Analysis And Optimization Design On Throughput Of Energy Harvesting Wireless Sensor Network

With the extensive research and application of Wireless Sensor Networks,the network lifetime has limited its further development.Wireless sensor nodes will eventually run out of energy due to battery power,and due to the wide range of characteristics of the monitoring area in its application areas,it is obviously unrealistic to replace batteries manually.The application of energy harvesting technology to Wireless Sensor Networks is to solve the problem of energy supply at these nodes.Nodes convert the potential energy in the deployment environment into the energy consumption of the electricity supply themselves.As long as the potential environmental energy is available,wireless sensor nodes can obtain continuous working capability.The advantages of this kind of Energy Harvesting Wireless Sensor Networks are obvious.As an emerging network technology,the research progress in all aspects is very limited.This is especially true for a class of Energy Harvesting Wireless Sensor Networks with linear characteristics which have a wide range of application scenarios,such as urban thermal network monitoring,petroleum pipeline network monitoring,and road or rail monitoring.For these types of networks,because their applications require monitoring data to be uploaded as quickly as possible,the throughput is a crucial performance indicator.The purpose of this paper is to analyze the throughput of Energy Harvesting Wireless Sensor Networks with linear characteristics and give a best possible optimization results.Since energy harvesting technology has a lot to do with the type of environmental energy,different environmental energy sources will have great differences due to different environmental conditions and even different time.This will make Energy Harvesting Wireless Sensor Networks have great uncertainty and randomness.The research content of this paper starts from the analysis of the theoretical upper bound of the throughput of Energy Harvesting Wireless Sensor Networks,fully considers this randomness,and is reflected in the process of node modeling,network modeling,and throughput modeling.Combined with the network topology characteristics,taking advantages of the structural features of the grid to assist in calculation of the related structural probabilities,the theoretical upper bound of relative throughput of Energy Harvesting Wireless Sensor Networks is deduced,and the benchmark for optimizing the throughput is obtained.Next,from the point of view of reducing the end-to-end delay as much as possible,a routing strategy to optimize throughput is proposed—Gradient Hierarchical Routing Protocol.Gradient Hierarchical Routing Protocol combines the linear topology characteristic of Energy Harvesting Wireless Sensor Networks to establish gradient stratification for network nodes,and then calculate the competition value by combining the remaining energy level,the energy harvesting level,and the position factor of the nodes.Then organizing nodes elect the Cluster Head node,those with higher competition values become Cluster Head nodes,and the data messages of the member nodes are collected by Cluster Head nodes each layer,and forwarded between the Cluster Heads in the direction of decreasing gradient,and finally received by the sink node.According to the definition of the gradient in this paper,this forwarding method goes through a minimum number of intermediate nodes and achieves the purpose of improving network throughput.Finally,the data of the node communication radius and the temperature difference characteristics of the urban thermal network is collected through the combined temperature difference energy harvesting module and the wireless sensor nodes.Under the OPNET simulation environment,the wireless thermal network scenarios,the node and the process model are established,and the Gradient Hierarchical Routing Protocol model is established.Verifying the validity of the protocol through simulation,and through simulation experiments to compare the combined parameters of Gradient Hierarchical Routing Protocol in terms of the optimization of the throughput.According to the simulation results of other routing methods can be seen that the Gradient Hierarchical Routing Protocol has a better performance on throughput performance.In this paper,theoretical analysis and simulation experiments are combined to give a theoretical upper bound on the throughput of Energy Harvesting Wireless Sensor Networks.At the same time,a routing strategy for effectively improving the throughput of linear Energy Harvesting Wireless Sensor Networks is proposed,which has a general guiding significance for practical network application scenarios.