Research On Key Technology Of Wireless Sensor Network In Big Data Environment

Big Data analysis and application of wireless sensor network can be utilized in various circumstances.We are now living in an era of information explosion,which numerous,diversified information gathers and forms important parts of people's life,entertainment and work.The vast amount of information needs to be collected,analyzed,dealt with,stored,transmitted and used with the help of computer.As the wireless sensor network application will be spread rapidly and used widely,its network data is certainly to boom and form a special type of big data.So,it is necessary to study key technologies of wireless sensor network in big data environment as below:1.The data source detection algorithm is studied for wireless sensor network in big data environment.Wireless sensor network is widely applied in various complex “data source” environments.The wireless sensor network senses the monitored targets in the region in real time,gets different kinds of data and transmits them to terminal users via transmission methods such as wireless communication,which facilitates the terminal users to acquire various data and information of every target within monitoring region.In this essay,Logical Regression Fusion Algorithm(LRFA)is proposed via the study and analysis of Logical Regression Fusion Rule(LRFR)for detecting the target of wireless sensor network,so that the accurate data source as needed can be transmitted on time via wireless sensor network.Experiments have proved the calculation of LRFA is simpler and it can improve the system performance with relative low calculation complexity.2.The time synchronization algorithm of the wireless sensor network is studied and GTS Global Time Synchronization is proposed.The big data of wireless sensor network needs effective support from basic data.Timing synchronization is required for all nodes of the whole network in various application situations of wireless sensor network,such as locating,tracking,data collecting,gathering,task distributing and coordinating etc.In most application environment,the wireless sensor network is powered by passive battery.In order to save energy for wireless sensor and extend efficient working time,dormant state is utilized in some periods to reduce energy consumption of nodes.Before operating,the wireless sensor is wakened on time according to certain regulations,which also requires the times of all nodes are accurate and synchronized.A set of new time synchronization agreement according to data analysis is proposed,namely,Global Time Synchronization(GTS).This algorithm is based on two different algorithms of one cascading to handle global timing: one deals with efficiency and the other deals with accuracy.Together,they achieve the timing synchronization in wireless sensor network environment.Experiments show that GTS has the properties of simpler algorithm,less space accumulation and high accuracy.3.Gravitational field route strategy in complex network environment is studied.Confidence coefficient is introduced to evaluate reliability of route patency rate,which consider the communication condition of all nodes from over all routes perspectives.On this basis,all nodes and the gravitational conditions of certain route under confidence coefficient are taken into account and an improved strategy for gravitational field route is proposed.In order to evaluate the transmission capability of route strategy,a command figure is introduced to measure the network handling capacity.Measuring the critical value from free flow condition to congest flow condition,this strategy has greatly increased the network handling capacity in single time unit compared with traditional shortest route strategy and unimproved gravitational field route.This can effectively balance the data load within network and ensure all nodes in the network to be utilized effectively.4.Bandwidth decompression method based on balanced genetic algorithm during equal network big data communication is proposed,which improves the transmission channel of wireless sensor network.In traditional equal network communication,point-to-point channel transmission is usually applied,in which point-to-point server only functions as a link rather than flow controller.This can easily lead to full occupation by huge data immediately when transmitting big data,which leads to high bandwidth occupation and low efficiency.Bandwidth decompression method based on balanced genetic algorithm during equal network big data communication is proposed,which is also suitable for wireless sensor network environment.By balanced genetic algorithm,a primary group is made of all the individuals in the network environment(i.e.the wireless sensor nodes in the network environment),thus calculations are operated for individuals in the group,such as choice,intersection and aberrance,to gain the proper management of bandwidth data during communication.This can realize the bandwidth decompression in big data network communication.Experiments show this algorithm can transmit huge data in short time and improve the bandwidth efficiency,which meet the practical need of big data communication.5.Data analysis technology of big data in wireless sensor network environment is studied.Solutions and frameworks based on ETL Agreement are proposed.Big data in wireless sensor network environment needs to be analyzed,stored,released and transmitted,extracted value so as to fully show the value and functions of big data in various fields.According to practical needs,actual problems in applications are particularly solved as information source collection,gathering,storage,management and sharing.This can be technical support for the extraction,transformation,exchange and loading sections of big data of various resources.The practical system application proves the practicability of the ETL technology,which can provide effective solutions for the value extraction,exportation and releasing of big data.