The Study Of Data Query Algorithm For Wireless Sensor Network Based On Cross-layer Optimization

Wireless sensor network through a large number of micro sensor nodes deployed in the monitoring area to obtain objective information, it has a very broad application prospects. Data query technology is one of the key technologies of wireless sensor networks. It determines the availability and effectiveness of the wireless sensor network. It is the basis of the wireless sensor networks. In this paper, use cross-layer optimization techniques for sensor nodes communication bandwidth. It proposes power control and communication slot allocation optimization. The algorithm reduces network energy consumption and ensures the quality of the query for different application environments.In order to reduce energy consumption and to ensure the efficiency and success rate of communication at the same time, this paper proposes an energy-efficient and ensured communication quality data query algorithm based on cross-layer power control. The algorithm is based on the energy and location of the nodes to select the best path from sensory node to base station by hop-to-hop. After that process, control the power of transmitting at real time based on cross-layer to reduce network power consumption and ensure the communication quality. The simulation results show that the algorithm can reduce network energy consumption to do the data query operations to achieve the purpose to extend the network lifetime.The traditional Top-k query has to transfer large amount of data and some node exists the problem of too rapidly energy consumption. This paper also proposes an algorithm of Top-k based on cross-layer. Top-k query in wireless sensor networks have a broader application. The algorithm use node information table to distribute the communication time slot reasonably to reduce the data transition in network. The algorithm proposes a hybrid network topology. It can adjust routing dynamically based on nodes’ energy to solve the problem of some nodes’energy consummating too rapidly by forwarding large amounts of data. Simulation results show, the algorithm significantly reduced the amount of data forwarding, and effectively extend the network lifetime in the data query process.