling clocks of a cluster of BSN nodes for biometric authentication, this paper modifies the Packet-Coupled Oscillators protocol by using a Dynamic controller (D-PkCOs). This protocol only involves one-way single packet exchange, which reduces the communication overhead significantly. For the purpose of maintaining precise sampling of these BSN nodes subject to drifting clock frequency and varying delays, the dynamic controller is designed via the H∞ robust method, and it is proved that all the BSN nodes' sampling jitters are bounded. The experimental results demonstrate that the D-PkCOs protocol can keep the sampling jitters less than a microsecond in a 10node IEEE 802.15.4 network. The application of D-PkCOs to the BSN shows that the HD-sEMG signal with a high signalto-noise ratio is obtained, which leads to better gesture classification performance.
“…Even though the standard deviation of MAC-level timestamp accuracy is around 1 µs [16], within the progress of sending and receiving a packet, the use of two timestamps for calculating clock offset 1 still lets the one-way synchronisation protocol [on the high-frequency (e.g. 32.768 MHz) embedded clock] suffer from the timestamp accuracy.…”
Section: A Related Workmentioning
confidence: 99%
“…no varying and low-resolution correction value) limits synchronisation performance [12], [23]. Hence, a Proportional (P) controller [16] is utilised to solve the above issue. In [21], the moving average solution is adopted for clock skew estimation, and a Proportional-Integral (PI) controller is used in [12] for eliminating the impacts of drifting clock skew.…”
Section: A Related Workmentioning
confidence: 99%
“…Hence, we use a dynamic controller (which is an advanced version of the PI controller and moving average methods) to adjust both the clock offset and skew, thereby extending previous works (i.e. [16], [24], [25]). This recursive controlling strategy possesses the features of compensating for the impacts of drifting clock frequency, and naturally removing the effects of varying processing delay.…”
Section: A Related Workmentioning
confidence: 99%
“…of the PI controller and moving average solutions) are determined empirically [12], [21]. In [16], the H ∞ method is used to design the P controller parameters in a pairwise network. Nevertheless, this work utilises the H ∞ solution for networked dynamic controller parameters' selection.…”
Section: A Related Workmentioning
confidence: 99%
“…In practice, as a result of the manufacturing tolerance and operating temperatures, P i [n] of the i-th regular node cannot be equal to P 0 [n]. Based on [16], P i [n] is given by…”
Owing to its unique, concealment and easy customisation by combining different wrist and hand gestures, High-Density surface electromyogram (HD-sEMG) is recognised as a potential solution to the next generation biometric authentication, which usually adopts a wireless Body Sensor Network (BSN) to acquire the multi-channel HD-sEMG biosignals from distributed electrode arrays. For more accurate and reliable classification, biometric authentication requires the distributed biosignals to be sampled simultaneously and be well-aligned, which means that the sampling jitters among the arrays need to be tiny. To synchronise data sampling clocks of a cluster of BSN nodes for biometric authentication, this paper modifies the Packet-Coupled Oscillators protocol by using a Dynamic controller (D-PkCOs). This protocol only involves one-way single packet exchange, which reduces the communication overhead significantly. For the purpose of maintaining precise sampling of these BSN nodes subject to drifting clock frequency and varying delays, the dynamic controller is designed via the H∞ robust method, and it is proved that all the BSN nodes' sampling jitters are bounded. The experimental results demonstrate that the D-PkCOs protocol can keep the sampling jitters less than a microsecond in a 10node IEEE 802.15.4 network. The application of D-PkCOs to the BSN shows that the HD-sEMG signal with a high signalto-noise ratio is obtained, which leads to better gesture classification performance.
Precise timing plays a key role in the time‐sensitive industrial Internet of Things (IIoT). However, precise time synchronization requires more frequent packet exchange, which consumes more communication bandwidth and energy. This is a particular challenge in battery‐powered wireless nodes, and low communication costs have become an important factor in clock synchronization. To address the challenge of achieving low communication cost clock synchronization in distributed wireless sensor networks, this paper proposes an improved event‐triggered control and synchronization scheme with a novel asynchronous broadcast packet exchange protocol. Unlike the traditional event‐triggered control scheme which is based on synchronous polling packet exchange, this proposed asynchronous broadcast packet exchange is more communication efficient and requires fewer number of packet exchanges. And it is worth noting that the proposed algorithm in this paper is a distributed algorithm and does not require real‐time acquisition of information from neighbouring nodes. Finally, a numerical example is given to illustrate the effectiveness of the proposed event‐triggered control strategy. The efficiency and precision of the proposed clock synchronization method is evaluated by intensive simulations, which show that the number of packet exchange is reduced by 60% for a moderate IIoT network and is particularly useful for large scale network.
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