Community Division-Based Content Distribution in Information-Centric Satellite Networks: An Efficient Approach for Remote Sensing

With the development of in-orbit processing technology of remote sensing satellites, the intelligent processing units carried on the satellites realize the real-time acquisition and intelligent processing of remote sensing images, thus satisfying users’ individual needs and enhancing the response speed of tasks. However, a large amount of observation data cannot be transmitted back to the ground in time due to the limitation of the transmission capability of remote sensing satellites to the ground and the visible time window between satellites and ground stations in the process of satellite-terrestrial transmission. To solve this problem, a community division-based content distribution strategy (CDCD) is proposed. Firstly, the time slot model is designed to capture the time-varying topological information of the satellite network. Also, a content naming method that fits the characteristics of remote sensing data is presented. Then, a caching scheme based on community division is proposed by analyzing the regional characteristics of user requests. Taking advantage of the community structure characteristics of satellite networks, a novel cache node selection algorithm is designed to meet the user’s demand for fast access to target files. Meanwhile, a cached content prioritization model is constructed to further optimize the utilization of caching resources. Finally, the community structure-based routing algorithm (CSR) is proposed to effectively reduce the redundant transmission during content access through the mutual collaboration of intra-community and inter-community routing schemes. Simulation experiments show that the CDCD strategy effectively exploits the limited caching resources in the satellite network compared with other strategies, which promotes the stable and efficient distribution of remote sensing data.