Research On Algorithm Of Data Gathering In Wireless Sensor Networks

Wireless Sensor Network(WSN), consisting of a large number of sensors which are powered by low energy battery, is self-organizing network by multi-hop. Wireless sensor network has a wide application in practice. However, the wireless sensors are powered by the batteries. To make use of the limited amount of energy efficiently is a critical concern. Moreover, the memory, the capability of processor and the transmission range are also limited. Since Compressive sensing(CS) requires a small number of measurement vector, the energy consumption for data gathering in WSNs is reduced significantly. In addition, the multiple mobile sinks can improve the energy load balance. In this dissertation, we mainly study the clustering algorithm based on compressive sensing and multiple mobile sinks for the purpose of extending the lifetime.We propose the CDHC algorithm based on the clustering and compressive sensing. In the cluster, the common sensors send their data to the cluster head directly, the cluster head aggregate the received data using CS and transmit it to the sink or father cluster head via a backbone routing tree. Furthermore, we analyze the relationship between the network energy consumption and cluster size. The simulation results show that the proposed algorithm is effective, and is better than hybrid tree algorithm in terms of energy consumption.This dissertation put forward CMSLM algorithm, making use of multiple mobile sinks for gathering data. When mobile sink moves to sojourn point, it establish the routing tree by using the ideas of the maximum flow, in order to make every layer node contains the number of children as equal as possible. The simulation results show that CMSLM algorithm improves the network lifetime and the quantity of data by comparing with GBP-MSSN algorithm and EBRAMS algorithm.