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Ad-hoc network clustering algorithm based on node data value

A technology of node data and node degree, applied in the field of Ad-hoc network clustering algorithm, can solve the problems of shortening network life cycle, reducing channel utilization, low cluster maintenance overhead, etc., achieving long network life cycle and high load balance. , to avoid the effect of excessive energy consumption

Active Publication Date: 2018-12-04
KUNMING UNIV OF SCI & TECH
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  • Claims
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Problems solved by technology

Minimum ID algorithm (LID), this algorithm is easy to implement, the replacement of cluster heads is slow, and the cost of cluster maintenance is small, but nodes with smaller IDs consume high energy because they serve as cluster heads for a long time, shortening the life cycle of the network
The highest node degree algorithm (HD), the number of clusters in this algorithm is small, which reduces the packet delay, but the small number of clusters will reduce the utilization of the channel
WCA algorithm, this algorithm considers many factors and calculates the corresponding weight value, selects the cluster head and divides the cluster structure of network nodes through the weight value, but the clustering process needs to know the weight value of the node in advance, prolong the cycle of the network, and make the information The forwarding overhead is large, and the energy consumption of nodes is increased at the same time

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  • Ad-hoc network clustering algorithm based on node data value
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  • Ad-hoc network clustering algorithm based on node data value

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Embodiment Construction

[0044] Embodiments of the invention are described in detail below, but the invention can be practiced in many different ways as defined and covered by the claims.

[0045]Based on the description in the background technology, in order to improve the shortcomings of traditional clustering algorithms, the present invention proposes an Ad-hoc network clustering algorithm based on node data values. First calculate any node M separately i Various indicators of , including its node degree d i The difference D with the optimal node degree α i , node data value V i , node energy value E i and node M i Average distance to all neighbor nodes in the same cluster Then calculate the combined weight where ω 1 +ω 2 +ω 3 +ω 4 = 1; Finally, by comparing node M i Clustering with the weight of neighbor nodes, the node with the smallest weight is the cluster head, and broadcasts a message to the neighbor nodes, announcing itself as the cluster head, in the case of the same weight, th...

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Abstract

The invention, which belongs to the technical field of the Ad-hoc wireless network, relates to an Ad-hoc network clustering algorithm based on a node data value. According to the invention, with comprehensive consideration of three factors including a node energy value, a node degree and an average node distance of the Ad-hoc network, a node data value factor is added, so that a problem of unrealtransmitted data caused by too high energy consumption and too small data because of the too large data transmitted by the node is solved. The generated cluster head has high stability; the update frequency is low; and the load balance is high; the network is optimized in terms of the cluster head number; the reentrant cluster and rule set updating is improved; the life cycle of the network is extended to some extents; and the stability of the cluster structure is enhanced.

Description

technical field [0001] The invention relates to an Ad-hoc network clustering algorithm based on node data values, and belongs to the technical field of Ad-hoc wireless networks. Background technique [0002] Ad-hoc network is a multi-hop, centerless, self-organizing wireless network. The entire network has no fixed infrastructure, and each node is mobile. It is precisely because of its characteristics that it brings scalability and management A series of inconveniences. In order to improve the scalability of the Ad-hoc network and achieve network load balancing, we use clustering algorithms for the network, and use the cooperative work of cluster heads and cluster members to improve the overall performance of the network. At present, the more common clustering algorithms include the minimum ID algorithm, the highest node degree algorithm and the WCA algorithm. Minimum ID algorithm (LID), this algorithm is easy to implement, the replacement of cluster heads is slow, and the...

Claims

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Application Information

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IPC IPC(8): H04W40/04H04W84/18
CPCH04W40/04H04W84/18Y02D30/70
Inventor 唐菁敏高张宝
Owner KUNMING UNIV OF SCI & TECH