Network lifetime maximization for time-sensitive data gathering in wireless sensor networks

2013 ◽  
Vol 57 (5) ◽  
pp. 1063-1077 ◽  
Author(s):  
Feng Shan ◽  
Weifa Liang ◽  
Jun Luo ◽  
Xiaojun Shen
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Data Gathering ◽  
Wireless Sensor ◽  
Sensitive Data ◽  
Lifetime Maximization

Lifetime Maximization Routing Based on Genetic Algorithm for Wireless Sensor Networks

2011 ◽  
Vol 230-232 ◽  
pp. 283-287
Author(s):  
You Rong Chen ◽  
Tiao Juan Ren ◽  
Zhang Quan Wang ◽  
Yi Feng Ping
Keyword(s):  
Genetic Algorithm ◽  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Data Gathering ◽  
Transmission Probability ◽  
Wireless Sensor ◽  
Total Energy Consumption ◽  
Lifetime Maximization

To prolong network lifetime, lifetime maximization routing based on genetic algorithm (GALMR) for wireless sensor networks is proposed. Energy consumption model and node transmission probability are used to calculate the total energy consumption of nodes in a data gathering cycle. Then, lifetime maximization routing is formulated as maximization optimization problem. The select, crosss, and mutation operations in genetic algorithm are used to find the optimal network lifetime and node transmission probability. Simulation results show that GALMR algorithm are convergence and can prolong network lifetime. Under certain conditions, GALMR outperforms PEDAP-PA, LET, Sum-w and Ratio-w algorithms.

scholarly journals Maximizing Lifetime of Wireless Sensor Networks with Mobile Sink Nodes

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Yourong Chen ◽  
Zhangquan Wang ◽  
Tiaojuan Ren ◽  
Yaolin Liu ◽  
Hexin Lv
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Optimization Model ◽  
Data Gathering ◽  
Mobile Sink ◽  
Path Selection ◽  
Wireless Sensor ◽  
Lifetime Optimization

In order to maximize network lifetime and balance energy consumption when sink nodes can move, maximizing lifetime of wireless sensor networks with mobile sink nodes (MLMS) is researched. The movement path selection method of sink nodes is proposed. Modified subtractive clustering method, k-means method, and nearest neighbor interpolation method are used to obtain the movement paths. The lifetime optimization model is established under flow constraint, energy consumption constraint, link transmission constraint, and other constraints. The model is solved from the perspective of static and mobile data gathering of sink nodes. Subgradient method is used to solve the lifetime optimization model when one sink node stays at one anchor location. Geometric method is used to evaluate the amount of gathering data when sink nodes are moving. Finally, all sensor nodes transmit data according to the optimal data transmission scheme. Sink nodes gather the data along the shortest movement paths. Simulation results show that MLMS can prolong network lifetime, balance node energy consumption, and reduce data gathering latency under appropriate parameters. Under certain conditions, it outperforms Ratio_w, TPGF, RCC, and GRND.

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