Research On Energy Efficient Multiple Queries Optimization In Wireless Sensor Networks

Wireless sensor networks (WSNs) are formed by a large number of nodes through mutual cooperation, which can carry out effective monitoring on a wide range of regions, process the monitoring data and transfer the data to users who need it. As a node is supplied by batteries, the node will be invalid if its energy is exhausted. Therefore, we focus on optimizing multiple queries energy efficiently to reduce energy consumption of sensor nodes.This thesis analyzes multiple queries in-network processing technologies in WSNs. Association Degree-based Multiple Queries Optimization algorithm (ADMQO) is proposed. In ADMQO algorithm, the concept of association degree is proposed, which is used to measure the data of nodes correlation. Nodes choose parent node by calculating association degrees between nodes and candidate parent nodes, and nodes covered by overlapping regions of queries cluster into a group. As the same values will be transferred once instead of being transferred repeatedly, the number of data transmitted can be efficiently reduced. Performance analysis and simulation results show that the proposed algorithm can reduce the amount of transmission load in WSNs.In this thesis, Query Rewriting-based Multiple Queries Optimization algorithm (QRMQO) is also proposed, due to the fact that values of queries are always existing overlap. In the base station, queries submitted by users in the previous period are rewritten into an optimized set that shares the commonality and eliminates the redundancy among queries in the original set, consequently, the number of queries send into the network is reduced, and the amount of data transmitted from sensor nodes to the base station is also reduced. Simulation results show that the proposed algorithm can decrease the number of data transmitted in WSNs.As the energy of sensor nodes mainly is consumed in transmitting data, reducing the amount of data transmitted can extend the network lifetime. The proposed two schemes efficiently take advantage of the work sharing mechanism among multiple queries, and effectively reduce the amount of transmission load. It is valuable to the related research in wireless sensor networks.