Ship to Air Collaborative Communication Network Topology Optimization Method Based on Genetic Algorithm

2016 ◽  
Author(s):  
Peng Pengfei ◽  
Yu Qian ◽  
Cui Haotian
Keyword(s):  
Genetic Algorithm ◽  
Communication Network ◽  
Topology Optimization ◽  
Network Topology ◽  
Optimization Method ◽  
Collaborative Communication ◽  
Network Topology Optimization ◽  
Topology Optimization Method

scholarly journals A Topology Optimization Method for Reducing Communication Overhead in the Kalman Consensus Filter

2021 ◽  
Vol 11 (15) ◽  
pp. 7107
Author(s):  
Lulu Lv ◽  
Huifang Chen ◽  
Lei Xie ◽  
Kuang Wang
Keyword(s):  
Topology Optimization ◽  
Network Topology ◽  
Structural Parameters ◽  
Estimation Algorithm ◽  
Optimization Method ◽  
Distributed Estimation ◽  
Communication Overhead ◽  
Consensus Filter ◽  
Network Topology Optimization ◽  
Topology Optimization Method

Distributed estimation and tracking of interested objects over wireless sensor networks (WSNs) is a hot research topic. Since network topology possesses distinctive structural parameters and plays an important role for the performance of distributed estimation, we first formulate the communication overhead reduction problem in distributed estimation algorithms as the network topology optimization in this paper. The effect of structural parameters on the algebraic connectivity of a network is overviewed. Moreover, aiming to reduce the communication overhead in Kalman consensus filter (KCF)-based distributed estimation algorithm, we propose a network topology optimization method by properly deleting and adding communication links according to nodes’ local structural parameters information, in which the constraint on the communication range of two nodes is incorporated. Simulation results show that the proposed network topology optimization method can effectively improve the convergence rate of KCF algorithm and achieve a good trade-off between the estimate error and communication overhead.

scholarly journals Fast Nondominated Sorting Genetic Algorithm II with Lévy Distribution for Network Topology Optimization

2020 ◽  
Vol 2020 ◽  
pp. 1-12 ◽  
Author(s):  
Maoqing Zhang ◽  
Lei Wang ◽  
Zhihua Cui ◽  
Jiangshan Liu ◽  
Dong Du ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Topology Optimization ◽  
Network Topology ◽  
Optimization Problems ◽  
Selection Strategy ◽  
Nsga Ii ◽  
Comparison Results ◽  
Practical Engineering ◽  
Network Topology Optimization ◽  
Nondominated Sorting

Fast nondominated sorting genetic algorithm II (NSGA-II) is a classical method for multiobjective optimization problems and has exhibited outstanding performance in many practical engineering problems. However, the tournament selection strategy used for the reproduction in NSGA-II may generate a large amount of repetitive individuals, resulting in the decrease of population diversity. To alleviate this issue, Lévy distribution, which is famous for excellent search ability in the cuckoo search algorithm, is incorporated into NSGA-II. To verify the proposed algorithm, this paper employs three different test sets, including ZDT, DTLZ, and MaF test suits. Experimental results demonstrate that the proposed algorithm is more promising compared with the state-of-the-art algorithms. Parameter sensitivity analysis further confirms the robustness of the proposed algorithm. In addition, a two-objective network topology optimization model is then used to further verify the proposed algorithm. The practical comparison results demonstrate that the proposed algorithm is more effective in dealing with practical engineering optimization problems.

Topology optimization method of lattice structures based on a genetic algorithm

2016 ◽  
Vol 16 (3) ◽  
pp. 743-753 ◽  
Author(s):  
Ruo-qiang Feng ◽  
Feng-cheng Liu ◽  
Wei-jia Xu ◽  
Min Ma ◽  
Yang Liu
Keyword(s):  
Genetic Algorithm ◽  
Topology Optimization ◽  
Optimization Method ◽  
Lattice Structures ◽  
Topology Optimization Method

A CAN Topology Optimization of Pure Electric Vechicle

2013 ◽  
Vol 791-793 ◽  
pp. 1819-1823
Author(s):  
Xi Chen ◽  
Jian Wu ◽  
Yang Zhao ◽  
Hong Tao Bai
Keyword(s):  
Genetic Algorithm ◽  
Topology Optimization ◽  
Network Topology ◽  
Network Performance ◽  
Can Bus ◽  
Optimization Method ◽  
Network System ◽  
Multi Objective Optimization ◽  
Upper Limit ◽  
Vehicle Network

In the design of CAN network system, as CAN bus topology will affect network performance and cost, it is important to optimize the network topology. This paper analyzes the CAN busload based on CAN protocol, calculates the upper limit of transmission message frames in a single CAN bus. As the amount of information on the bus is increasing, a single CAN bus cannot meet the communication requirements, we put forward dividing the network into multiple homogeneous segments via multi-objective optimization method, developing a genetic algorithm strategy and solving the problem in a MATLAB platform. Finally utilize the method to design a pure electric vehicle network topology.

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