.png){kind=icon}
Return
SSMA: simplified slime mould algorithm for optimization wireless sensor network coverage problem
.png){kind=icon}
OA
AI
DOI：10.1080/21642583.2022.2084650.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Wireless sensor network (WSN) coverage problem is to think about how to maximize the network coverage to obtain reliable monitoring and tracking services with guaranteed quality of service. In this paper, a simplified slime mould algorithm (SSMA) for solving the WSN coverage problem is proposed. In SSMA, we mainly conducted 13 groups of WSNs coverage optimization experiments and compared them with six well-known meta-heuristic optimization algorithms. The experimental results and Wilcoxon rank-sum test show that the proposed SSMA is generally competitive, outstanding performance and effectiveness. We proposed SSMA algorithm could be helpful to effectively control the network nodes energy, improve the perceived quality of services and extend the network survival time.
Keywords:
Wireless sensor network (WSN)
simplified slime mould algorithm (SSMA)
effective coverage rate
meta-heuristic optimization algorithm
Journal
IF:
4.4
Papers:
486
Citations:
2.1K
Organization
Cited Papers
Endotoxin, cytokines, and endotoxin binding proteins in obstructive jaundice and after preoperative biliary drainage.png)
Gut
OAAI
GutIF0
OAAIShareSaveShareSaveA novel adaptive sequential niche technique for multimodal function optimizationNEUROCOMPUTING
NEUROCOMPUTINGIF6.5
PREAI
ShareSaveShape recognition based on neural networks trained by differential evolution algorithmNEUROCOMPUTING
NEUROCOMPUTINGIF6.5
PREAI
ShareSaveConnected Coverage Optimization for Sensor Scheduling in Wireless Sensor NetworksIEEE SENSORS JOURNAL
IEEE SENSORS JOURNALIF4.5
PREAI
ShareSave
View more