On Emptying Small Satellite Networks with In-Network Data Aggregation
Recently, small satellites have attracted much attention in both academia and industry. These satellites can form a swarm and communicate via Inter-Satellite Links (ISLs) and help each other download data to one or more Ground Stations (GSs). A key challenge is that each satellite has a short contact period with different GSs over time. Henceforth, this paper considers the following objective: minimize the download time of a given amount of data from each satellite to ground stations. The main challenging issues are that satellites have different energy and buffer constraints. We model the problem as a Mixed Integer Linear Program (MILP). Its objective is to minimize the total number of time slots taken to download a fixed amount of data from each satellite. Its key decision variables relate to (i) routing, (ii) link scheduling, and (iii) data aggregation rate in each time slot. Our results show that in-network data aggregation is able to significantly reduce the total download time by 52% to 84% when the data aggregation rate is between 10% to 50%.
L. Wang & K. Chin, "On Emptying Small Satellite Networks with In-Network Data Aggregation," in 2018 28th International Telecommunication Networks and Applications Conference, ITNAC 2018, 2018, pp. 353-360.