Mobile charging vehicle multi-target charging scheduling method based on energy priority

Abstract

The invention discloses a mobile charging vehicle multi-target charging scheduling method based on energy priority, and the method comprises the steps: firstly clustering a network through a K-Means-PER algorithm so that a node with high energy demand emergency degree becomes a clustering center in priority; secondly, comprehensively considering double weights of energy and distance of the node, selecting a communication cluster head by adopting an RED-CHS mechanism, and enabling the communication cluster head to transfer information between a common node and a base station; then, according tothe virtual force field theory, determining the optimal positions of the anchor points in the cluster by adopting a VFF-AS algorithm, so that the charging requirements of the nodes in the cluster canbe considered; and finally, improving the ant colony system, using a PER-ACS algorithm to perform path planning and scheduling on the MCV, so that the moving path is optimal, the charging amount of the MCV to the node is adaptively adjusted according to the request condition, and the parking duration of the MCV at each anchor point is accurately solved. According to the PER-MTCS method provided by the invention, the optimal scheduling of the MCV is given, and the energy supply problem of the WRSN node is effectively solved.

Description

technical field [0001] The present invention generally belongs to the field of wireless rechargeable sensor networks, and specifically relates to technical fields such as network node clustering, wireless energy transmission, ant colony system intelligent calculation, path planning, and mobile scheduling. Background technique [0002] The traditional wireless sensor network (Wireless Sensor Network, WSN) is a multi-hop self-organizing network composed of a large number of low-cost micro sensor nodes, which has a wide range of applications in the fields of military investigation, health care, environmental monitoring, warehouse management and smart home. prospect. However, due to the small size of the WSN node and the limited battery capacity on it, the node often dies due to energy exhaustion. The method of extending the life of the network by replacing the battery is often inconvenient to operate, high in maintenance costs, and sometimes even not feasible at all, which ser...

AI Technical Summary

Problems solved by technology

However, with the expansion of the network scale and the increase of node density, the charging efficiency of this method is low, and it is only suitable for small-scale networks with sparse nodes.

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