Data Processing And Data Transmission Technology In Wireless Sensor Network (wsn) Research

Wireless Sensor Networks (WSNs) is a low-cost, low power, distributed multi-hopself-organized networks. It’s a cutting-edge of research filed started recent years homeand abroad. The study includes wireless communication technology, embeddedtechnology, sensor technology, distributed processing technology and MEMStechnology. Wireless Sensor Networks has a great application prospect and practicalvalue in military, environmental science, health care, industry, business and so on. Inthe Business Week’s report of the future technology predictions, WSN is listed as themost influential21inventions in the21st century. MIT lists WSN as one of10keytechnologies that change the world. For “Internet of things” which is one of50inventions evaluated by Time magazine, is treated as the future research direction ofWireless Sensor Networks.Wireless sensor network is a new information acquisition platform. By usingwireless multi-hop transmission method, WSN’s nodes that scattered on observationenvironment transmit monitoring information back to Sink. Wireless sensor networksand traditional networks have lots of differences. Wireless sensor network havecharacters such as data collection-centric, limited energy of nodes, applicationcorrelation, so there’s many key research challenges such as topology control,network protocols, data collection and processing, application system. In this thesis,our main research interests, based on environmental monitoring application, focus onkey research challenges such as data processing and data collection. Our goal is toreach network energy-efficiency.Data processing is a fundamental and key challenge in wireless sensor networks, itusually processes the data reported by nodes, from fused, compressed data to reducenetwork transmission and save network energy. This paper’s research based onenvironmental monitoring, aim to use contour mapping processing technology intowireless sensor network. The main research contents and contributions of this thesisare as follows: 1. Discusses problems and challenges of data processing and data collection inwireless sensor networks.2. Aiming to the energy-constraint problem in environmental monitoringapplication, we propose a contour mapping scheme based on least-square Bezierfitting which used in wireless sensor networks. This scheme focuses on the curvefeature of contour lines. By using Bezier curves fits contour lines, this schemeprocesses data form data source, reduces the amount of nodes’ data, and thenreduces network energy consumption efficiently.3. In the analysis of wireless transceiver modules,and realized that this is themajor energy consumption of wireless sensor network, while noticing theshortcomings of LS that LS brings data accumulation will forming Bezier curves.This paper introduces a novel energy-efficient contour mapping scheme based onLS-T algorithm, and named this algorithm SENS-T. SENS-T takes the thought thatBezier curve is calculated on each node before transmission, so it restraints theamount data of Bezier curves segment, and further reduces network traffic. Bycomparing existing methods, SENS-T achieves the same monitoring accuracy whilereducing45%of the network energy.Data transmission technology is also one of the key research challenges ofwireless sensor networks, our work also studies routing and data collectionprotocol of wireless sensor networks, and the main research contents andcontributions of this thesis are as follows:1. In the combination of the features of geographic routing and energy gradientrouting, this paper presents a routing strategy based on vector synthesis named ED.this strategy constructs a directional unit vector by using node in the direction ofpointing Sink. According to the residual energy of neighboring nodes around thenode, this strategy establishes an energy unit vector. After these two unit vectors areweighted, the next hop routing node is calculated. This strategy considers thedirection of data streams while taking into account the energy consumption of thenetwork. Comparing whit existing methods, our test proves that it reduces thenetwork energy consumption while balancing energy consumption of sensor networks.2. Aiming to the problem of the nodes that close to Sink are always shoulderexcessive energy consumption, the paper design a rotation-type transmissionmethod. While nodes using time synchronization, nodes adopts intermittent sleepway to fulfill the mission of energy consumption reduction of nodes that next toSink and balances the network energy consumption.