Most launcher networks are based on proprietary buses such as MIL-STD-1553B whose low bandwidth limits the introduction of new services of suitable characteristics. Ethernet technology, because of its low cost and high performance, has been considered an excellent candidate for its use in launcher networks. The real time Ethernet solutions based on the Time Sensitive Networking (TSN) standards seem the most suitable because of its multi-vendor product characteristics. In this paper we propose a real time Ethernet solution for aerospace applications in which negligible jitter services has to be guaranteed. The proposed solution is based on the following TSN standards: IEEE 802.1AS/ASrev as synchronization protocol and 802.1Qbv-2015 for deterministic traffic scheduling. To improve both the bandwidth effective and the frame delay the solution is also based on a change in the management of the Priority Code Point field in IEEE 802.1Q standard. The optimal scheduling problem is formulated so as to minimize the makespan, defined as the time needed to deliver all of the messages of an elementary cycle. The problem has been resolved with the CPLEX solver and the proposed solution has been evaluated in terms of both delay and bandwidth effective by comparing its performance with the TTEthernet, FTTEthernet benchmark solutions. The obtained results in a real traffic scenario characterized by the set of messages of the VEGA launcher show how the proposed solution allows for the same performance of TTEthernet, i.e., the solution of proprietary and real-time Ethernet with better performance.

The success of small satellites has lead to the study of new technologies for the realization of Nano and Micro Launch Vehicle (NMLV) in order to make competitive launch costs. The paper has the objective to define and experimentally investigate the performance of a communication system for NMLV interconnecting the End Systems as On-Board Computer (OBC), telemetry apparatus, Navigation Unit...we propose a low cost Ethernet-based solution able to provide the devices with high interconnection bandwidth. To guarantee hard delays to the Guide, Navigation and Control applications we propose some architectural changes of the traditional Ethernet network with the introduction of a layer implemented in the End Systems and allow for the lack of any contention on the network links. We show how the proposed solution has comparable performance to the one of TTEthernet standard that is a very expensive solution. An experimental test-bed equipped with Ethernet switches and Hercules boards by Texas Instruments is also provided to prove the feasibility of the proposed solution.

Orbital Edge Computing (OEC) capability on board satellites in Earth Observation (EO) constellations would surely enable a more effective usage of bandwidth, since the possibility to process images on board enables extracting and sending only useful information to the ground. However, OEC can also help to reduce the amount of energy required to process EO data on Earth. In fact, even though energy is a valuable resource on satellites, the on-board energy is pre-allocated due to the presence of solar panels and batteries and it is always generated and available, regardless of its actual need and use in time. Instead, energy consumption on the ground is strictly dependent on the demand, and it increases with the increase in EO data to be processed by ground stations. In this work, we first define and solve an optimization problem to jointly allocate resources and place processing within a constellation-wide network to leverage in-orbit processing as much as possible. This aims to reduce the amount of data to be processed on the ground, and thus, to maximize the energy saving in ground stations. Given the NP hardness of the proposed optimization problem, we also propose the Ground Station Energy-Saving Heuristic (GSESH) algorithm to evaluate the energy saving we would obtain in ground stations in a real orbital scenario. After validating the GSESH algorithm by means of a comparison with the results of the optimal solution, we have compared it to a benchmark algorithm in a typical scenario and we have verified that the GSESH algorithm allows for energy saving in the ground station up to 40% higher than the one achieved with the benchmark solution.

Resource prediction algorithms have been recently proposed in Network Function Virtualization architectures. A prediction-based resource allocation is characterized by higher operation costs due to: (i) Resource underestimate that leads to quality of service degradation; (ii) used cloud resource over allocation when a resource overestimate occurs. To reduce such a cost, we propose a cost-aware prediction algorithm able to minimize the sum of the two cost components. The proposed prediction solution is based on a convolutional and Long Short Term Memory neural network to handle the spatial and temporal correlations of the need processing capacities. We compare in a real network and traffic scenario the proposed technique to a traditional one in which the aim is to exactly predict the needed processing capacity. We show how the proposed solution allows for cost advantages in the order of 20%.