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A node mobility clustering method and system

A mobility and node technology, applied in the field of communication engineering, can solve the problems that cluster head selection cannot achieve global optimization, shorten the network life cycle, and too many factors of manual intervention.

Active Publication Date: 2021-03-02
HUNAN CITY UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

There are mainly the following points of view: First, reduce the packet loss rate at the cost of increasing network overhead. This method will increase node power consumption and shorten the life cycle of the network. In large-scale networks, network congestion may occur, thereby reducing transmission The second is to establish a relatively stable transmission path between cluster members and cluster heads. This method effectively improves the transmission success rate and reduces node power consumption and network overhead, but it is not suitable for nodes in large-scale wireless sensor networks. Scenes with frequent movement
Third, in order to solve the problem of node mobility, a Mobility-based Clustering Protocol (MBC) is proposed. To limit the establishment of a stable topology between cluster members and cluster heads, the main idea is to construct a fitness value related to the connected cluster head nodes for non-cluster head nodes to calculate the remaining energy of cluster heads, the connection time between each other and Cluster head node degree and transmission distance, the fitness value is obtained by manually setting parameters and linearly summing each factor, there are too many manual intervention factors, and the selection of cluster heads cannot achieve global optimality.

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  • A node mobility clustering method and system
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  • A node mobility clustering method and system

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Experimental program
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Embodiment 1

[0049] Such as figure 1 As shown, a node mobility clustering method provided in this embodiment includes:

[0050] Step 101: According to the set mutation probability, perform a genetic mutation operation on the optimal cluster to obtain a dominant subgraph and a non-dominated subgraph, and store the non-dominant subgraph in the first set corresponding to the current iteration number, and set The dominant subgraph is stored in the second set corresponding to the current number of iterations; wherein the optimal cluster is the optimal solution; the optimal solution is obtained by sequentially inputting the clusters in the initial population into the multi-objective optimization function Obtained; the optimal solution is a cluster comprising only one cluster head node; the multi-objective optimization function is an objective function of maximizing residual energy, minimizing connection distance, and maximizing connection time; the initial population includes multiple clusters;...

Embodiment 2

[0066] In order to improve the clustering accuracy of the large-scale wireless sensor network, on the basis of Embodiment 1, an additional step is added to adjust the mutation probability and the selection probability, and repeat steps 101 to 107. Wherein, in this embodiment, no initial population construction and multi-objective optimization function construction are required, and the total number of iterations remains unchanged.

Embodiment 3

[0068] Such as figure 2 As shown, a node mobility clustering system provided in this embodiment includes:

[0069] The storage module 100 is configured to perform a genetic mutation operation on the optimal cluster according to a set mutation probability to obtain a dominant subgraph and a non-dominated subgraph, and store the non-dominant subgraph in the first set corresponding to the current iteration number , store the dominant subgraph in the second set corresponding to the current iteration number; wherein, the optimal cluster is the optimal solution; the optimal solution is obtained by sequentially inputting the clusters in the initial population into the multi-objective Obtained in the optimization function; the optimal solution is a cluster that only contains one cluster head node; the multi-objective optimization function is an objective function that maximizes the remaining energy, minimizes the connection distance, and maximizes the connection time; the initial Th...

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Abstract

The invention discloses a node mobility clustering method and system, and relates to the technical field of communication engineering. The invention uses the maximization of remaining energy, the minimization of connection distance, and the maximization of connection time as multi-objective optimization functions, and based on multi-objective evolutionary planning Genetic algorithm is a processing method, through the initialization of the parent population, mutation, and selection operations, clustering is carried out for large-scale wireless sensor networks, and the stable connection between non-cluster head members and cluster heads is established to the maximum extent to reduce the network packet loss rate. The purpose of reducing network overhead and saving power consumption provides a reference for the analysis method of node movement scenarios in large-scale wireless sensor networks.

Description

technical field [0001] The invention relates to the technical field of communication engineering, in particular to a node mobility clustering method and system based on a multi-objective evolutionary programming genetic algorithm. Background technique [0002] Node energy in large-scale wireless sensor networks has always been one of the most important considerations in network communication. Routing protocols based on energy saving have always been the focus of researchers. Relevant studies have shown that the use of clustering strategies in large-scale wireless sensor networks is helpful for load balancing, efficient use of resources and data fusion. There are mainly the following points of view: First, reduce the packet loss rate at the cost of increasing network overhead. This method will increase node power consumption and shorten the life cycle of the network. In large-scale networks, network congestion may occur, thereby reducing transmission The second is to establ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04L12/715H04W40/02H04W40/04H04W40/10
CPCH04L45/46H04W40/02H04W40/04H04W40/10Y02D30/70
Inventor 邓曙光曹步文肖湘杨冰秦华
Owner HUNAN CITY UNIV