Research On Data Compression Algorithm Using Wavelet In Asynchronous Wireless Sensor Networks

Wireless sensor networks have been the targets of active research in the recent past due to their military and civil applications. Differentiating from traditional networks, WSN are very resource constrained. In view of the main tasks for WSN are to collecting information from areas under surveillance, it is an important issue to save communication energy meanwhile ensure the sampled data reliable. Medium access control(MAC) protocols are the basis of communication for each node, therefore researching protocols are dramatically significant for relieving collisions and filtering redundant,so that to reduce communication energy. Data compression is also one of important method to reduce energy. This paper mainly opens out the research based on the MAC protocol of the asynchronous communication mode and the compression algorithm using wavelet base on this MAC protocol, with the follow production:Firstly, this paper proposes a concept of asynchronous communicaton mode, based on the feasibility of low-power asynchronous communicaton module. In allusion to the possible effects on each-layer protocol and global performance of wireless sensors networks from the asynchronous mode, it has designed an asynchronous MAC protocol using peridical awake-sleep, partial time-synchronization and interactive-confirmation ACK mechanism etc. Then based on the data-correlation and actual-demand of wireless sensors networks, the peridical awake-sleep mechanism mainly include two different kinds of mechanism, which are sequential-awake and interleaving-awake. With the system simulation, experimental results show that the MAC mechanism is good at energy-saving in the low-ratio scene .Secondly, The data sensor node collected normally have Multiple-modalities pertinence. Multiple-modalities pertinence refers to the different types of data which the same node sampled have some correlation. A adaptive multiple-modalities data compression algorithm using wavelet was designed. In a given threshold of the correlation, the data can be adaptive classified using this algorithm. the relevant data can be estimated using the least square estimation. And then the characteristics data are abstracted as a matrix, then we can exploit the spatial and temporal corrections using wavelet transform. Theoretically and experimentally, the proposed algorithm can effectively exploit the correlation of the data, the compression ratio of the algorithm has improved. Effectively, it can provide a significant reduction in energy consumption.Thirdly,A simulator named VWSN is designed and developed based on open source OMNeT++ framework.VWSN mainly aims for asynchronous communication, building whole protocol stack from physics to application layer, universal interfaces between layers are provided also can be applied to synchronous-based WSN. VWSN employs two methods to enhance scalability and reduce simulation runtime, i.e., virtual mote mechanism and filtering square based interference computing algorithms. Simulation results show that VWSN has good accuracy, is able to provide efficient evaluation methods for protocols or algorithms researches in large scale WSN.