A data fusion collection method based on unequal cluster sensor network

Abstract

The invention discloses a wireless sensor network data fusion collection strategy based on unequal clustering, which is characterized in that the previous strategy is improved and optimized according to the requirement of fast network-wide data aggregation in the wireless sensor network. The method of the invention provides a clustering network with a large cluster radius in the far base station area and a small cluster radius in the near base station area; and proposes a corresponding unequal clustering network data fusion collection and scheduling algorithm. Inter-cluster data collection) to complete data fusion collection. The unequal clustering structure proposed by the present invention can shorten the time required for data aggregation collection and improve the speed of data aggregation; at the same time, since each cluster head node starts its data transmission immediately after completing the data aggregation in the cluster, the It only takes 1 time for the state transition, while the previous strategy requires 2 times (one time from the sleep state to the working state for data collection in the cluster, and then to the sleep state, and then wakes up again when the cluster head data is sent, and the cluster head data is collected. send). Therefore, the method of the present invention can reduce one state transition, thereby reducing energy consumption and improving network life.

Description

technical field [0001] The invention relates to the field of wireless sensor network data collection speed and energy saving, in particular to a data fusion collection method based on unequal clustering in the sensor network. Background technique [0002] TDMA scheduling is a widely used and highly efficient MAC layer protocol. In the previous research on scheduling algorithms, most of them focused on shortening the scheduling time or using distributed methods to realize these two aspects. [0003] Many-to-one scheduling has been addressed in previous studies. In the early research, an evolutionary algorithm integrating genetic algorithm and particle swarm algorithm was proposed to improve the search ability; a heuristic algorithm was proposed to increase the ability of parallel transmission by scheduling as many independent parts as possible. [0004] Liqi Shi et al. proposed a cross-layer optimization strategy to achieve high energy usage efficiency and low latency in wi...

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Problems solved by technology

[0008] The purpose of the present invention is to provide a data fusion collection method based on unequal clustering in sensor networks to solve the problems of large network delay and low energy use efficiency in existing clustering network protocols

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