Lattice‐Based 3‐Dimensional Wireless Sensor Deployment

Wang, Zhigang; Tian, Li; Lin, Lianhai; Tong, Yinghua

doi:10.1155/2021/2441122

Cited by 2 publications

(1 citation statement)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…First of all, the deployment method is primarily used under the conditions of a good geographical environment, such as plains, wheat fields, grasslands, and lakes. In [14], sensors are deployed using a regular lattice model that can be full of space, but the actual monitoring environment cannot be an ideal 2D or 3D space. The environment often has flat terrain and is easy to plan and deploy.…”

Section: Wireless Communications and Mobile Computingmentioning

confidence: 99%

A Metaheuristic Algorithm for Coverage Enhancement of Wireless Sensor Networks

Wang

Tian

et al. 2022

Wireless Communications and Mobile Computing

Self Cite

View full text Add to dashboard Cite

When wireless sensors are randomly deployed in natural environments such as ecological monitoring, military monitoring, and disaster monitoring, the initial position of sensors is generally formed through deployment methods such as air-drop, and then, the second deployment is carried out through the existing optimization methods, but these methods will still lead to serious coverage holes. In order to solve this problem, this paper proposes an algorithm to improve the coverage rate for wireless sensor networks based on an improved metaheuristic algorithm. The sensor deployment coverage model was firstly established, and the sensor network coverage problem was transformed into a high-dimensional multimodal function optimization problem. Secondly, the global searching ability and searching range of the algorithm are enhanced by the reverse expansion of the initial populations. Finally, the firefly principle is introduced to reduce the local binding force of sparrows and avoid the local optimization problem of the population in the search process. The experimental results showed that compared with ALO, GWO, BES, RK, and SSA algorithms, the EFSSA algorithm is better than other algorithms in benchmark function tests, especially in the test of high-dimensional multimodal function. In the tests of different monitoring ranges and number of nodes, the coverage of EFSSA algorithm is higher than other algorithms. The result can tell that EFSSA algorithm can effectively enhance the coverage of sensor deployment.

show abstract

Section: Wireless Communications and Mobile Computingmentioning

confidence: 99%