2019
DOI: 10.1109/access.2019.2960299
|View full text |Cite
|
Sign up to set email alerts
|

RSS-Based Coverage Deployment Method Under Probability Model in 3D-WSN

Abstract: Due to the wider application of wireless sensor networks in real life, 3D coverage closer to the actual application environment has become a research hotspot of current sensor networks. To this end, this paper proposes a three-dimensional coverage deployment method based on RSS (Received Signal Strength) under a probabilistic model. According to the path loss of the wireless signal in the propagation process, the distance between the nodes can be roughly calculated, and the maximum distance between the nodes i… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
4
0

Year Published

2021
2021
2024
2024

Publication Types

Select...
7
1

Relationship

1
7

Authors

Journals

citations
Cited by 12 publications
(6 citation statements)
references
References 42 publications
0
4
0
Order By: Relevance
“…About 35% of the reviewed studies worked on an update to swarm intelligence optimization algorithms [ 40 , 44 , 46 ] such as particle swarm optimization (PSO) [ 42 , 58 , 66 , 68 , 69 , 74 , 75 , 76 , 77 , 81 , 88 , 97 , 99 ], ant colony optimization (ACO) [ 33 ], and bee colony optimization (BCO) [ 48 , 65 ], due to their ability to solve complex problems and provide a satisfactory solution in a feasible time [ 90 ]. These algorithms are applied to enhance network performance by combining them with other approaches and then comparing the obtained results with other algorithms, such as the genetic, greedy, and multi-objective evolutionary algorithms.…”
Section: Resultsmentioning
confidence: 99%
See 2 more Smart Citations
“…About 35% of the reviewed studies worked on an update to swarm intelligence optimization algorithms [ 40 , 44 , 46 ] such as particle swarm optimization (PSO) [ 42 , 58 , 66 , 68 , 69 , 74 , 75 , 76 , 77 , 81 , 88 , 97 , 99 ], ant colony optimization (ACO) [ 33 ], and bee colony optimization (BCO) [ 48 , 65 ], due to their ability to solve complex problems and provide a satisfactory solution in a feasible time [ 90 ]. These algorithms are applied to enhance network performance by combining them with other approaches and then comparing the obtained results with other algorithms, such as the genetic, greedy, and multi-objective evolutionary algorithms.…”
Section: Resultsmentioning
confidence: 99%
“…This metric represents a measure of link quality and depends on the distance between two nodes to calculate the reachability of the node through the communication process. RSSI stands for received signal strength indicator that can be determined from the following equation [ 76 , 105 ]: RSSI = −10 × n × log 10 (d) + p where, d: is the distance from the sensor node measured in meters; n: is the propagation constant or path-loss exponent; p: is the power in reception mode (Dbm) (decibel-milliwatts). …”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…The authors point out that energy hole and coverage hole degrade the performance of UASNs in terms of network throughput and lifetime (Hao et al, 2019). A three-dimensional coverage deployment method is proposed, and the method was based on received signal strength.…”
Section: Node Deployment Optimizationmentioning
confidence: 99%
“…The existence of node selfishness greatly affects the cooperation between all nodes, resulting in uneven energy consumption and shortened life cycle of the network during routing. 8 Therefore, the game theory is introduced to restrain the selfish selection of nodes in the routing process and solve the policy conflicts between nodes, so as to further solve the problem of uneven energy consumption in the network.…”
Section: Introductionmentioning
confidence: 99%