Abstract
In the practical application of large-scale photovoltaic module monitoring, adopting wireless sensor network (WSN) technology is a method worth researching. With increasing nodes in the wireless sensor network, widely existing clock skew, increased geometrically, is bringing about greater energy consumption. Due to the random distribution of nodes, in order to improve the transmission efficiency and reduce the computational load of the coordinator, the node processor needs to the use edge computing for preliminary analysis. This paper puts forward an improved energy-efficient reference broadcast synchronization algorithm (ERBS). This algorithm firstly calculates the average phase offset of nonadjacent nodes in the network after receiving a message. It then uses the least square method to solve the clock skew to achieve high-precision synchronization of the whole network. Simulation results show that compared with RBS, the time synchronization precision of ERBS is greatly improved and synchronization times are greatly reduced, decreasing energy consumption significantly.
Highlights
With the development of microelectromechanical system (MEMS), wireless communications, Internet of Things, big data, and AI transforming distributed sensing, edge computing, and communication into wireless sensor nodes at a low cost and low power consumption is becoming the focus of research
While solving the synchronization problem of wireless sensor network (WSN), the accessing time of channels in the media access control (MAC) layer is the biggest source of error, so it is very important to further study the defects in the reference broadcast synchronization (RBS) algorithm and find an improved algorithm
The analysis found that the average synchronization errors of the RBS and efficient reference broadcast synchronization algorithm (ERBS) algorithms are not affected much by n
Summary
With the development of microelectromechanical system (MEMS), wireless communications, Internet of Things, big data, and AI transforming distributed sensing, edge computing, and communication into wireless sensor nodes at a low cost and low power consumption is becoming the focus of research. In order to improve the computational efficiency, Wu et al proposed an online optimization algorithm based on device data analysis, maximizing fairness and throughput balance and using Lyapunov and convex optimization to improve the effectiveness of resource allocation through numerical simulation, aiming at the randomness of wireless mobile edge traffic arrival, the time coupling of uplink and downlink decision-making, and the incompleteness of system state knowledge [10]. The proposed ERBS algorithm can effectively reduce network energy consumption and enhance the reliability of network time synchronization on the basis of ensuring synchronization accuracy. It can be applied in large-scale WSN construction
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