Adjustment method of heterogeneous wireless sensor network nodes based on multiple covering

Abstract

The invention discloses an adjustment method of heterogeneous wireless sensor network nodes based on multiple covering. Parameter adaptive and self-regulation binary difference algorithm is adopted, multiple covering is performed to hot spot regions where monitoring targets appear frequently in situations that heterogeneous distribution of the monitoring targets, isomerism of scheduling node perceived radiuses, energy and work period consumed energy are taken into account, and basic covering are kept for other regions, the monitoring quality of the targets is effectively improved, the quantity of active nodes and the fault tolerance of a monitoring network are simultaneously reduced, and the energy consumption of the nodes is reduced. The method is based on the binary difference algorithm to optimize the node state, simultaneously adopts a periodic interception / sleeping mechanism and a sleep wake up mechanism, ensures that heterogeneous nodes can excellently accomplish detection task in monitoring occasions where targets are not uniformly distributed, and simultaneously prolongs the network life cycle and reduces the network energy consumption.

Description

technical field [0001] The invention relates to the wireless sensor network technology in the modern communication system, in particular, it is a multi-coverage-based heterogeneous wireless sensor network node scheduling method. Background technique [0002] In sensor networks, since the energy carried by the nodes themselves is very limited, how to prolong the working time of the network as much as possible under the premise of making full use of energy has become a key issue in wireless sensor networks; at the same time, due to the high density deployment of nodes in the monitoring area, a On the one hand, the monitoring areas of the nodes overlap with each other, which makes the obtained data highly correlated. On the other hand, the nodes compete with each other for channels, which makes a large number of data packets collide. Node scheduling is an effective method to optimize the energy efficiency of wireless sensor networks based on application requirements. By contro...

AI Technical Summary

Problems solved by technology

However, the particle swarm optimization strategy is prone to "premature" when searching the solution space, which has an adverse effect on the node state optimization, and when using this algorithm, the search space will increase with the optimized vector dimension; the optimization based on genetic algorithm covers several Although the basic difference algorithm has the characteristics of simple optimization process, few controlled parameters, and outstanding global optimization performance, it lacks the robustness to the selection of initial parameters. Whether the selection of parameters is appropriate will greatly affect the global optimization ability

Images