Message Scheduling Optimization with Energy Constraints and Uncertain Demands in a Store-and-Forward Nanosatellite Communications Architecture

Message Scheduling Optimization with Energy Constraints and Uncertain Demands in a Store-and-Forward Nanosatellite Communications Architecture

We formulate message scheduling optimization models for a communications network architecture containing nanosatellites, gateways, and remote users. In this architecture, messages are to be scheduled at gateways and nanosatellites during certain contact time windows to be delivered to their associated remote users using a store-and-forward approach. Two deterministic models and one probabilistic model are presented which derive message paths and schedules while addressing short contact windows, limited energy capacity and uncertainty in link quality. In the probabilistic model, uncertainty in link quality is incorporated by representing the demand to each user with a random variable and formulating it as a chance-constrained programming model. In order to compare the resulting strategies of the optimization models, a discrete-event scheduling simulator with message flow and energy dynamics is created. A simple greedy strategy is also derived by finding earliest message arrival paths to remote users based on the contact windows only. Probabilistic simulations are performed using the discrete-event simulator to compare the various strategies. Simulation results demonstrate that a well-balanced path usage and minimum average total delivery time is achieved with the strategy of the probabilistic model when compared with the deterministic models and the greedy strategy.