Research On Database Technology In Wireless Sensor Network

The flexibility and scalability of the wireless sensor network enables it to be widely applied in various fields such as the military, intelligent transportation and environmental monitoring. How to improve the network energy efficiency, how to apply wireless sensor network database technology and how to extend the network lifetime has recently become a research hotspot. The research in this thesis aims at data aggregation based on clusters, and it mainly focused on data aggregation algorithm based on network coding and efficient cluster head selection strategy.Since the adaptive data aggregation scheme is only suitable for single-hop networks, ADANC(Adaptive Data Aggregation with Network Coding) is proposed which can work in multi-hop networks, and it will adjust status of network to be optimal. There are relay nodes and encoder nodes in the encoding region around the cluster head. The relay nodes are only responsible for the transmission of data, while the encoder nodes are responsible for the selection of either the traditional data aggregation algorithm or the network coding depending on data correlation. The sink node adjusts the data correlation threshold which determines the current status of network and guarantees the final stability of the network. The experimental results show that the proposed method can make the network converge to desired reliability from any initial state, and improve the energy efficiency of the wireless sensor network.ACHSDA(Associate Cluster Head Selection based Data Aggregation), a data aggregation algorithm based on efficient cluster head selection is proposed to deal with the issue of energy that each cluster head reselection will consume. In setup phase, an associate cluster head node is selected at the same time when a cluster head node is selected. When the energy of cluster head node is below the average energy in the cluster, the associate cluster head node will replace the cluster head to avoid energy consumption of cluster reselection and to effectively extend the lifetime of the network. Compared with LEACH(Low Energy Adaptive Clustering Hierarchy), experimental results show that the proposed scheme has more surviving nodes and less energy consumption, and greatly extend the network lifetime.