Abstract
Since the existing methods cannot evaluate the time delay of different layers of sensor networks, there are some problems such as the low precision of clock error compensation, high time delay, and low efficiency of communication in sensor networks. To solve this problem, a method of clock error compensation in sensor networks based on a cyclic symmetry algorithm is proposed. Based on the basic theory of cyclic symmetry, the cyclic symmetry matrix of the sensor network is constructed; in the communication process, all nodes are extended to get the cumulative delay rate of the sensor network in the specified time domain. Using the cumulative delay rate of the cyclic network and the sensor network, the autoregressive integral sliding mode control model is established to compensate for the cumulative error of clock synchronization. The simulation results show that the compensation accuracy of this method is more than 98%, which can effectively reduce the delay of sensor network. It improves the communication efficiency of the sensor network, meets the communication requirements of the sensor network, and has a very broad application prospect.
Highlights
Due to the shrinking size of hardware devices and the rapid development of software computing speed, wireless sensor networks are put into use
In order to verify the effectiveness of this method in compensating for the clock error of sensor networks, a simulation experiment is carried out
The compensation of the clock error in the sensor network can provide a standard time for the wireless sensor network to refer to, which provides the basic premise for real-time interaction and the collaborative processing of sensor node information and the scheduling of network time
Summary
Due to the shrinking size of hardware devices and the rapid development of software computing speed, wireless sensor networks are put into use. Wireless sensor network applications cover many fields such as public safety, security intensification, health monitoring, intelligent transportation, environmental monitoring, battlefield reconnaissance, target tracking, and emergency location and navigation of fire scenes [2]. Wireless sensor networks can be used to monitor conflict zones, reconnaissance local terrain and arming, and detect nuclear, biological, and chemical attacks or hazardous materials. It can monitor enemy movements, monitor enemy forces and equipment, locate and track targets, and provide a basis for decision-making [4]. In the field of smart grids, wireless sensor networks store and correlate electricity information, provide power-saving feedback services, form an efficient and environmentally-friendly
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