Research On Data Compression Algorithm In Wireless Sensor Network

Wireless sensor network (WSN) is comprised of many micro sensor nodes. These nodesare deployed in environment system and they perceive, collect and process the environmentinformation by wireless communication way, multi-hop form, self-organization forming localarea network, and then send the processed information to the base station (or control center).The wireless sensor network covers the network computing, intelligent storage, wirelesscommunication, sensor technology and other fields, and become an advanced networkresearch field. Wireless sensor network is usually deployed in adverse circumstances, difficultto reach regional, and which leads to the limited whole network energy. In this case itinevitably leads to us looking for the way that the network energy consumption less andeffectively prolong the network life cycle.This paper mainly studies the data compression technology in wireless sensor network, andresearch effectively reduce the amount of data transmission and improve precision of datacompression algorithm. We start with the background and significance of the subject,summarize the relevant knowledge and basic content of wireless sensor network, and discussseveral classes wide application of data compression method in wireless sensor networkincluding application idea, range, advantages and disadvantages of the different kinds ofalgorithms. To effectively reduce the data transmission and improve the data precision of datacompression purposes, the proposed algorithms in this paper are given.At first, we propose one lossy data compression algorithm which is based on the idea of DP,optimal curve data compression algorithm in wireless sensor network, the algorithm isselected the cluster-head which can reflect the systematic characteristics of the data as thefeature points to transmit. This can effective release node limited memory space. Thesimulation results demonstrate that the algorithm has better extraction efficiency featurepoints for volatile data.Then it puts forward data aggregation compression algorithm in wireless sensor network.The algorithm improved ODLRST compression algorithm and is undistorted datacompression. In the algorithm, we consider various possible trends of the monitoring datathrough accuracy and precision of the predicting data two aspects to project the discontinuous point determination of the monitoring data and data trend prediction. And what’s more, thealgorithm does not need to set the threshold, and it can be used to monitor any environmentsand has good performance and very strong practical applications.Finally, we put forward a kind idea which is different with the traditional sense ofcompression to environmental monitoring state and judging thought, two unbiased greyMarco prediction in wireless sensor network state determination. The method is firstlyforecasted of data, then transmit state identification that meet the purpose of monitoringaccording to Marco forecast thought on monitoring data state judgment. The simulationresults show that the method could be predicted accurate data and state judgment, and caneffectively reduce the network data transmission amount, thereby reducing the energyconsumption for data transmission.