Wireless sensor network routing method based on improved ant colony algorithm

2018 ◽  
Vol 10 (3) ◽  
pp. 991-998 ◽  
Author(s):  
Zongfeng Zou ◽  
Ying Qian
2014 ◽  
Vol 685 ◽  
pp. 583-586
Author(s):  
Tian Jun Lu ◽  
Yue Wang

This paper discusses the relevant theoretical problems of ant colony algorithm, analyzes the defects of the traditional ant colony algorithm, and proposed an improved ant colony algorithm to solve these problems. Wireless sensor network routing should satisfy both to ensure data transmission and reduce the amount of communication requirements. The paper presents development of routing protocol for wireless sensor network based on improved ant colony algorithm technology. The simulation results show the effectiveness of this algorithm.


2013 ◽  
Vol 397-400 ◽  
pp. 1117-1120
Author(s):  
Hai Yang

As a new method of obtaining information and disposal pattern, wireless sensor network has been a hot issue nowadays. In this paper the network model and energy consumption model of wireless sensor network are introduced firstly. The improved inspiring factor takes energy into account. Then a parallel ant colony algorithm based on award-punishment mechanism is proposed. The experimental results show that the energy consumption and time delay of the improved algorithm are superior to energy efficient ant based routing and basic ant colony algorithm.


2017 ◽  
Vol 13 (05) ◽  
pp. 174 ◽  
Author(s):  
Liping LV

<p class="0abstract"><span lang="EN-US">In order to make the energy consumption of network nodes relatively balanced, we apply ant colony optimization algorithm to wireless sensor network routing and improve it.</span><span lang="EN-US"> In this paper, we propose a multi-path wireless sensor network routing algorithm based on energy equalization. The algorithm uses forward ants to find the path from the source node to the destination node, and uses backward ants to update the pheromone on the path. In the route selection, we use the energy of the neighboring nodes as the parameter of the heuristic function. At the same time, we construct the fitness function, and take the path length and the node residual energy as its parameters. The simulation results show that the algorithm can not only avoid the problem of local optimal solution, but also prolong the life cycle of the network effectively.</span></p>


2016 ◽  
Vol 12 (10) ◽  
pp. 86 ◽  
Author(s):  
Jingyi Bo ◽  
Yubin Wang ◽  
Na Xu

<span style="font-family: 'Times New Roman',serif; font-size: 10pt; -ms-layout-grid-mode: line; mso-fareast-font-family: SimSun; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;">Combining the characteristics of wireless sensor network, the ant colony algorithm is applied to a wireless sensor network, and a wireless sensor network route algorithm based on energy equilibrium is proposed in this paper. This algorithm takes the energy factor into the consideration of selection of route based on probability and enhanced calculation of information so as to find out the optimal route from the source node to the target node with low cost and balanced energy, and it prolongs the life cycle of the whole network</span><span style="font-family: 'Times New Roman',serif; font-size: 10pt; mso-fareast-font-family: SimSun; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;">.</span>


2014 ◽  
Vol 587-589 ◽  
pp. 2339-2345
Author(s):  
Jia Yan Li ◽  
Jun Ping Wang

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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