Alocação dinâmica de recursos computacionais para experimentos científicos com replanejamento automatizado a bordo de satélites / Dybanic allocation of computational resources for scientific experiments with autonomous replanning aboards satellites

AUTOR(ES)
DATA DE PUBLICAÇÃO

2007

RESUMO

The experiments aboard the Brazilian scientific satellites are currently thought to execute its tasks in a repetitive way, collecting, storing and sending data in a cycle that does not suffer great alterations. This way of dealing with the experiments operation fits perfectly to long-term scientific observation. There are, however, short-duration scientific phenomena of which occurrence, although predictable, are random. To better analyze these phenomena it may be important to increase the acquisition rate or the precision of the data collected. This increases the consumption of resources, such as memory and power, beyond the originally predicted. Due to the short duration and the difficulty to specify exactly when a phenomenon of this kind will occur, it is not enough to leave the ground operations team in charge of the satellite reconfiguration. The necessary time for the phenomenon to be reported and for the ground team to create and send a new operation plan to the satellite is in general much longer than the duration of the phenomenon. There is then the need for allowing the experiments, when detecting the occurrence of a short-duration phenomenon, to request from the onboard computer the temporary reallocation of resources. This reallocation shall occur in a way that affects the least possible the operation of the other experiments and the satellite itself. As the number of states in which the system can be is huge, it becomes difficult the use of classical programming techniques to handle it. This work proposes the use of Artificial Intelligence Planning and Scheduling techniques to allow the onboard replanning of operations, when a short-duration scientific phenomenon is detected. The main goal is to provide more autonomy to the satellite and, consequently, more strength to respond to external events. It was defined an architecture for an onboard replanning service, to be used in INPEs scientific satellites. There was the concern for context this architecture in the current INPEs projects for satellites and computers. Thus, it was developed a prototype based on this architecture, implemented for execution in a satellite onboard computer which is being developed at INPE. Due to the lack of software tools for this kind of computer, it was also necessary to develop a knowledge representation language and a planning system, specific for this domain. The prototype created is based on the idea of guaranteeing a greater integration between the planning process and the rest of the satellite software. The knowledge representation language brings a form of modeling closer to the operation and behavior of satellites than other existing languages, which are not directed to the space area. The results gotten show that the prototype is adequate for execution in the onboard environment, and that this work can be considered a first step in the direction of increasing the autonomy of the software aboard future INPEs satellites.

ASSUNTO(S)

escalonamento planejamento scheduling autonomy artificial intelligence computer science inteligência artificial planning knowledge representation representação do conhecimento autonomia

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