Optimization of APTEEN Routing Protocol for Wireless Sensor Networks Based on Genetic Algorithm

2020 ◽  
pp. 712-721
Author(s):  
Minghao Wang ◽  
Shubin Wang ◽  
Bowen Zhang
Keyword(s):  
Genetic Algorithm ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Routing Protocol ◽  
Wireless Sensor

A genetic algorithm based distance-aware routing protocol for wireless sensor networks

2016 ◽  
Vol 56 ◽  
pp. 441-455 ◽  
Author(s):  
Tarunpreet Bhatia ◽  
Simmi Kansal ◽  
Shivani Goel ◽  
A.K. Verma
Keyword(s):  
Genetic Algorithm ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Routing Protocol ◽  
Wireless Sensor

scholarly journals Energy-Efficient and Load-Balanced Clustering Routing Protocol for Wireless Sensor Networks Using a Chaotic Genetic Algorithm

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 158082-158096
Author(s):  
Chuhang Wang ◽  
Xiaoli Liu ◽  
Huangshui Hu ◽  
Youjia Han ◽  
Meiqin Yao
Keyword(s):  
Genetic Algorithm ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Routing Protocol ◽  
Energy Efficient ◽  
Wireless Sensor ◽  
Balanced Clustering ◽  
Load Balanced

An Improved Genetic Algorithm Based Annulus-sector Clustering Routing Protocol for Wireless Sensor Networks

2021 ◽  
Author(s):  
Wang Chu-hang ◽  
Liu Xiao-li ◽  
Youjia Han ◽  
Hu Huang-shui ◽  
Wu Sha-sha
Keyword(s):  
Genetic Algorithm ◽  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Routing Protocol ◽  
Fitness Function ◽  
Minimum Energy ◽  
Wireless Sensor ◽  
Optimal Routing ◽  
Improved Genetic Algorithm

Abstract In wireless sensor networks, uniform cluster formation and optimal routing paths finding are always the two most important factors for clustering routing protocols to minimize the network energy consumption and balance the network load. In this paper, an improved genetic algorithm based annulus-sector clustering routing protocol called GACRP is proposed. In GACRP, the circular network is divided into sectors with the same size for each annulus, whose number is determined by calculating the minimum energy consumption of each annulus. Each annulus-sector forms a cluster and the best node in this annulus-sector is selected as cluster head. Moreover, an improved genetic algorithm with a novel fitness function considering energy and load balance is presented to find the optimal routing path for each CH, and an adaptive round time is calculated for maintaining the clusters. Simulation results show that GACRP can significantly improve the network energy efficiency and prolong the network lifetime as well as mitigate the hot spot problem.

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