Sleep scheduling method and system for energy acquisition sensor network

Abstract

The invention discloses a sleep scheduling method and system for an energy acquisition sensor network. The sleep scheduling method comprises the following steps: predicting an energy acquisition amount at a corresponding moment of the next day according to historical data of energy acquired by each node in a network monitoring area, and establishing an energy value matrix X; dividing all energy acquisition sensor nodes into K K-means clusters in each time quantum according to the predicated energy acquisition amount; sequencing the K-means clustering nodes according to the ranges of the energy acquisition values from small to big, and preferentially awaking the K-means clustering node with the smallest clustering center value on the premises of set sleep scheduling period and coverage requirements. The sleep scheduling method and the sleep scheduling system have the capability of well utilizing the energy acquired from outside, especially adapting to a situation that energy of nodes in an energy acquisition sensor network is limited, and is particularly applicable to a sensor network for field monitoring.

Description

technical field [0001] The invention relates to the technical field of sensor networks, in particular to a sleep scheduling method and system for an energy harvesting sensor network. Background technique [0002] Energy harvesting technology is a hot spot in the field of wireless sensor network development in recent years. The energy that can be collected includes light energy and wind energy. Due to the interference of many factors, there are many uncertainties and instabilities in the energy harvesting process, and it is difficult to match the energy that the nodes need to use. At the same time, the amount of energy obtained is also limited, and it cannot fully guarantee that nodes can use the obtained energy indefinitely. Therefore, when designing various algorithms and applications, people still need to optimize the use of acquired energy, master the law of energy acquisition, rationally allocate acquired energy, and improve energy use efficiency. [0003] As an effect...

AI Technical Summary

Problems solved by technology

[0004] Existing dormancy scheduling methods are mainly aimed at sensor networks without energy acquisition. Although these methods can effectively extend the network life cycle, they do not consider the randomness of energy arrival and the optimal use of the energy obtained.

Few dormant scheduling methods involve energy harvesting sensor networks, but do not focus on the relationship between the energy harvested by nodes

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