Delay/Disruption Tolerant Reinforcement Learning and Aurora Based Communication System

Cognitive communication techniques are needed to ensure optimal use of very expensive space communications resources. The vast distances and numerous satellites in current and future NASA missions necessitate multi-hop communications utilizing temporary stores. Space communication networks are characterized by intermittent links, high latencies, low bandwidths, ad hoc connections, mobile physical nodes, asymmetric data rates, higher error rates, and heterogenous node types.nbsp; DREAMS focuses on two separate but related aspects of optimal communicationsmdash;routing and link optimization. Link optimization is the ability to optimize a given link by tuning the modulation scheme, coding scheme, transmit power, symbol rate, and roll-off factor, where optimality is the weighted sum of Bit Error Rate (BER), throughput, occupied bandwidth, spectral efficiency, transmit power efficiency, and Direct Current (DC) power consumption. Routing refers to the ability, given that links are already optimized and known (to the extent possible), to optimally schedule storage and transmission of data to maximize throughput.To optimally fill the router role, in Phase II we will develop a near-operational, distributed, optimized transmission and storage scheduler in three versions integrated with GRCrsquo;s ground testbed and ready for thorough testing in realistic simulations on a large number of very diverse scenarios.nbsp; The distributed nature is accomplished by a straightforward division of labor between separate computational nodes and exchange of extremely low volume information (resource status and the current schedule).nbsp; The Link Optimizer is based on Machine Learning techniques using data from KRATOSrsquo;s high fidelity RF Link simulator while the scheduler is based on the bottleneck avoidance algorithm, which uses information from the entire schedule and current resource status and congestion to best utilize ALL possible links to maximize successful transmission of the highest number of packets.