A Research On An Efficient Spatial-query Routing Protocol For Wireless Sensor Networks

The wireless sensor network(WSN) is a kind of wireless multi-hop self-organizing network system, which is formed by plenties of sensor nodes deployed in the monitoring area. It is one of the hotspots in the field of information technology, which has a great academic value, a broad application prospect and a significant business value. And with the advancement of wireless communications technology, sensor technology and other relative technologies, WSNs have been more and more widely used in the socioeconomic fields. In the data-centric and large-scale WSN applications, most of the sensor data queries submitted by users are usually spatial queries, which intend to get the status information of a local region in the entire monitoring network. However, in the realistic scenarios, the battery-powered sensor nodes are sharply constrained in energy. Moreover, with the constraints of the deployment environment and the network size of WSNs, it’s usually very difficult to reinforce the battery capacity for sensor nodes. So it becomes an urgent problem to improve the energy efficiency of spatial query for sensor data.GeoGrid is a totally location-based routing protocol, it has good scalability,it is easily to achieve and it is well suitable for the large-scale WSN application scenarios. However, there still remains some disadvantages for the GeoGrid to conduct more efficient spatial queries. Aimed at scenarios of spatial queries in the large-scale WSNs, this paper optimizes and improves the GeoGrid in its clustering, cluster head election, networks topology hierarchy and routing strategy, and proposes QuadGrid, an efficient routing protocol for WSNs. Firstly, adopt a new network partitioning approach, bulid a hierarchal network topology based on the quadtree structure, which is quite efficient for the spatial queries, encode the partitioned grids with the Morton code, and add management nodes in the relative quadtree hierarchies. Secondly, on the cluster head nodes election procedure, comprehensively consider sensor nodes’ residual energy, the distance between the sensor node and the very center point of the grid that it belongs to and the distance between the sensor node and its eight neighbouring cluster heads, and then select the sensor node with the optimal overall performance as the cluster head. Thirdly, on the next hop routing node election, take two factors, sensor nodes residual energy and the data trassmission distance from the current cluster head to the next-level parent cluster node via the candidate next-hop cluster head nodes, into full consideration and choose the optimal neighbouring cluster head of the current cluster head as the next-hop routing node. Lastly, design a spatial query strategy for the newly proposed QuadGrid on the distribution of query data packets and the collection of sensor data packets.Analyses and simulations have been made on the number of survived nodes, the average network energy consumption and the average energy consumption for spatial queries. It turns out that QuadGrid is much better in the energy balance and it has a longer network lifetime than the the GeoGrid and the QTBDC. Besides, QuadGrid has a relative lower energy consumption for spatial queries. Generally speaking, QuadGrid is an efficient spatial query routing protocol for wireless sensor netwoks.