Mission Aware Contact Plan Design in Resource-Limited Small Satellite Networks

Small satellite networks (SSNs) are playing an increasing role in nowadays earth observation due to their less development cost and energy consumption. In SSNs, it is pivotal to transmit a huge amount of data for differentiated missions to ground stations. Nevertheless, due to limited transponders and energy budget, not all contacts, i.e., potential available communication links, are feasible in data delivery. Besides, satellite downlink channel conditions are indeed time-varying due to atmospheric precipitation. Therefore, one daunting challenge is searching for feasible contacts termed as contact plan design with consideration of the differentiation for missions. In this paper, we exploit an extended time-evolving graph to characterize network resources. Based on the graph, we formulate the design of mission-aware contact plan, aiming at maximizing network profit in terms of sum weighted data volume as a mixed-integer linear programming. Due to its NP-hardness, we propose a primal decomposition method to efficiently solve the formulated problem by exploiting its special structure. To further reduce the complexity, we propose a link metric considering the issues of residual energy of satellites, time-varying satellite downlink contact capacity, and the differentiation for missions in the conflict graph. Based on the conflict graph, we devise a heuristic algorithm to design contact plan. Simulation results demonstrate the efficiency of the proposed algorithms and necessitate the consideration of the time-varying downlinks and the differentiation of missions for contact plan design.