The Research Of Routing Algorithm In Multi-Sink Wireless Sensor Networks

With the fast development of Internet, mobile Internet, the sensor technology and the wireless communication technology, the wireless sensor networks(WSN) which take advantage of these technologies has been promoted greatly.Because the sensor node in WSN is powered by batteries, its energy and function is critically limited. Therefore, how to prolong the lifetime of WSN and increase the energy efficiency of the whole network are the key points of the research on WSN routing algorithm.Nowadays, the research on single-sink WSN routing algorithm is relatively in-depth and comprehensive. But the single-sink WSN has many defects. If the single sink node breaks down by accident, the information from the source node cannot reach the sink node any more.Moreover, since all the information converges atthe single sink node, the burden of data fusion for the node is too heavy and the energy consumption of the network is increased. The energy consumption of the network is unbalanced. If the node is closer to the sink node, it will be more likely that the node breaks down because of using up the energy earlier. Therefore, researchers pay more attention to the multi-sink WSN routing algorithm. Because there are several sink nodes to collect the information, how to select an optimal sink node as the destination node is the key point of the research on multi-sink WSN routing algorithm.This paper proposes a probabilistic routing algorithm based on Naive Bayesian Classification Model in multi-sink WSN. The proposed algorithm firstly establishes an effective sink selection mechanism.The sensor node can take various conditions of the network into consideration by using Naive Bayesian Classification Model. And then the sensor node can select the optimal sink node as the destination in the current scene. After the above step, the probabilistic routing mechanism will be established to make the construction of routing path more dynamic. Thus, the reliability of the network is strengthened and the energy consumption is more balanced.Through the simulation, we can find out that the proposed algorithm makes an effective use of the sensor node which has a high level of residual energy, balances the energy consumption of the network, prolongs the lifetime of the network and strengthens the reliability of received data.