Node Positioning Algorithm in a Wireless Sensor Network

2013 ◽  
Vol 321-324 ◽  
pp. 604-607
Author(s):  
Wei Liu ◽  
Qin Sheng Du ◽  
Le Le Wang
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Wireless Sensor ◽  
Ant Colony Optimization Algorithm ◽  
Positioning Accuracy ◽  
Positioning Method ◽  
Portfolio Optimization Problem ◽  
Dynamic Portfolio Optimization

Node positioning technology in the Wireless sensor network is a very important issue. This article introduces the ant colony algorithm and its characteristics. It is a good solution to the static and dynamic portfolio optimization problem. The node positioning method in the wireless sensor network can be divided into two categories based ranging and no ranging. In order to get a higher positioning accuracy, and a further improvement the positioning accuracy, this paper introduces the ant colony optimization algorithm based on the first positioning method of the feasibility. The experimental results demonstrate the decrease of the number of transmitting beacon and the optimal mobile path after being optimized.

scholarly journals An Improved Ant Colony Algorithm in Wireless Sensor Network Routing

2017 ◽  
Vol 13 (05) ◽  
pp. 174 ◽  
Author(s):  
Liping LV
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Ant Colony Algorithm ◽  
Fitness Function ◽  
Optimal Solution ◽  
Network Routing ◽  
Ant Colony ◽  
Wireless Sensor ◽  
Destination Node ◽  
Ant Colony Optimization Algorithm

<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>

scholarly journals Study of Wireless Sensor Network Route Based on Improved Ant Colony Algorithm

2016 ◽  
Vol 12 (10) ◽  
pp. 86 ◽  
Author(s):  
Jingyi Bo ◽  
Yubin Wang ◽  
Na Xu
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Ant Colony Algorithm ◽  
Low Cost ◽  
Ant Colony ◽  
Wireless Sensor ◽  
Font Size ◽  
Energy Equilibrium ◽  
Route Algorithm ◽  
Selection Of

<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>

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.

Clustering Routing Algorithm Ant Colony Optimization-Based for Wireless Sensor Network

2014 ◽  
Vol 568-570 ◽  
pp. 594-597
Author(s):  
Jun Ye Zhang ◽  
Dong Ya Chen
Keyword(s):  
Wireless Sensor Network ◽  
Ant Colony Optimization ◽  
Sensor Network ◽  
Wireless Channels ◽  
Routing Algorithm ◽  
Ant Colony ◽  
Wireless Sensor ◽  
Ant Colony Optimization Algorithm ◽  
Limited Power ◽  
Dynamic Adaptability

Nodes in wireless sensor network have limited power supply and wireless channels between them are sensitive to interference. In order to make good use of the limited energy, a routing algorithm is proposed which uses the Ant Colony Optimization Algorithm to balance the load of the network and extend the network life, the proposed algorithm utilizes the dynamic adaptability and optimization capabilities of the ant colony to get the optimum route between the cluster heads．Simulation results show the feasibility and effectiveness of this algorithm．

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