Research On Multi-objective Routing Optimization In Wireless Sensor Networks

Wireless Sensor Network(WSN)consists of a number of sensor nodes placed in the monitoring area.These sensor nodes cooperate with each other to collect monitoring information to the base station.With the development of information technology,wireless sensor networks have been widely used in agricultural irrigation management,military intrusion monitoring,industrial control and other fields.The energy supply of traditional wireless sensor networks usually comes from batteries,and its capacity is very limited.Therefore,how to reduce the energy consumption of nodes and maximize the lifetime of networks has always been a hot issue in the research of wireless sensor networks.With the development of energy acquisition technology,it is possible for the network to run indefinitely by equipping nodes with energy collection devices such as solar cells and thermoelectric cells.However,energy collection in the environment is random and uncertain,so it is necessary to design a routing that can be applied to energy-gathering wireless sensor networks.In this thesis,a multi-hop data forwarding algorithm considering energy consumption and delay is proposed for wireless sensor networks powered by solar cells and storage batteries.The algorithm divides the monitoring area of the network and the communication area of the nodes.By selecting the appropriate next hop forwarding node from the appropriate area for each sensor node,the transmission path from the data source node to the base station is formed.In order to reduce the energy consumption and delay in the network,a multi-objective integer programming model for selecting the next hop data forwarding node is established.In order to solve this NP-hard problem,we adopt multi-objective particle swarm optimization(MOPSO)algorithm,and eliminate the bias problem of population particle renewal when two target orders of magnitude are inconsistent by using the improved maximin fitness function.The non-dominant solution with closer distance is screened by using the method of ?-domination,which increases the diversity of population particles and makes the particle arrangement more uniform.Considering that the decision variables are all integers,we restricts the evolution of particles in the integer space by taking the initial position and velocity of particles as integers,so that the value of each particle is still integer after updating.Eventually we got the Pareto front.We take several solutions from Pareto frontier and use MATLAB to carry out simulation experiments.The simulation results of MATLAB show that by changing the transmission power level according to the node power,the network performance can be improved when the energy is sufficient,the network delay can be reduced,the energy overhead can be reduced when the energy is insufficient to prevent the node power from being too low,and the individual can be avoided because of the uneven energy consumption of the network.Node power is exhausted.The routing algorithm proposed in this thesis is suitable for wireless sensor networks powered by solar cells and storage batteries.It can adapt to the energy changes in the network and make full use of the energy obtained.