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An Energy Balanced Routing Optimization Method for Wireless Sensor Networks Based on Cluster Head Expectations

A wireless sensor and energy balancing technology, applied in network traffic/resource management, network topology, wireless communication, etc., can solve problems such as unbalanced energy consumption of cluster heads, achieve extended network life cycle, cluster head distribution and quantity stability, The effect of improving energy efficiency

Active Publication Date: 2018-07-20
HUAQIAO UNIVERSITY
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The purpose of the invention is to overcome the deficiencies of the prior art, and provide a wireless sensor network energy balance routing optimization method (CHEEB) based on cluster head expectations. An optimization goal is to ensure that the number of cluster heads in each round is within the expected range by improving the threshold when electing cluster heads, so as to alleviate the problem of unbalanced energy consumption of cluster heads; at the same time, by controlling the coverage of cluster heads in different positions, the distance weight is considered and the remaining energy weight, so that the member nodes of the cluster head are distributed more evenly, so as to improve the energy efficiency of the nodes

Method used

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  • An Energy Balanced Routing Optimization Method for Wireless Sensor Networks Based on Cluster Head Expectations
  • An Energy Balanced Routing Optimization Method for Wireless Sensor Networks Based on Cluster Head Expectations
  • An Energy Balanced Routing Optimization Method for Wireless Sensor Networks Based on Cluster Head Expectations

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Embodiment 1

[0051] see figure 1 and figure 2 As shown, an energy-balanced routing optimization method for wireless sensor networks based on cluster head expectations of the present invention is characterized in that it includes: adding factors such as the number of clusters, the remaining energy of nodes, and the load balance of clusters to the election of cluster heads, The load distribution of the clusters and the remaining energy of the nodes are used as the two main indicators for the election of the cluster head; the working time unit of the election of the cluster head is a round, and each round is divided into two parts: the cluster establishment phase and the data transmission phase, through Adjust the threshold to ensure that the number of cluster heads in each round is within the expected range, and solve the problem of unbalanced energy consumption of cluster heads; by controlling the coverage of cluster heads at different positions, and calculating distance weights and remain...

Embodiment 2

[0069] The LEACH algorithm adopts the method of rotating cluster heads, and the unit of working time is a round, and each round is divided into two parts: the cluster establishment phase and the data transmission phase. In the cluster establishment phase, node i randomly generates a positive number less than 1, if it is less than the threshold P i , then node i is elected as the cluster head of this round. Threshold P i for:

[0070]

[0071] Where n is the total number of nodes, the expected number of cluster heads is k (k is a user-defined parameter, such as k=5%*n), r is the number of current rounds, and n / k rounds are defined as a cycle. C i is an indicator function of whether node i has become a cluster head in the current period, that is, if node i has not become a cluster head in the current period, then C i = 1, otherwise C i =0. For the convenience of calculation and proof, formula (1) is rewritten as formula (2):

[0072]

[0073] There are many improved...

Embodiment 3

[0096] The pseudo code of the proposed CHEEB algorithm of the present invention is as follows:

[0097]

[0098]

[0099]

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Abstract

The invention discloses a wireless sensor network energy balance route optimization method based on cluster head expectation. An algorithm considers two optimal objects which are cluster load distribution condition and node residual energy while electing cluster heads, and ensures the number of cluster heads in each round to be in an expected range by improving a threshold value while electing cluster heads so as to solve the problem that the energy consumption of the cluster heads is unbalanced. Simultaneously, the algorithm considers distance weight and residual energy weight by controlling coverage areas of different cluster heads in different positions so that the member node distribution of the cluster heads could be relative even to improve node energy efficiency. The algorithm presented by the invention has relative high energy efficiency, well balances the energy consumption of nodes in the network, and enables the cluster head distribution and number to be more stable. The optimization method of the invention could improve data transmission amount, prolongs network lifetime and preferably meet the requirement of the wireless sensor network to the network lifetime in a periodic monitoring environment.

Description

technical field [0001] The present invention relates to a wireless sensor network energy balance route optimization method, in particular to a cluster head expectation based wireless sensor network energy balance route optimization method. Background technique [0002] As an important branch of the Internet of Things, WSN (Wireless Sensor Networks) is used to sense and collect data in the monitored environment. Adjacent nodes perceive the same object information in real time, and then fuse and compress it through wireless ad hoc The multi-hop protocol is sent to the base station. WSN cluster routing has the advantages of clear hierarchy, strong scalability, and easy fusion of adjacent data, which is very suitable for industrial monitoring and other application fields. [0003] The clustering routing algorithm includes the election of the cluster head, the communication between the cluster head and the base station, and two communication methods, single-hop and multi-hop, ca...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04W28/08H04W40/10H04W40/20H04W84/18
CPCH04W28/08H04W40/10H04W40/20H04W84/18Y02D30/70
Inventor 蒋文贤赖超
Owner HUAQIAO UNIVERSITY
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