Revised beaconing glowworm swarm optimization ant colony optimization algorithm to localize nodes and optimize the energy consumed by nodes in wireless sensor networks

2020 ◽  
Author(s):  
Vandana Reddy ◽  
Gayathri P
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Ant Colony Optimization ◽  
Optimization Algorithm ◽  
Ant Colony ◽  
Wireless Sensor ◽  
Ant Colony Optimization Algorithm ◽  
Swarm Optimization ◽  
Glowworm Swarm Optimization

scholarly journals Low-Energy Secure Routing Protocol for WSNs Based on Multiobjective Ant Colony Optimization Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Xueli Wang
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Ant Colony Optimization ◽  
Optimization Algorithm ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Ant Colony Optimization Algorithm

As one of the three pillars of information technology, wireless sensor networks (WSNs) have been widely used in environmental detection, healthcare, military surveillance, industrial data sampling, and many other fields due to their unparalleled advantages in deployment cost, network power consumption, and versatility. The advent of the 5G standard and the era of Industry 4.0 have brought new opportunities for the development of wireless sensor networks. However, due to the limited power capacity of the sensor nodes themselves, the harsh deployment environment will bring a great difficulty to the energy replenishment of the sensor nodes, so the energy limitation problem has become a major factor limiting its further development; how to improve the energy utilization efficiency of WSNs has become an urgent problem in the scientific and industrial communities. Based on this, this paper researches the routing technology of wireless sensor networks, from the perspective of improving network security, and reducing network energy consumption, based on the study of ant colony optimization algorithm, further studies the node trust evaluation mechanism, and carries out the following research work: (1) study the energy consumption model of wireless sensor networks; (2) basic ant colony algorithm improvement; (3) multiobjective ant colony algorithm based on wireless sensor routing algorithm optimization. In this study, the NS2 network simulator is used as a simulation tool to verify the performance of the research algorithm. Compared with existing routing algorithms, the simulation results show that the multiobjective ant colony optimization algorithm has better performance in evaluation indexes such as life cycle, node energy consumption, node survival time, and stability compared with the traditional algorithm and the dual cluster head ant colony optimization algorithm.

Analysis of Routing Protocols for Wireless Sensor Networks Based on Improved Ant Colony Optimization Algorithm

2014 ◽  
Vol 978 ◽  
pp. 248-251 ◽  
Author(s):  
Shu Min Duan
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Ant Colony Optimization ◽  
Optimization Algorithm ◽  
Routing Protocols ◽  
Ant Colony Algorithm ◽  
Solution Space ◽  
Ant Colony ◽  
Wireless Sensor ◽  
Ant Colony Optimization Algorithm

Wireless sensor networks with node calculation ability is weak, node power (battery provides) Limited, routing algorithm of wireless sensor networks should be the energy saving and simple algorithm. Ant colony algorithm shows good search results in the discrete solution space. This paper improves the ant colony optimization algorithm. The paper presents analysis of routing protocols for wireless sensor networks based on improved ant colony optimization algorithm, and the simulation results verify the effectiveness of the improved algorithm.

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