SECM: status estimation and cache management algorithm in opportunistic networks

Abstract

In online social network, many data are created by human activities. Data communication in social networks can be recorded and analyzed by evaluation. The identification of nodes with the same types of attribute among numerous users has become a research problem in the field of social opportunistic network. Many mobile devices by users have to save and deliver information moment by moment. However, cache space with devices in social network is limited; a large amount of data must be saved and transmitted on time in online social networks. Delay and low delivery ratio may affect communication in opportunistic network. Thus, we propose an algorithm based on user nodes and neighbors in opportunistic networks to improve the transmission environment. Such networks can identify surrounding neighbors to evaluate nodes with probability, which will evaluate neighbors, ensure the high probability of node preferential access to information, and achieve the objectives of cache adjustment. Cache by node can be distributed reasonably. Experiments and a comparison of social opportunistic network algorithms show that the proposed method improves the cache utilization rate of nodes, reduces data transmission delay, and improves the overall network efficiency.