Mobile Agent routing algorithm for WSN based on Q learning hybrid with ant colony optimization

2013 ◽  
Vol 33 (9) ◽  
pp. 2440-2443
Author(s):  
Xiaochao DANG ◽  
Haohao YAO ◽  
Zhanjun HAO
Keyword(s):  
Ant Colony Optimization ◽  
Mobile Agent ◽  
Routing Algorithm ◽  
Ant Colony ◽  
Q Learning

scholarly journals Drafs A Routing Algorithm Based On Distributed Food Sources Using Ant Colony Optimization

2014 ◽  
Vol 08 (03) ◽  
pp. 265-281
Author(s):  
Arash Ghorbannia Delavar ◽  
Emetis Niazmand ◽  
Javad Bayrampoor ◽  
Vahe Aghazarian
Keyword(s):  
Ant Colony Optimization ◽  
Routing Algorithm ◽  
Ant Colony ◽  
Food Sources

Wireless Sensor Network Mobile Agent Routing Based on the Improved Ant Colony Algorithm

2014 ◽  
Vol 587-589 ◽  
pp. 2339-2345
Author(s):  
Jia Yan Li ◽  
Jun Ping Wang
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Mobile Agent ◽  
Large Scale ◽  
Ant Colony Algorithm ◽  
Routing Algorithm ◽  
Ant Colony ◽  
Wireless Sensor ◽  
Communication Overhead ◽  
Redundant Data

This paper proposes a new wireless sensor routing algorithm by combining the ant colony algorithm with the mobile agent technology. This algorithm considers the distance and path energy overhead among nodes and residual node energy, equalizes the energy overhead in the network, improves the update rule of the ant colony information elements and speeds up convergence of the ant colony algorithm to get the optimal values. The simulation results indicate that this algorithm can improve the globalization and convergence speed, effectively reduce redundant data transmission and communication overhead, extend the network lifecycle and be very suitable for a large-scale wireless sensor network compared to other mobile agent routing algorithms.

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