scholarly journals Parallel Processing for Range Assignment Problem in Wireless Sensor Networks

2020 ◽  
Author(s):  
M. Prasanna Lakshmi ◽  
D. Pushparaj Shetty
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Parallel Processing ◽  
Assignment Problem ◽  
Wireless Sensor ◽  
Range Assignment

A multi-objective evolutionary algorithm for the deployment and power assignment problem in wireless sensor networks

2010 ◽  
Vol 54 (6) ◽  
pp. 960-976 ◽  
Author(s):  
Andreas Konstantinidis ◽  
Kun Yang ◽  
Qingfu Zhang ◽  
Demetrios Zeinalipour-Yazti
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Evolutionary Algorithm ◽  
Assignment Problem ◽  
Wireless Sensor ◽  
Power Assignment ◽  
Multi Objective

Optimal range assignment in solar powered active wireless sensor networks

2012 ◽  
Author(s):  
Benjamin Gaudette ◽  
Vinay Hanumaiah ◽  
Sarma Vrudhula ◽  
Marwan Krunz
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Wireless Sensor ◽  
Optimal Range ◽  
Range Assignment ◽  
Solar Powered

scholarly journals An Energy-Efficient Coverage Enhancement Strategy for Wireless Sensor Networks Based on a Dynamic Partition Algorithm for Cellular Grids and an Improved Vampire Bat Optimizer

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 619 ◽  
Author(s):  
Xiaoqiang Zhao ◽  
Yanpeng Cui ◽  
Zheng Guo ◽  
Zhanjun Hao
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Assignment Problem ◽  
Energy Cost ◽  
Task Assignment ◽  
Residual Energy ◽  
Coverage Rate ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Vampire Bat

Sensor nodes perform missions based on the effectual invariable coverage of events, and it is commonly guaranteed by the determinate deployment for sensor nodes who deviate from the optimum site frequently. To reach the optimal coverage effect with the lowest costs is a primary goal of wireless sensor networks. In this paper, by splicing the sensing area optimally with cellular grids, the best deployment location for sensors and the required minimum number of them are revealed. The optimization problem of coverage rate and energy consumption is converted into a task assignment problem, and a dynamic partition algorithm for cellular grids is also proposed to improve the coverage effect when the number of sensors is variable. Furthermore, on the basis of solving the multi-objective problem of reducing and balancing the energy cost of sensors, the vampire bat optimizer is improved by introducing virtual bats and virtual preys, and finally solves the asymmetric assignment problem once the number of cellular grids is not equal to that of sensors. Simulation results indicate that the residual energy of sensors during redeployment is balanced notably by our strategy when compared to three other popular coverage-enhancement algorithms. Additionally, the total energy cost of sensor nodes and coverage rate can be optimized, and it also has a superior robustness when the number of nodes changes.

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