Node placement optimization in ShuffleNets

1998 ◽  
Vol 6 (3) ◽  
pp. 319-324 ◽  
Author(s):  
K.L. Yeung ◽  
T.-S.P. Yum
Keyword(s):  
Node Placement ◽  
Placement Optimization

scholarly journals Regional Optimization Dynamic Algorithm for Node Placement in Wireless Sensor Networks

Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4216
Author(s):  
Yijie Zhang ◽  
Mandan Liu
Keyword(s):  
Sensor Nodes ◽  
Wireless Sensor ◽  
Search Performance ◽  
Search Range ◽  
Node Number ◽  
Dynamic Algorithm ◽  
Node Placement ◽  
Placement Optimization ◽  
Coverage Hole ◽  
Comparison Algorithms

Node placement is one of the basic problems in a Wireless Sensor Network (WSN). During the operation of a WSN, sensor nodes may fail or die suddenly, which may lead to a coverage hole. To solve this problem, the node placement needs to be re-optimized. The dimensions of node placement optimization are high because of the large node number. In view of this defect, a regional optimization dynamic algorithm is put forward. In this paper, the regional optimization problem of node placement is modeled, and a regional optimization dynamic algorithm with a mixed strategy for node placement (MRDA) is proposed. Simulation experiments are carried out for the proposed algorithm and other comparison algorithms. Results of experiments show that the proposed algorithm can greatly reduce the dimensions and narrow the search range, with a significant improvement in the search performance and convergence speed.

scholarly journals Node Placement Optimization of Wireless Sensor Networks Using Multi-Objective Adaptive Degressive Ary Number Encoded Genetic Algorithm

Algorithms ◽  
2020 ◽  
Vol 13 (8) ◽  
pp. 189
Author(s):  
Yijie Zhang ◽  
Mandan Liu
Keyword(s):  
Optimization Algorithm ◽  
Low Cost ◽  
Wireless Sensor ◽  
Multi Objective Optimization ◽  
Placement Problem ◽  
Node Placement ◽  
Multi Objective ◽  
Placement Optimization ◽  
Monitoring Accuracy ◽  
Encoding Method

The wireless sensor network (WSN) has the advantages of low cost, high monitoring accuracy, good fault tolerance, remote monitoring and convenient maintenance. It has been widely used in various fields. In the WSN, the placement of node sensors has a great impact on its coverage, energy consumption and some other factors. In order to improve the convergence speed of a node placement optimization algorithm, the encoding method is improved in this paper. The degressive ary number encoding is further extended to a multi-objective optimization problem. Furthermore, the adaptive changing rule of ary number is proposed by analyzing the experimental results of the N-ary number encoded algorithm. Then a multi-objective optimization algorithm adopting the adaptive degressive ary number encoding method has been used in optimizing the node placement in WSN. The experiments show that the proposed adaptive degressive ary number encoded algorithm can improve both the optimization effect and search efficiency when solving the node placement problem.

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