Optimization Strategy Of LEACH Routing Protocol Based On Energy Balance And Efficiency

With the advent of the information technology era,the Wireless Sensor Network(WSN),as a new type of network technology,has attracted the attention of domestic and foreign researchers.Different from traditional networks,WSN combines wireless sensing technology with traditional network technology and has wide application in all aspects of real life.WSN is mainly composed of various sensor nodes scattered in the monitoring area.Its characteristic is flexible and wide application range,low application cost,and wireless.Due to the wireless nature of the sensor nodes,energy is not continuously supplied to the nodes,and the WSN's routing design focuses on power issues.The low power adaptive clustering routing protocol(LEACH)is known as one of many important routing protocols in the WSN.Many clustering routing protocols are based on its improvements,such as the PEGASIS protocol and HEED protocol.The LEACH protocol divides the network transmission time into continuous time periods.Each cycle is divided into a route establishment phase and a network transmission phase;a cluster-head is selected in each cycle,then the network is divided into clusters.However,each cycle of the LEACH routing protocol randomly selects cluster-heads using thresholds.It does not consider the energy consumption and geographical location of cluster-heads.It is easy to cause nodes with low energy and poor geographical locations to be elected as cluster-heads;and LEACH protocol is only applicable to network scenarios where nodes and base stations can communicate data directly between nodes.This paper proposes a LEACH routing protocol synthesis optimization strategy based on energy balance and high efficiency.In this strategy,two directions of improvement are divided into intra-cluster and inter-cluster routing protocols.In the intra-cluster direction,for the random selection of cluster-heads in the LEACH routing protocol cluster,the spacing factor,residual energy factor,and node density factor are added to optimize the threshold formula.In addition,in the application of different WSN,weighting factors are introduced based on the effect of remaining energy and geographical location on the selection of cluster-heads.An algorithm for controlling the weighting factor by a dichotomy is proposed.Moreover,a temporal dynamic function is constructed and an algorithm for dynamically adjusting the weighted value of the remaining energy factor is proposed.For the inter-cluster routing protocol,the research method of the optimal number of cluster-heads is given.Moreover,the node energy consumption function and the shortest forwarding distance are introduced,and the best method for node entry and the routing protocol for data transmission between cluster-heads are found.Through MATLAB simulation experiments,the improved algorithm effectively saves the network energy consumption and slows down the rate of node depletion.The specific content is as follows:(1)For the LEACH protocol,the cluster-head is selected through the threshold,and the residual energy factor,spacing factor,distance factor and weighting factor are added by adopting the method of improving the threshold formula.The location and energy conditions of the candidate nodes are comprehensively considered.(2)It has been verified through experiments that the density factor has different importance in different experimental scenarios.Therefore,according to different network environments,simulation experiments can be conducted to obtain the best weighting value of density factor.In the experimental of this paper,the weighted value of the optimal density factor in this experimental scene is obtained through experiments.(3)For the weighted value of the remaining energy factor,a dichotomy is innovatively proposed.Divide the remaining energy of the node into two,and give an improved algorithm to adjust the weighted value of the remaining energy factor.Dichotomies were compared with the constant value method.However,the disadvantage of the dichotomy is its low energy sensitivity.(4)Aiming at the shortcomings of the dichotomy,the temporal dynamic function is constructed,and an algorithm for dynamically changing the weighted value of the remaining energy factor is proposed innovatively.In this algorithm,as the time of network information transmission progresses,the weighted value of the remaining energy is dynamically adjusted so that the sensitivity of the weighted value of the remaining energy factor is higher.(5)The number of cluster-head has a great impact on network performance.The optimal cluster-head ratio algorithm is given and its accuracy is verified through experiments.(6)The energy consumption function is introduced,and the optimal clustering scheme for nodes is given.For the data transmission algorithm from cluster-head to base station,the shortest forwarding path is introduced,and the more appropriate transit hop number for data transmission between cluster-heads is obtained.