Compressed sensing technology-based construction method of data gathering tree with high-energy efficiency

Abstract

The invention provides a compressed sensing technology-based construction method with high-energy efficiency data acquisition tree. The construction method comprises the following steps: step one, converting transmission cost into of one side of data in a network into a null normal form of a transmission vector of a corresponding node by using a transmission matrix R, dividing the node into different levels according to distances between the node and sink node, constructing a minimum transmission gathering tree by using an iteration way according to a principle of a level sequence from far to near so as to minimize the transmission cost of the data in the network; and step two, adjusting the structure of the minimum transmission gathering tree to realize a load balance of the node in the network, thereby prolonging the network survival time. According to the invention, the data gathering tree construction algorithm is brought forward and the data transmission cost and network survival time in the network are taken into consideration comprehensively, so that the number of bottle neck nodes can be effectively reduced on the premise that the transmission cost is not increased obviously, the network survival time is effectively prolonged, and the balancing between the transmission cost and the network survival time is realized.

Description

technical field [0001] The invention relates to a method in the technical field of wireless sensor networks, in particular to a method for constructing a data collection tree with high energy efficiency based on compressed sensing technology. Background technique [0002] An important application of wireless sensor network is to monitor the environment. In this application, the basic operation in the network is to collect data, collect the data sensed by each sensor node and transmit it to the sink node for data processing. Due to the particularity of monitoring applications, a large amount of data needs to be collected and stored in the network, and transmitted to the sink node, which consumes a lot of energy. Since nodes in sensor networks are generally powered by batteries, energy efficiency is a crucial issue in a sensor network. At present, there are many technologies to study energy efficiency in sensor networks, and compressive sensing technology used in the data col...

AI Technical Summary

Problems solved by technology

[0009] Considering that in each iteration of the MTT algorithm, all nodes that have not been added to the data acquisition tree are considered, and at the same time, when calculating the additional cost of each newly added node, all nodes that have been added to the data acquisition tree need to be considered, so the calculation amount is relatively At the same time, because the algorithm does not consider the load balancing status of nodes, it will lead to some bottleneck nodes, which will affect the network survival time

Images