The Opportunistic Sensor Network Connectivity Model Base On Network Connectivity Degree

Opportunistic Sensor Network(OSN) is a kind of tolerant delay and disconnection self-organization network which is no need of a complete path between the source node and the destination node, and relying on the node mobility opportunity to achieve network communication. OSN has some significant features such as long delay and intermittent connection, however, the traditional mobile ad hoc network connectivity analysis methods cannot be used for OSN directly. As an important index to measure the performance of network, network connectivity is an important reference for the design of routing forwarding and data forwarding mechanism. Therefore, it is very important to establish a connectivity model of OSN to improve the performance of the network.The program is supported by the National Natural Science Foundation. After analyzing the characters of OSN,this thesis construct connectivity model of OSN based on temporal graph theory. The thesis summarizes the development of OSN. And it introduces the status of the art of Wireless Sensor Network(WSN), Mobile Ad hoc Network(MANET) and Delay Tolerant Network(DTN) in connectivity. The region connectivity is studied,and the region connectivity efficiency is defined to reflect the connectivity of nodes in the region. In order to reflect the connectivity between the region and the Sink nodes, the Sink connectivity efficiency of region is defined, and the computing method by means of corresponding adjacency matrix in snapshot of network is proposed. The whole network connectivity has been studied based on connectivity efficiency between Sink and region. In order to depict the network connectivity, the connectivity degree of the network is defined. Simulation experiments are carried out on region connectivity efficiency, Sink connectivity efficiency and network connectivity degree respectively. The simulation results show that region connectivity efficiency and Sink connectivity efficiency can reflect the connectivity between nodes within the region and the connectivity between regions and the sink node well, and network connectivity degree can reflect the connectivity of network in different experimental scenarios, however, when the network connectivity goes worse, the network connectivity degree becomes 0, which is inconsistent with the real case. The method for computing the network connectivity degree is improved by using the sliding time window. The simulation results show that the improved network connectivity degree can reflect connectivity of OSN more accurately in different experiment scenarios.