The Dynamic Optimization Strategy Research of Wireless Sensor Network Based on Multi-populations Cultural Framework

2013 ◽  
Vol 5 (4) ◽  
pp. 393-404
Author(s):  
RUAN Dianxu ◽  
ZHANG Xiaoguang
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Dynamic Optimization ◽  
Wireless Sensor ◽  
Optimization Strategy ◽  
Strategy Research ◽  
Cultural Framework

Wireless Sensor Network Routing Optimization Based on Improved Shuffled Frog Leaping Algorithm

2014 ◽  
Vol 681 ◽  
pp. 253-257
Author(s):  
Yong Chun Ma ◽  
Hua Gang Shao
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Network Routing ◽  
Route Optimization ◽  
Path Optimization ◽  
Wireless Sensor ◽  
Local Optimum ◽  
Optimization Strategy ◽  
Shuffled Frog Leaping Algorithm ◽  
Shuffled Frog Leaping

Against path optimization problem for wireless sensor network, this paper proposes a path optimization strategy for wireless sensor network based on improved shuffled frog leaping algorithm. The shuffled frog leaping algorithm was used as wireless sensor network path optimization main frame, gauss mutation and opposition-based learning were used to overcome the defects of easily trapping into local optimum and low accuracy computation. Simulation results show that the route optimization mechanism can effectively prolongs the network lifetime,reduces energy consumption, and improves the overall network performance.

Algorithm for Wireless Sensor Network Data Fusion Based on Radial Basis Function Neural Networks

2014 ◽  
Vol 577 ◽  
pp. 873-878 ◽  
Author(s):  
Zi Yang ◽  
Ming Rui Chen ◽  
Wei Wu
Keyword(s):  
Neural Networks ◽  
Wireless Sensor Network ◽  
Data Fusion ◽  
Radial Basis Function ◽  
Sensor Network ◽  
Basis Function ◽  
Wireless Sensor ◽  
Optimization Strategy ◽  
Radial Basis ◽  
Neural Networks Optimization

This paper presents a data fusion method on wireless sensor network based on radial basis function neural networks. In consideration of the hierarchical relationship topology wireless sensor networks, data acquisition, handling and delivery, we proposed a typical classification approach based on radial basis function neural networks. Optimization strategy adopted to process node data for each node indicated different reaction related with energy consumption. Simulation results verify that the method converges fast and effectively.

scholarly journals Coverage Optimization Strategy for WSN based on Energy-aware

2016 ◽  
Vol 11 (6) ◽  
pp. 877 ◽  
Author(s):  
Li Zhu ◽  
Chunxiao Fan ◽  
Zhigang Wen ◽  
Huarun Wu
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Path Loss ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Optimization Strategy ◽  
Network Coverage ◽  
Energy Aware ◽  
Coverage Optimization

In order to optimize the wireless sensor network coverage, this paper designs a coverage optimization strategy for wireless sensor network (EACS) based on energy-aware. Under the assumption that the geographic positions of sensor nodes are available, the proposed strategy consists of energy-aware and network coverage adjustment. It is restricted to conditions such as path loss, residual capacity and monitored area and according to awareness ability of sensors, it would adjust the monitored area, repair network hole and kick out the redundant coverage. The purpose is to balance the energy distribution of working nodes, reduce the number of “dead” nodes and balance network energy consumption. As a result, the network lifetime is expanded. Simulation results show that: EACS effectively reduces the number of working nodes, improves network coverage, lowers network energy consumption while ensuring the wireless sensor network coverage and connectivity, so as to balance network energy consumption.

Research of Energy Optimization Strategy for WSN

2015 ◽  
Vol 740 ◽  
pp. 843-846
Author(s):  
Zhan Gao ◽  
Lin Mao Huang
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Power Supply ◽  
Transmission Loss ◽  
Energy Optimization ◽  
Wireless Sensor ◽  
Optimization Strategy ◽  
Data Loss ◽  
Collection Data

The energy of the nodes in wireless sensor network is very limited. Power supply module power supply, not only need to give themselves also need to collect data of the sensor power supply, monitoring data sending and receiving, processing, also need to consume energy. If the node due to run out of battery and enter a state of "death", can cause the node collection data loss; If the node is terminal nodes, only this node data loss; But if the node is routing nodes, not only can cause data loss of this node, also can cause by all nodes of the node for data transmission loss of data. So, the question of energy consumption becomes a research focus in the field. Through the architecture of wireless sensor network and the analysis of the wireless sensor network protocol stack, according to the characteristics of the wireless sensor network (WSN) and energy optimization strategy of background points out the necessity of energy optimization. By analyzing the energy consumption of wireless sensor network, the wireless sensor network energy optimization strategy is given.

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