Abstract-We consider energy-efficient time synchronization in a wireless sensor network where a head node (i.e., a gateway between wired and wireless networks and a center of data fusion) is equipped with a powerful processor and supplied power from outlet, and sensor nodes (i.e., nodes measuring data and connected only through wireless channels) are limited in processing and battery-powered. It is this asymmetry that our study focuses on; unlike most existing schemes to save the power of all network nodes, we concentrate on battery-powered sensor nodes in minimizing energy consumption for time synchronization. We present a time synchronization scheme based on asynchronous source clock frequency recovery and reverse two-way message exchanges combined with measurement data report messages, where we minimize the number of message transmissions from sensor nodes, and carry out the performance analysis of the estimation of both measurement time and clock frequency with lower bounds for the latter. Simulation results verify that the proposed scheme outperforms the schemes based on conventional two-way message exchanges with and without clock frequency recovery in terms of the accuracy of measurement time estimation and the number of message transmissions and receptions at sensor nodes as an indirect measure of energy efficiency.

The highly parallel artificial neural systems based on transistor-like devices have recently attracted widespread attention due to their high-efficiency computing potential and the ability to mimic biological neurobehavior. For the past decades, plenty of breakthroughs related to synaptic transistors have been investigated and reported. In this work, a kind of photoelectronic transistor that successfully mimics the behaviors of biological synapses has been proposed and systematically analyzed. For the individual device, MXenes and the self-assembled titanium dioxide on the nanosheet surface serve as floating gate and tunneling layers, respectively. As the unit electronics of the neural network, the typical synaptic behaviors and the reliable memory stability of the synaptic transistors have been demonstrated through the voltage test. Furthermore, for the first time, the UV-responsive synaptic properties of the MXenes floating gated transistor and its applications, including conditional reflex and supervised learning, have been measured and realized. These photoelectric synapse characteristics illustrate the great potential of the device in bio-imitation vision applications. Finally, through the simulation based on an artificial neural network algorithm, the device successfully realizes the recognition application of handwritten digital images. Thus, this article provides a highly feasible solution for applying artificial synaptic devices to hardware neuromorphic networks.

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The ever-increasing number of WSN deployments based on a large number of battery-powered, low-cost sensor nodes, which are limited in their computing and power resources, puts the focus of WSN time synchronization research on three major aspects, i.e., accuracy, energy consumption and computational complexity. In the literature, the latter two aspects haven't received much attention compared to the accuracy of WSN time synchronization. Especially in multi-hop WSNs, intermediate gateway nodes are overloaded with tasks for not only relaying messages but also a variety of computations for their offspring nodes as well as themselves. Therefore, not only minimizing the energy consumption but also lowering the computational complexity while maintaining the synchronization accuracy is crucial to the design of time synchronization schemes for resourceconstrained sensor nodes. In this paper, focusing on the three aspects of WSN time synchronization, we introduce a framework of reverse asymmetric time synchronization for resourceconstrained multi-hop WSNs and propose a beaconless energyefficient time synchronization scheme based on reverse oneway message dissemination. Experimental results with a WSN testbed based on TelosB motes running TinyOS demonstrate that the proposed scheme conserves up to 95% energy consumption compared to the flooding time synchronization protocol while achieving microsecond-level synchronization accuracy.

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