Study Of Overlapping Community Based Routing Protocol And Movement Model For Opportunistic Networks

The goal of Opportunistic Networks is to utilize the every contact opportunities between mobile devices to delivering messages in infrastructureless situations. For the incredible penetration of pocket devices with wireless communication capabilities (e.g., Wi-Fi, Bluetooth, Cellular, Zigbee) among the global population, the cell phones, PDAs, tablet PCs and laptops carried by people consist of a strong background for developing the Opportunistic Networks.In this kind of networks, the movements of the different devices mirror those of those owners, finding a suitable route between two disconnected devices implies uncovering habits in human movements and patterns in their connectivity (i.e., frequencies of meetings, average duration of a contact, etc.), and exploiting them to predict future encounters. Considering the environment and demand of applications in Opportunistic Networks, we first analyzed the real trace data. And by combining the theories of complex network and sociology, we proposed an Overlapping Community Detection Algorithm; an Overlapping Community based Routing Protocol and Social Aggregation Based Combination Movement Model for Opportunistic Networks.The overlapping community detection algorithm consists of an improved K-means and second-dividing algorithms, and can get the overlapping community structure and the active mode of sub-communities of nodes. The Time Routing can reduce the consumption of network resource and improve the delivery ratio by taking advantage of the overlapping community structure. The Social Aggregation Based Combination movement Model can reproduce more detailed human behavior for simulation by a flexible modeling mechanism. By deploy those algorithms and model in ONE Simulator; we test the efficiency, accuracy and flexibility of them.