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A Method for Solving the Optimal Path of Wireless Sensor Networks Using Differential Evolution

A wireless sensor and optimal path technology, applied in network topology, wireless communication, advanced technology, etc., can solve problems such as long search time, stagnant local optimal solution, sensitive search speed and precision, etc., to achieve good performance and good convergence sexual effect

Active Publication Date: 2018-06-15
HENAN UNIV OF CHINESE MEDICINE
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

The research found that these methods have certain shortcomings in the solution speed and performance. For example, when solving the problem based on genetics, it takes a long time to search, and it is easy to stagnate in the local optimal solution.
When using the particle swarm algorithm to solve this problem, more parameter settings are required, and it is more sensitive in terms of search speed and accuracy.

Method used

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  • A Method for Solving the Optimal Path of Wireless Sensor Networks Using Differential Evolution
  • A Method for Solving the Optimal Path of Wireless Sensor Networks Using Differential Evolution
  • A Method for Solving the Optimal Path of Wireless Sensor Networks Using Differential Evolution

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Embodiment 1

[0031] The present invention proposes a method for solving the optimal path of wireless sensor networks by using differential evolution. According to the knowledge of graph theory, an undirected graph G=(V, E) is used to describe the path problem of wireless sensor networks, and to study the optimal path of wireless sensor networks. Nodes and information transmission, in the undirected graph G=(V, E), V represents the collection of all nodes in the network, E is the collection of all communication routes, V=V head , V 1 ,...,V k ,...,V n ;E=E 1 ,...,E k ,...,E n ;E 1 is the connection link of the first node, E k is the connecting link of the kth node; suppose that V head is the target node in the cluster, that is, the cluster head node; the kth node is the source node, and the path optimization model is established, and then the differential evolution algorithm is used as a search tool to obtain the minimum energy consumption required to transfer from the source node to...

Embodiment 2

[0033] The method of using differential evolution to solve the optimal path of the wireless sensor network in this embodiment is different from Embodiment 1 in that further: V i , V j is a node in the undirected graph G=(V, E), node V i and V j The energy consumed by transferring links between is C ij , the energy consumption matrix of the entire network is C=[C ij ], the matrix is ​​a symmetric matrix L of n*n, namely C ij =C ji ; node V i and V j The connection between is I ij , if node V i to V j There is a link between them, then I ij =1, otherwise I ij =0;

[0034] Transform the optimal path in the wireless sensor network into a minimization problem, and obtain the optimization objective function

[0035]

[0036] In the formula, i and j are node numbers, which are natural numbers; s is the source node, and D is the target node; the optimal transmission path is obtained by obtaining the minimum energy consumption required for transmission from the source n...

Embodiment 3

[0038] The method of using differential evolution to solve the optimal path of the wireless sensor network in this embodiment is different from that in Embodiment 2 in that: a path-based variable-length decimal chromosome coding method is used to code and design chromosomes, and randomly generate initialization chromosomes Population, chromosomes are composed of integer queues, and the integers of each gene are different. These integers are the node numbers in the wireless sensor network. The first and last genes of all chromosomes are the source node and the target node respectively;

[0039] After the population is initialized, the mutation operation is first performed, and the set-based DE / rand / 1 mutation is adopted, and the chromosome r2 and r3 are subtracted to obtain c, which is equivalent to r2-r3 in the classic differential mutation, and then the chromosome r1 and c are merged. Set operation, similar to r1+(r2-r3) in classic mutation, because it is a set processing, the...

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Abstract

The invention relates to a method for solving the optimal path of a wireless sensor network by using differential evolution. According to the method, an undirected graph is utilized to describe wireless sensor network path problems and research nodes and information transmission in the wireless sensor network according to graph theory knowledge; the undirected graph can be expressed by an equation that G=(V,E), wherein V indicates the set of all nodes of the network, E is the set of all communication lines, V=Vhead, V1,... , Vk,... , Vn, and E=E1,... , Ek,... En; Vhead is assumed to be the target node in the cluster, namely, a cluster head node; a k-th node is adopted as a source node, and a path optimization model is established; a differential evolution algorithm is adopted as a search tool to find minimum energy consumption required by information transmission from the source node to the target node; and a path with minimum energy consumption required by information transmission from the source node to the target node is found. With the method adopted, an optimal transmission path with minimum energy consumption can be calculated quickly and accurately.

Description

technical field [0001] The invention relates to a solution to the optimal path problem in wireless sensor networks (Wireless Sensor Networks, WSNs) using a differential evolution algorithm (Differential Evolution, DE). The method can quickly and accurately calculate the optimal transmission path with the least energy consumption path. Background technique [0002] Wireless sensor networks are the core technology of the Internet of Things and are widely used in military, medical, agricultural, transportation and other industries. Due to energy constraints in WSNs, how to achieve the longest survival time is the most critical issue. [0003] In order to maximize the survivability of wireless sensor networks (WSNs), it can be achieved from many different perspectives. Finding the optimal transmission path with the least energy consumption in wireless sensor networks is a classical method. This problem can be transformed into an undirected graph, the optimal path problem from...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04W40/08H04W84/18
CPCH04W40/08H04W84/18Y02D30/70
Inventor 许玉龙王晓鹏余孝奎张晗王忠义谢志豪王晓辉曹莉吕雅丽王林景
Owner HENAN UNIV OF CHINESE MEDICINE
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