scholarly journals Wireless Sensor Network Route Optimization Based on Improved Ant Colony-Genetic

2015 ◽  
Vol 11 (9) ◽  
pp. 4 ◽  
Author(s):  
Wei Liu ◽  
Yongfeng Cui ◽  
Zhongyuan Zhao

The objective of this paper is focuses on route optimization, for a given wireless sensor network. We detail the significance of route optimization problem and the corresponding mathematical model. After analyzing the complex multi-objective optimization problem, Ant Colony Optimization (ACO) algorithm was introduced to search the best route. Inspired by Genetic Algorithm (GA), we embed two operations into ACO to refine it. First, every ant after achieving sink will be regarded as an individual such as that in GA. The crossover operation will be applied and then, the generated new ants will replace the weaker parents. Second, we designed a mutation operation for ants selecting next nodes to visit. Experimental results demonstrate that the proposed combination algorithm has significant enhancements than both GA and ACO. The lifetime of WSN can be extended and the coverage speed can be accelerated.

2021 ◽  
Author(s):  
Muhammad Iqbal ◽  
Muhammad Naeem ◽  
Alagan Anpalagan ◽  
Ashfaq Ahmed ◽  
Muhammad Azam

Optimization problems relating to wireless sensor network planning, design, deployment and operation often give rise to multi-objective optimization formulations where multiple desirable objectives compete with each other and the decision maker has to select one of the tradeoff solutions. These multiple objectives may or may not conflict with each other. Keeping in view the nature of the application, the sensing scenario and input/output of the problem, the type of optimization problem changes. To address different nature of optimization problems relating to wireless sensor network design, deployment, operation, planning and placement, there exist a plethora of optimization solution types. We review and analyze different desirable objectives to show whether they conflict with each other, support each other or they are design dependent. We also present a generic multi-objective optimization problem relating to wireless sensor network which consists of input variables, required output, objectives and constraints. A list of constraints is also presented to give an overview of different constraints which are considered while formulating the optimization problems in wireless sensor networks. Keeping in view the multi facet coverage of this article relating to multi-objective optimization, this will open up new avenues of research in the area of multi-objective optimization relating to wireless sensor networks.


2021 ◽  
Author(s):  
Muhammad Iqbal ◽  
Muhammad Naeem ◽  
Alagan Anpalagan ◽  
Ashfaq Ahmed ◽  
Muhammad Azam

Optimization problems relating to wireless sensor network planning, design, deployment and operation often give rise to multi-objective optimization formulations where multiple desirable objectives compete with each other and the decision maker has to select one of the tradeoff solutions. These multiple objectives may or may not conflict with each other. Keeping in view the nature of the application, the sensing scenario and input/output of the problem, the type of optimization problem changes. To address different nature of optimization problems relating to wireless sensor network design, deployment, operation, planning and placement, there exist a plethora of optimization solution types. We review and analyze different desirable objectives to show whether they conflict with each other, support each other or they are design dependent. We also present a generic multi-objective optimization problem relating to wireless sensor network which consists of input variables, required output, objectives and constraints. A list of constraints is also presented to give an overview of different constraints which are considered while formulating the optimization problems in wireless sensor networks. Keeping in view the multi facet coverage of this article relating to multi-objective optimization, this will open up new avenues of research in the area of multi-objective optimization relating to wireless sensor networks.


2013 ◽  
Vol 33 (12) ◽  
pp. 3410-3414 ◽  
Author(s):  
Congcong MIAO ◽  
Qingkui CHEN ◽  
Jianwei CAO ◽  
Gang ZHANG

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>


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