A cluster-head election method based on preset priority for multi-hop networks

Abstract

The invention discloses a preset-priority-based cluster head selection method for a multi-hop network. On the basis of a node priority, a cluster head selection function can be realized only by broadcasting information, so that generation of more other signaling is avoided and the system cost is low. According to the invention, a priority is set for each node, wherein the priorities of all nodes are different from each other, the node with the highest priority serves as a cluster head of a cluster and other nodes serve as common nodes; a cluster head ID, a cluster head priority, and a broadcast serial number in a current network are recorded in local records of all node; the cluster head broadcasts a message to other nodes periodically, wherein the broadcasted message includes the cluster head ID, the cluster head priority, and the broadcast serial number; and after the common nodes receive the broadcasted message, the cluster head priority in the broadcasted message and the cluster head priority in local records are checked and the cluster head with the higher priority serves as the cluster head.

Description

technical field [0001] The invention relates to the technical field of multi-hop ad hoc networks, in particular to a method for electing cluster heads based on preset priorities suitable for multi-hop networks. Background technique [0002] The goal of cluster head election in ad hoc networks is to construct and maintain a cluster set with less computing and communication overhead, and generate a new cluster structure when the network structure changes to ensure normal network communication. Currently several typical clustering algorithms include the following: minimum ID clustering algorithm, highest node degree clustering algorithm and minimum mobility clustering algorithm. Among them, the minimum ID clustering algorithm is simple to calculate, easy to implement, and the algorithm converges quickly, but the algorithm has a lot of node overhead; in the highest node degree clustering algorithm, nodes need to frequently count their own connectivity and constantly inform other...

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Problems solved by technology

Among them, the minimum ID clustering algorithm is simple to calculate, easy to implement, and the algorithm converges quickly, but the algorithm has a lot of node overhead; in the highest node degree clustering algorithm, nodes need to frequently count their own connectivity and constantly inform other nodes in the network. When the mobility of the node is strong, the update frequency of the cluster head is high, and the cluster maintenance cost is high; the minimum mobility clustering algorithm is a kind of node weight clustering algorithm, but it needs a variety of other auxiliary means to obtain mobile information, which is not easy operate

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