Research On Time-efficient Data Collection Schemes In Wireless Sensor Networks

Wireless Sensor Network(WSN)technology is one of the key technologies in the Internet of Things perception layer.It is a bridge between the computer digital world and the human physics world.In 2017,Chinese wireless sensor network market totaled reached more than 44.67 billion yuan.In recent years,wireless sensor network technology has been widely used in industrial production,environmental monitoring,smart home and smart city scenarios.The timeliness of its information collection mechanism also directly limits the response speed of ap-plications.This paper focuses on the challenges of sensor node energy limitation,low wireless link transmission capability,large number of nodes,and high dynamic performance in wireless sensor network systems.Based on the investigation of existing methods and research results,based on the differences of application scenarios,the dynamic duty cycle adjustment mechanis-m based on aging energy balance,the congestion control mechanism based on network utility maximization and the change based on slot state The estimation mechanism of the number of ab-normal nodes in the category to improve the timeliness of the wireless sensor network informa-tion collection mechanism.The specific research contents and innovation points are summarized as follows.Dynamic duty-cycle scheme based on the tradeoff between timeliness and energy consump-tion:For reducing the transmission energy consumption of the sensing layer,we mainly studied how to reduce the transmission energy consumption under the premise of ensuring the network end-to-end delay in the wireless sensor network.We have found that opportunistic routing proto-cols in wireless sensor networks are superior to unicast routing protocols in terms of improving network throughput and reducing network delay.At the same time,since the node consumes a lot of energy when it wakes up,whether it is idle,sending or receiving data.Reducing the number of waking up time slots can reduce the energy cost of the system.Therefore,we pro-posed a new dynamic duty cycle scheme in the opportunistic routing network.By formulating the functional relationship between the number of wake-up time slots and the end-to-end delay,we can get the trad off of the number of wake-up time slots and end-to-end delay.In solving this problem,the whole problem can be separated into the single-hop delay control problem by decomposing the end-to-end delay requirement.Then we use the feedback controller to find out the approximate optimal solution.Compared with the dynamic duty cycle scheme in unicast routing network,the transmission scheme of this is superior to the above method in controlling the end-to-end delay and reducing the transmission energy consumption.Congestion control scheme based on network utility maximization:In terms of improving the transmission throughput of the sensing layer,this paper mainly studies how to improve the throughput in high-rate applications.Due to the wireless characteristics of the IOT sensing layer,the transmission capacity of the link is limited and it is difficult to predict on-the-fly.Therefore,how to maximize the actual throughput of the system becomes a difficulty.So we combine the network utility problem and congestion control mechanism to allocate the transmission rate of each node.At first,we maximize the utility of one-hop nodes to the sink without the knowledge of the capacity of the links.Then we use the congestion control scheme based on the PRR to allocate the multi-hop nodes.With this method,we can not only maximize network utility,but also achieve fairness of each node based on the selection of the utility function.At the same time,it can improve the overall throughput of the system to meet the actual requirements of high-rate applications.Compared with the traditional utility maximization algorithm,it can be seen that our method can maximize the utility of the network,and it also improves the overall throughput of the system.Multi-category abnormal nodes cardinality estimation scheme based on framed slotted alo-ha:For large-scale long-term deployment scenarios,wireless rechargeable sensor networks have become a hotspot in recent years.However,since the current wireless rechargeable wireless sen-sor network adopts a master-slave communication mode,the system signal conflict is severe,and the channel bandwidth is very limited.The existing information collection mechanism is propor-tional to the number of nodes and cannot meet the high timeliness requirements of the system.Considering the number of abnormal nodes can be used to determine the degree of abnormality of the current system to reduce the amount of data transmitted from the sensing node to the sink node.This is based on a transmission mechanism of sampling ideas.Through the method of probability and statistics,the mathematical relationship between real data and observed data is established.Under the premise of ensuring certain precision,the execution time of the protocol is minimized by optimizing the parameters.In particular,considering multiple categories of information at the same time improves the timeliness of the information collection mechanism in the case of multiple users or multiple sensing nodes.At the same time,through the dynamic culling strategy,the transmission of useless information is reduced.Compared with the existing agreement,the protocol greatly improves the timeliness of the system,while collecting informa-tion to ensure a certain accuracy.