Wireless sensor network routing energy saving method based on particle swarm

A wireless sensor and particle swarm algorithm technology, applied in wireless communication, energy consumption reduction, advanced technology, etc., can solve the problems of fast energy consumption, death, and high algorithm overhead of nodes, so as to prolong the life cycle, delay the death rate, and save energy. The effect of load balancing

Inactive Publication Date: 2016-04-06
TIANJIN UNIV
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  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] 1. Early TopDisc clustering algorithm [1] , can make nodes quickly form a cluster structure in a densely deployed sensor network, and establish a tree relationship between cluster heads, but the cluster network formed by this method is not flexible enough, and the algorithm overhead is too large
[0006] 2. Relevant scholars at the University of Southern California proposed a GAF clustering algorithm based on the geographical location of nodes [2] , but the algorithm requires precise geographic location and does not guarantee uniform energy consumption
[0007] 3. LEACH algorithm [3] It is a low-power adaptive hierarchical routing algorithm and the first clustering routing algorithm p

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  • Wireless sensor network routing energy saving method based on particle swarm
  • Wireless sensor network routing energy saving method based on particle swarm
  • Wireless sensor network routing energy saving method based on particle swarm

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Embodiment 1

[0037] see figure 1 , the embodiment of the present invention provides a particle swarm based wireless sensor network routing energy saving method, the wireless sensor network routing energy saving method includes the following steps:

[0038] 101: Obtain the fitness value function used to select the cluster head, iterate the fitness value function through the particle swarm optimization algorithm, and find the wireless sensor node with a large fitness value as the cluster head in the network;

[0039] 102: Broadcast the selected cluster head to other wireless sensor nodes, and other wireless sensor nodes perceive the distance from the cluster head according to the strength of the broadcast signal received, so as to select which cluster to join;

[0040] 103: The cluster head receives and fuses the environmental information data sent by other wireless sensor nodes, and then sends the fused environmental information data to the sink node, and the communication ends.

[0041] W...

Embodiment 2

[0051] Combine belowfigure 1 1. The specific calculation formula introduces the scheme in embodiment 1 in detail, see the following description for details:

[0052] 201: Randomly define n wireless sensor nodes in a limited area, and the initial energy E of each wireless sensor node 0 all the same;

[0053] 202: Initialize each wireless sensor node through the LEACH algorithm;

[0054] During specific implementation, other algorithms may also be used to initialize each wireless sensor node. The initialization steps are well known to those skilled in the art, and will not be described in detail in this embodiment of the present invention.

[0055] 203: Obtain the fitness value function used to select the cluster head, iterate the fitness value function through the particle swarm optimization algorithm, and find the sensor node with a larger fitness value as the cluster head in the network;

[0056] Wherein, after the initialization of each wireless sensor node in step 202, so...

Embodiment 3

[0087] Combined with Table 1 below, figure 2 and image 3 The scheme in embodiment 1 and 2 is carried out feasibility verification, see the following description for details:

[0088] The particle swarm-based wireless sensor network routing method proposed in the embodiment of the present invention is verified below. Simultaneously, a simulation experiment is compared with an existing routing method to prove that the method can effectively prolong the life cycle of the network.

[0089] Next, use MATLAB software for simulation. First, set the parameters. The simulation parameter table is as follows:

[0090]

[0091]

[0092] First with the existing HEED algorithm [5] and Hausdoff algorithm [6] Comparing the initial node death time, the result is as follows figure 2 shown. The abscissa is the number of different wireless sensor nodes defined in the simulation, and the ordinate is the death time of the first wireless sensor node. figure 2 It can be seen from the ...

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Abstract

The invention discloses a wireless sensor network routing energy saving method based on a particle swarm, and relates to the field of a wireless sensor network. The wireless sensor network routing energy saving method comprises the following steps of: acquiring a fitness function for selecting cluster heads, carrying out iteration on the fitness function by a particle swarm algorithm, searching wireless sensor nodes with large fitness values and using the selected wireless sensor nodes as the cluster heads in the network; broadcasting the selected cluster heads to other wireless sensor nodes, so that other wireless sensor nodes, according to strength of received broadcast signals, sense distances with the cluster heads to select which clusters to add; and enabling the cluster heads to receive environment information data sent by other wireless sensor nodes, carrying out fusion on the environment information data, then sending the fused environment information data to a convergent node, and ending communication. According to the wireless sensor network routing energy saving method based on the particle swarm, residual energy information and position information of the nodes are sufficiently considered, and the suitable cluster heads are selected by particle swarm optimization so as to balance energy consumption of the network and prolong the life cycle.

Description

technical field [0001] The invention relates to the field of wireless sensor networks, in particular to a particle swarm-based wireless sensor network routing energy-saving method. Background technique [0002] Due to its own limitations, wireless sensor networks have very limited energy. Moreover, wireless sensor networks are very different from traditional wireless networks. The primary design goals of traditional wireless networks are to improve application-oriented service quality, reliability and make bandwidth utilization more efficient, and then energy saving is taken into consideration. However, most of the collected areas that use sensor nodes to obtain information are very harsh or uninhabitable areas, such as deserts, forests, and oceans. In this environment, when the sensor network works for a certain period of time and consumes a lot of energy, It is extremely unrealistic to replace the battery artificially. [0003] Therefore, the primary problem in the devel...

Claims

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Application Information

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IPC IPC(8): H04W40/10H04W40/20
CPCH04W40/10H04W40/20Y02D30/70
Inventor 王宁周圆陈莹
Owner TIANJIN UNIV
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