Data Collection In Wireless Sensor Networks Based On Mobile Sink

WSN (Wireless Sensor Network) is a multi-hop ad hoc network, which is formed by the wireless communication between large numbers of low-cost micro sensor nodes which are deployed in the monitoring area. WSN is a new platform for information collection, which can monitor and gather information of various detected objects within the network coverage in real time, and send the information to the gateway node to realize complex object detection and tracking in the specified range. It is with rapid deployment, survivability, and other characteristics, and has broad application prospects.Energy consumption is an important point in the design of WSN, because each sensor node has very limited battery power, and once the node is assigned to a detected environment, it is not practical to recharge the battery. In static sensor networks, the perceived information is relayed to the base station through the multi-hop manner. This scheme cause some nodes soon run out of their energy and become bottleneck nodes, making the network dead soon. Recently some researches suggest that adding mobility to the network can greatly save energy, and extend the lifetime of the network.This paper continues the idea of mobility. Since the main problem is how to collect data in the network with the introduction of mobile nodes, this paper first presents a rational taxonomy for the data collection based on this approach, and gives a survey of this subject's situation, problems and challenges. DataSalmon protocol is a typical solution based on the mobile sink, which not only eases the problem of bottleneck nodes, and effectively resolves the problem of uneven distribution of data traffic. This paper discusses DataSalmon protocol's main content, and noted its advantages and disadvantages, and then improves it from the following three aspects. Firstly, the paper adds cluster structure and cluster head election mechanism to the protocol. Secondly, the paper suggests forming the optimal data delivery tree in flood manner. Thirdly, the paper takes both data traffic and remaining energy into account to collect data. The improved DataSalmon protocol further develops the advantages of the original one, and avoids its disadvantages, making it more adaptive and more effectively balance and save the network's energy. Finally, we simulate the protocols, and the simulation results show that the improved protocol performs better than the original one in terms of energy saving and prolonging the network lifetime.