Research Of The Edge Detection Technology In Wireless Sensor Networks

Wireless Sensor Network (WSN) is made up of a large number of sensor nodes which deploy in a monitoring region. The sensor nodes within the region construct a multi-hop Ad hoc self-organization network system through wireless communication. They sense, collect and process environment data, and send the corresponding data to user. Because of the sensor nodes need to complete the task of collecting, processing, storing and communicating, and they are only supported by the battery, if the energy is depleted, the sensor nodes will stop working. This will cause the reduction of monitoring region or the appearance of holes. This phenomenon means data lost or monitor distortion and so on in WSN.Edge detection of WSN is one of the key supporting technologies to achieve Quality Service application in wireless network. Edge detection is very important in coverage detection, route structure and outline detection. This paper mainly studies the edge detection algorithm for WSN. The research achievements are:(1) In order to solve the problem of energy consumption in multi-hop which exist in distribute information detection algorithm, a distribute edge detection algorithm based on circle research is proposed. This algorithm constructs distance-quadrant table between neighbor node and detected node and uses the quick research algorithm to detect the edge node by using neighbor node topological structure and basic perimeter coverage principles. Experimental results show that the algorithm works well in the detection of precision, efficiency and the reduction of energy consumption.(2) In order to solve the problem of energy consumption in distribute algorithm and the mistake detection in MoSBoD algorithm, an improved algorithm based on MoSBoD is proposed. This algorithm is able to collect data which consume too many energy without nodes' positions and flood. The sink is equipped with a Wireless communication module and a sectored directional antenna to locate the farthest node with anticlockwise, and then determine the edge node with clockwise methods. Experimental results show that the improved algorithm has higher precision and lower mistake rate and miss rate than MoSBoD.