Optimization method for survival time of multi-Sink-node movement wireless sensor network

Abstract

The invention discloses an optimization method for the survival time of a multi-Sink-node movement wireless sensor network. The optimization method comprises the steps that (1), a gateway node collects position information of Sink nodes and sensing nodes, and dump energy information of the sensing nodes, and a monitored area is divided into grids of the same size; (2), the potency value of each grid is calculated; (3), all anchor points where the Sink nodes need to remain are calculated to obtain an anchor point set; (4), anchor points in the anchor point set are distributed to M clusters, and the Sink nodes are distributed to the corresponding clusters; (5), the shortest movement path along which the Sink nodes distributed to the corresponding clusters pass through all the anchor points in the clusters is calculated, and is broadcast and informed to the corresponding Sink nodes; (6), all the Sink nodes collect data of the sensing nodes at the same time along the respective shortest movement paths; (7), after data collection of one time period is completed, dump energy information of the sensing nodes is collected again, and if energy of the sensing nodes are used up, the process ends, or, the step (2) is carried out.

Description

technical field [0001] The invention relates to a network survival time optimization method, in particular to a wireless sensor network survival time optimization method in which multiple Sink nodes move. Background technique [0002] Wireless sensor networks (WSNs) usually contain a large number of sensor nodes. These sensor nodes collect various data in the monitoring area, and send the data to the sink node for further processing through multi-hop. They are usually used in the monitoring of indoor / outdoor environment, sanitation and health, electricity, inventory location, factory and process automation, earthquake and structure, and the tracking of targets such as animals, humans, and vehicles, and are increasingly popular in the industry and The attention of academia has enormous potential to enhance and transform how people interact with the world. In wireless sensor networks, the network lifetime is one of the most important indicators to measure the performance of ...

AI Technical Summary

Problems solved by technology

However, the underwater wireless sensor network has the following problems: there is also the energy hole problem; the water surface gateway must communicate with the underwater sensor node and the sink node, which consumes more energy

The wireless sensor network lifetime optimization method with fixed node positions Assuming that the node positions are fixed, the sensor nodes distributed around the Sink nodes can easily become hub nodes, which receive and forward more neighbor node data and consume less energy. Large, limited network lifetime

No matter how you adjust the algorithm, there will always be unbalanced distribution of energy consumption of nodes in the monitoring area, and the problem of energy holes will appear

Many wireless sensor network survival time optimization methods about the movement of a single sink node only consider moving the sink node to the position of the sensor node to collect data

This method limits the selection range of the sink node's stay position, and the result obtained is a local optimal solution, which has certain limitations.

Since the wireless sensor network survival time optimization method for the movement of a single sink node only considers the movement of one sink node, and the sink node needs to collect the data of all sensor nodes, so its moving path is long and the network delay is large

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