Study On Acquisition Query Techniques Based On Teams In Wireless Sensor Networks

Wireless sensor network techniques have been promoted by the development of sensor technique, wireless communication technique, micro electronic technology, and increasing maturity of micro electronic mechanism system. Wireless sensor networks have been successfully used in various application areas and they have a bright future for its extensive uses. However, most applications of wireless sensor networks are largely limited by finite battery energy. Therefore, consuming large amounts of energy to transmit the full sensing data for most applications is impractical. To address this issue, this thesis proposes an acquisition query technique, which is based on the teams of the historical data to reduce the transmission of data, so as to achieve the purpose of saving energy.The thesis discusses acquisition queries based on constructing teams from historical data. Energy and lifecycle are core factors in the wireless sensor networks due to limited energy of the wireless sensor networks. The data which is collected by wireless sensor nodes often has relevance with the time and space. Furthermore, considering the data's value only, there is strong similarity between different sensors'change trend. Based on the above considerations, in this thesis, attributes are first classified into teams according to their similarity. Each team is then mapped into a forest. This thesis proposes two forest-based aggregation techniques, namely forest-based aggregation technique (FBAT) and forest-based accelerated aggregation technique (FBAAT). In addition, an adjusting policy in consideration of wireless networks' real-time nature is proposed to make the two techniques more effective. As a result, data is compressed remarkably and lifecycle is prolonged considerably.Finally, experiments are carried out to prove the proposed techniques'feasibility, validity, and real-time nature. Extensive experiments show that the proposed FBAT and FBAAT can reduce energy consumption and lengthen lifetime as long as possible.