Research On Energy-Efficient Data Query In Wireless Sensor Networks

With the development of the wireless sensor networks, the monitoring of the dangerous environment and various applications can be reliable easily. There exists a large amount of detected data that need to be tackled properly, so that the users of the database can get their interested information. Because the efficient query is limited by many factors of the WSNs, such as low data processing capability of the sensors, limited data storage, and limited energy and so on, among which the limited energy is the core factor that limits the development of the WSNs, and shortens the lifetime of WSNs. Thus, our focus of the paper is to study an energy-efficient data query algorithm.Firstly, an optimization algorithm based on time domain is proposed. With an energy-efficient model, the simulation is conducted. According to the powerful computing ability and abundant storage of the WSNs'sinks, an energy-efficient combined algorithm is proposed, which reducing the data redundan by the data managemen of database. This algorithm is optimized in time domain for single user query, so the energy consumption is reduced over data transmission. The tackling method lies in that, the redundant messages are compressed at the nodes, so the energy consumption is reduced and the WSNs'life is longer.Secondly, this paper discusses several algorithms and proposes improvements and optimization. For a class of multi-user query, a multi-user merge algorithm is proposed to minimum energy consumption It sums up the query types and algorithms, makes the probability of query selection more accurate via reviseing historical data of each node.. The simulation results show that, as time increases, the number of queries slower than non-merging algorithm and other merging algorithms. while the .network transmission energy consumption is less..The energy-efficient combined algorithm and multi-user merge algorithm is implemented based on the NS2. Simulation results indicate that these algorithm performs better than other query algorithms.