Study On Grid-based Wireless Sensor Network Data Aggregation Algorithm

Wireless Sensor Networks (WSN) refer to the self-organizing multi-hop networks in which the monitoring area is composed of many micro-sensor nodes and formed by wireless communication, aiming to collaboratively perceive, collect and dispose the information from the perceived objects in the network overlay area, and then send to the observer. They have broad application prospects such as national defense and military, urban management, health care, environmental monitoring, disaster sites and so on. However, there is energy limitation of the nodes and short lifetime of the network. So it is important to design a robust and expansible network with high efficient and low energy consuming data processing and packet routing protocol.Data aggregation is such a kind of technique that sensor nodes eliminate the redundancy of the data sensed or received from other node, combine them into one packet and then forward it to the next hop. It can reduce the number of the transferred packets in the network, reduce the probability of the duplicated packet received at sink node, improve the accuracy of the monitoring results and reduce the energy consumed.Grid is a hierarchical network architecture based on geography. When grid is formed, every grid has a gateway. The grid gateway could manage the nodes in the grid, route and transfer packets. It forwards packets based on the relative position of the grids rather than a routing tree.The paper designed a data aggregation protocol based on grid network architecture. The protocol improved the grid formation mechanism and presented a new method of gateway election and update considering node's energy and the distance between nodes and the center of the grid. Nodes and gateway had their own sleep mechanism. Data forwarding was based on RTS/CTS. According to whether the gateway had aggregate data and was closer to the sink the protocol set it a different priority. The gateways with different priorities sent CTS message with different delay to decide which gateway was the next hop. A detailed analysis of data aggregation timing was made to meet the maximum data aggregation. Five data aggregation timing methods were presented with a simulation comparison.The simulation results displays that the data aggregation protocol can combine data as early as possible, reduce the number of transferred packets effectively and achieve a good energy saving. The data aggregation timing method can achieve the maximum data aggregation. The RTS/CTS data forwarding mechanism reduces the data return delay. The mechanism of nodes sleeping and gateway election not only balances the network energy consumption and prolongs the network lifetime, but also improves the network robustness and scalability.