Wireless rechargeable sensor network charging scheduling method based on quasi-arrays

Abstract

The invention discloses a wireless rechargeable sensor network charging scheduling method based on a quasi-array, and the method comprises the steps: S1, checking the charging request information, andbuilding a corresponding weighted quasi-array model according to the residual energy, the energy consumption rate, and the forwarding data volume of a request node; s2, according to the established weighted quasi-matrix model, dividing the request nodes into two types, namely an advance node and a delay node by adopting a greedy algorithm; and S3, respectively determining scheduling sequences ofthe two types of nodes, and preferentially ensuring that the advanced node can be charged in time, thereby obtaining a final scheduling sequence. The method can be applied to the charging scheduling problem of different request concurrence quantities; under the condition of high concurrency, the greedy algorithm is adopted to preferentially charge the node with high forwarding quantity, so that the influence of dormancy of the node on the network topology due to the fact that the node cannot be charged in time is reduced to the maximum extent, the influence on the network energy consumption due to the change of the network topology structure is reduced, and the network performance is improved.

Description

technical field [0001] The invention relates to the field of wireless rechargeable sensor networks, in particular to a charging scheduling method for a wireless rechargeable sensor network based on a matroid. Background technique [0002] The wireless sensor network is composed of a large number of small and low-cost sensor nodes deployed in the target monitoring area, and forms an ad hoc network system through wireless communication to monitor and collect various environmental information in the coverage area. At present, wireless sensor networks play an important role in various applications such as environmental monitoring, smart home, smart transportation, military defense, and target tracking, especially in areas that are difficult to reach or in harsh environments. However, the energy limitation of sensor networks has become the biggest obstacle to its large-scale application. Sensor nodes are usually powered by batteries with limited energy, and the deployment environ...

AI Technical Summary

Problems solved by technology

The node located in the center of the network forwards a large amount of data. If it cannot be charged in time and enters a dormant state, it will not forward data, which will affect the topology of the network and increase the energy consumption of the data transmission of its last hop node, thus increasing the network capacity. total energy consumption

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