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Method of wireless sensor network clustering by using Hopfield nerve network

A wireless sensor and neural network technology, applied in the field of wireless sensor network clustering, can solve the problem of large energy consumption

Inactive Publication Date: 2013-06-19
SHANDONG UNIV
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  • Abstract
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  • Claims
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Problems solved by technology

In this case, when transmitting information with the cluster head nodes through a long-distance communication, these nodes need to consume a lot of energy

Method used

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  • Method of wireless sensor network clustering by using Hopfield nerve network
  • Method of wireless sensor network clustering by using Hopfield nerve network
  • Method of wireless sensor network clustering by using Hopfield nerve network

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Experimental program
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Embodiment

[0049] A method for wireless sensor network clustering with Hopfield neural network, first establishes a wireless sensor network system model:

[0050] The properties that this model has are:

[0051] (1) Each node performs sensing tasks and always sends data to the base station regularly;

[0052] (2) The fixed base station can be located both inside and outside the sensor network;

[0053] (3) All nodes are fixed and energy-constrained;

[0054] (4) Nodes have the ability to control their power to change their transmission power;

[0055] (5) All nodes can run in cluster head mode and sensor node mode;

[0056] The transmitter consumes energy to run radio electronics and power amplifiers, while the receiver also consumes energy to run radio equipment, power control the radio so that it can consume the lowest energy to transmit the required information to the intended receiver, in order will send distance d 0 The signal-to-noise ratio required for a message of λ bits is ...

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Abstract

Disclosed is a method of wireless sensor network clustering by using Hopfield nerve network. The method belongs to the technical field of wireless sensor network, improves deficiencies of LEACH (Low Energy Adaptive Clustering Hierarchy) protocol to balance energy consumption of each node and distribution of each cluster-head, and models the clustering protocol into a combination optimization problem. The method improves traditional Hopfield nerve network local extreme value problem and fixed step length problem, and provides a dynamic step length chaotic Hopfield nerve network under the name of DSC-HNN. DSC-HNN achieves best cluster-head selection. The method can effectively achieve the principle of protocol, delay the death time of nodes to maximize the life cycle of the wireless sensor network to prolong the life cycle of network.

Description

technical field [0001] The invention relates to a method for clustering a wireless sensor network, in particular to a method for clustering a wireless sensor network by using a Hopfield neural network, and belongs to the technical field of wireless sensor networks. Background technique [0002] Wireless sensor network (WSN) is composed of a large number of cheap micro-sensor nodes deployed in the monitoring area, forming a multi-hop, self-organizing network system through wireless communication, and its purpose is to cooperatively perceive, collect and process the network coverage area The information of the perceived object in the object is sent to the observer. Compared with the current common wireless networks (including mobile communication networks, wireless local area networks, Bluetooth networks, Ad hoc networks, etc.), wireless sensor networks have limited hardware resources. Limited power capacity, no center, self-organization, multi-hop routing, dynamic topology, ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04W40/02H04W84/18
CPCY02D30/70
Inventor 江铭炎杨敏
Owner SHANDONG UNIV
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