Node Scheduling Algorithm Based on Grid for Wireless Sensor Networks

Author(s):  
Kun Zhang ◽  
Jing Chen ◽  
Chong Shen ◽  
Yu Chen ◽  
Keliu Long ◽  
...  
2012 ◽  
Vol 4 ◽  
pp. 32-37
Author(s):  
Jin Song Chen

This paper introduces the basics of wireless sensor networks, focusing on the concept of sensor network data collection, data collection mechanisms, data collection in-network data aggregation, data collection and data collection applications Research. This paper presents the data collection in WSN node scheduling concept, analyzed the two data collection in WSN scheduling mechanism, which is based on data collection interval node scheduling mechanism and turn the data based on perceived probability of node sleep scheduling mechanism.


2019 ◽  
Vol 15 (1) ◽  
pp. 155014771982631 ◽  
Author(s):  
Zhangquan Wang ◽  
Yourong Chen ◽  
Banteng Liu ◽  
Haibo Yang ◽  
Ziyi Su ◽  
...  

To improve the regional coverage rate and network lifetime of heterogeneous wireless sensor networks, a sensor node scheduling algorithm for heterogeneous wireless sensor networks is proposed. In sensor node scheduling algorithm, heterogeneous perception radius of sensor node is considered. Incomplete coverage constraint and arc coverage interval are analyzed. Regional coverage increment optimization model, arc coverage increment optimization model, and residual energy optimization model are proposed. Multi-objective scheduling model is established using weight factors and integrated function. Furthermore, the heuristic method is proposed to solve the multi-objective optimization model, and scheduling scheme of heterogeneous sensor nodes is obtained. When the network is in operation for a period of time, some sensor nodes are invalid and relevant regions are uncovered. The repair method is proposed to wake up sleep sensor nodes and repair the coverage blind area. The simulation results show that if keeping the same regional coverage rate, sensor node scheduling algorithm improves network lifetime, increases number of living sensor nodes, and keeps average node energy consumption at a low level. Under certain conditions, sensor node scheduling algorithm outperforms DGREEDY, two-tiered scheduling, and minimum connected cover.


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