Very few Mission Planning Systems oriented to DSS consider network topologies, the dynamism 600
influenced by orbit trajectories or their lossy nature (especially for missions that rely on small spacecraft technologies). Figure 8 tries to emphasize the fact that node interactions (i.e. trans-fer of data, coordination messages, etc.) happen in an intermittent manner. In addition to that, different nodes in the constellation may be characterized by different ISL bandwidths, ranges or even technologies (i.e. optical, RF bands). Nevertheless, many of the consulted references propose 605
MPS that do not rely or consider these network features: they are executed on-ground and then send the solution to the network of satellites. A notable exception is the one published in [37, 75].
These researchers from the French CNES and ONERA propose a cooperative framework based on a negotiation approach that actually takes advantage of the fact that orbits can be considered quasi-periodic. With this primitive assumption, they designed a decentralized, on-board planning scheme 610
where satellites predict future interactions based on orbit period information. At every satellite encounter, spacecraft exchange information in order to allow the negotiation scheme to converge to a feasible planning solution. They implemented an epidemic inter-satellite communication proto-col (known to propagate a given information unit in Oplog nq communication rounds) to allow for indirect communication between the satellites. Their simulations show how, on average, a satellite 615
constellation with 3 satellites is able to absorb more than 70% of the requests in less than 48 hours
(with the constellation initialized with 150 requests and two blocks of 200 requests triggered during the simulation). Nonetheless, their work does neither analyze the network overhead nor show the ac-tual convergence time for this algorithm, making it difficult to evaluate the suitability for demanding contexts requiring short revisit times or deadlines. Moreover, despite centralized, the algorithm they
620
presented assumes a fixed and known constellation, precluding dynamic or opportunistic concepts such as FSS.
Novel approaches such as the one in [68], propose hierarchical networks of indirectly-communicated satellites in order to provide a scale-free solution to the planning problem in huge constellations or satellite swarms. This idea, however, was not explored in their published work and does not seem
625
to be developed in further publications of the authors.
Finally, it is interesting to mention that the MPS presented in [36] was validated for a complex network consisting of several ground stations, 3 GEO satellites to provide data rely capabilities and 12 LEO satellites performing Earth Observation datatakes. Interestingly, despite dating from 2005, this work seems to capture the network complexity of future distributed satellite systems, at least
630
in a very primitive way (i.e. small constellation, unconstrained ISL, etc).
5 Conclusions
This paper has tried to lay out the potential benefits of autonomy in Distributed Satellite Sys-tems by revisiting and structuring its traditional motivations and the current prospects. Autonomy is presented as an integral characteristic of DSS that could enable coordination of spacecraft in
635
distributed Earth observation endeavors. Particularly, the need for autonomous DSS has been dis-cussed in the context of innovative space systems; those that foresee re-usable, increasingly complex and large-scale systems, composed of interconnected spacecraft with heterogeneous capabilities. As such, autonomy is not only targeted at solving task scheduling problems but rather at becoming an all-pervasive operational scheme that can contribute to the achievement of many system qualities.
640
In line with this, the paper highlighted that operating DSS autonomously could improve respon-siveness of the system, and even bring about other qualities like resiliency, adaptability and in-orbit exchange of resources.
Autonomous operations can be designed as part of next-generation Mission Planning and Schedul-ing frameworks. AccordSchedul-ingly, the paper devoted several sections to present an exhaustive knowledge 645
classification that has aimed at identifying the architectural, modeling and execution characteristics of current MPS solutions. Among the explored characteristics of MPS, several coordination and organization approaches towards increasing autonomy have been presented, namely: bio-inspired and self-organizing systems; MAS-based designs; and MPS that generate mission plans in batch.
Problem division, the type and modeling of resources, and the timeline representation have been 650
presented as some of the design traits of multiple MPS. Additionally, their runtime characteristics have been classified into deliberative, reactive, and hybrid approaches. With the former being com-mon for MPS that generate mission plans in batch, reactive decision making has been found to be one of the commonalities of negotiation-based and bio-inspired solutions. Similarly, this classifica-tion has also attempted to distinguish the segmentaclassifica-tion between on-board and on-ground mission 655
planning designs. Moreover, the paper has also explored many of the metaheuristic families used in the solving of DSS scheduling problems when these are formulated as a multi-dimensional Knapsack problem.
Albeit some works have addressed autonomous operations in regards to flight-formation, fail-ure detection and mitigation, or the generation of observational requests (through processing of 660
on-board data), achieving autonomous operations at all levels is still an open field of research. Sev-eral fundamental questions remain open and should be addressed in future works. Undoubtedly thought-provoking, one of such questions continues to revolve around what is the most appropriate organizational paradigm to implement autonomous DSS (i.e. multi-agent-based, bio-inspired, based on heuristics and optimization techniques, based on negotiation algorithms, hybrid constitution.) 665
Related to that, future studies may also inquire further into the actual tradeoffs of decentralized
on-board decision making in contrast to centralized on-ground alternatives. Furthermore, attaining the system qualities of a DSS through autonomous operations has still not been demonstrated. Future research is expected to tackle these aspects, which may also comprehend the ability to provide in-orbit data services or, more generally put, the exchange of on-board resources. Assessing the impact
670
of small spacecraft technologies and their limitations in regards to autonomous operations is equally pivotal. In particular, new satellite coordination mechanisms need to circumvent the constraints enforced by the low datarate inter-satellite links inherent to small satellite designs. Ultimately, it is important to highlight the need to put all these questions in the context of disruptive DSS designs:
large-scale, dynamic networks in which heterogeneous satellites cooperatively perform distributed
675
Earth observation.
6 Acknowledgments
The work presented in this paper has been carried out in the frame of the Operational Network of Individual Observation Nodes (ONION) project, and has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement 687490, coordinated
680
by Thales Alenia Space France.
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