Periodic Reporting for period 1 - MISSION (Models in Space Systems: Integration, Operation, and Networking)
Período documentado: 2021-10-01 hasta 2024-05-31
Spacecraft must work robustly in the presence of uncertainties such as random hardware faults, operator mistakes, space debris, and radiation. Classic space missions address uncertainty via large safety margins and bult-in redundancy, leading to a spiral of increasing cost and complexity. A recent trend is the small-business commercialisation of space using commercial-off-the-shelf components for networked constellations of small satellites. This "New Space" approach reduces component weight, size, price, and lead time, and makes innovation increasingly driven by software. This pertains especially to resource management and data handling, while simpler components and new interactions increase uncertainty, and come with less reliable parts. Thus, overall mission connectivity, efficiency, dependability and safety in the New Space needs to be achieved on a system level - for which there is no systematic approach yet. This is partly rooted in the empirical focus of many teams, and partly in a lack of easy-to-use methods to model, analyse, and guarantee system-level dependability.
The interdisciplinary MISSION project sets out to solve this space engineering problem by exploiting highly advanced techniques from the forefront of computing science research, especially model-based algorithmics. We strive for sound and efficient software tools for the development of dependable, networked, and resource-aware New Space missions. For this, the MISSION project will develop an integrated model-based technology to establish and maintain system-level properties of critical space mission parameters. A strong consortium of excellent academic and industrial partners in Europe, Argentina, and China has agreed on a joint research and knowledge sharing agenda that will foster a shared culture of research and innovation, to finally deliver an ecosystem of easy-to-use methods and software tools to the New Space industry.
The interdisciplinary MISSION project sets out to solve this space engineering problem by exploiting highly advanced techniques from the forefront of computing science research, especially model-based algorithmics. We strive for sound and efficient software tools for the development of dependable, networked, and resource-aware New Space missions. For this, the MISSION project will develop an integrated model-based technology to establish and maintain system-level properties of critical space mission parameters. A strong consortium of excellent academic and industrial partners in Europe, Argentina, and China has agreed on a joint research and knowledge sharing agenda that will foster a shared culture of research and innovation, to finally deliver an ecosystem of easy-to-use methods and software tools to the New Space industry.
The MISSION project has worked towards developing models of energy and resource usage in space components, towards improving the reliability and resilience of space components and missions, on dependable and high-performance radio links and communication networks in and to/from space, in a way that integrates cross-cutting concerns and technology across these topics.
On the topic of energy and resource modelling and optimisation, we have created an inventory of current resource modelling practice at the project's industrial partners, followed by the design of a MISSION resource modelling platform. In this way, from a deep understanding of the state of practice, MISSION derived a resource modelling platform focussing on resource awareness in space missions. Closely related is our inventory of industrial practice and requirements related to modelling formalisms and tools in a broad sense, based on a questionnaire answered by all of the project's industrial participants.
On reliability and resilience, we focused on extensions of fault trees, a failure modelling and evaluation approach whose basic form has been established in industrial practice for nearly 5 decades. We have created a training compendium on deriving fault frees from data and using rare-event simulation approaches for their analysis, as well as a comprehensive survey and specification document on extended fault trees. It provides a survey of fault tree extensions with repair and maintenance aspects and investigates and resolves issues concerning their formal semantics. We have implemented a novel two-step hybrid approach in the Storm model checker for the efficient analysis of both static and dynamic fault trees.
Our work on links and communication networks resulted in new algorithms that efficiently route data across space networks, utilising topological and mission-specific data to minimise congestion in links and buffers effectively. Extensive simulation campaigns affirmed the algorithms' performance and practical applicability in real-world scenarios. To improve the dependability of communication, we created space routing methods through modelling space communication protocols using Markov decision processes. The approach involves intelligent data replication to enhance successful and timely data delivery over delayed, disrupted, and congested links. In tight collaboration with the project's industrial partners, we also improved error recovery and flow control in space communication links by modelling and optimising link protocols for miniaturised RF transponders.
The technical expertise and developments in the MISSION project were disseminated within the scientific community through publications and at dedicated workshops. In addition, the project sponsored two editions of the Rio Summer School of Informatic Sciences in Río Cuarto, Argentina, where undergraduate and graduate students attended courses by MISSION and external teachers on topics such as the verification of fault trees or routing in the space Internet.
On the topic of energy and resource modelling and optimisation, we have created an inventory of current resource modelling practice at the project's industrial partners, followed by the design of a MISSION resource modelling platform. In this way, from a deep understanding of the state of practice, MISSION derived a resource modelling platform focussing on resource awareness in space missions. Closely related is our inventory of industrial practice and requirements related to modelling formalisms and tools in a broad sense, based on a questionnaire answered by all of the project's industrial participants.
On reliability and resilience, we focused on extensions of fault trees, a failure modelling and evaluation approach whose basic form has been established in industrial practice for nearly 5 decades. We have created a training compendium on deriving fault frees from data and using rare-event simulation approaches for their analysis, as well as a comprehensive survey and specification document on extended fault trees. It provides a survey of fault tree extensions with repair and maintenance aspects and investigates and resolves issues concerning their formal semantics. We have implemented a novel two-step hybrid approach in the Storm model checker for the efficient analysis of both static and dynamic fault trees.
Our work on links and communication networks resulted in new algorithms that efficiently route data across space networks, utilising topological and mission-specific data to minimise congestion in links and buffers effectively. Extensive simulation campaigns affirmed the algorithms' performance and practical applicability in real-world scenarios. To improve the dependability of communication, we created space routing methods through modelling space communication protocols using Markov decision processes. The approach involves intelligent data replication to enhance successful and timely data delivery over delayed, disrupted, and congested links. In tight collaboration with the project's industrial partners, we also improved error recovery and flow control in space communication links by modelling and optimising link protocols for miniaturised RF transponders.
The technical expertise and developments in the MISSION project were disseminated within the scientific community through publications and at dedicated workshops. In addition, the project sponsored two editions of the Rio Summer School of Informatic Sciences in Río Cuarto, Argentina, where undergraduate and graduate students attended courses by MISSION and external teachers on topics such as the verification of fault trees or routing in the space Internet.
The MISSION project is underway to boost the state of the art in modelling and algorithms for energy and resource usage evaluation and optimisation in space missions, for ensuring their reliability and resilience, and for the next-generation space communication infrastructure. MISSION delivered notable contributions beyond the state of the art in distributed on-demand routing for LEO mega-constellations, evauated on a Starlink case study; on running TCP over Starlink in a stable manner; on novel software-defined DTN protocol stacks; on statistical, analytical, and learning-based routing approaches for delay-tolerant networks; on the space-terrestrial Internet of Things; on novel methods with unprecedented scalability for the analysis of fault trees combining dynamic sub-tree decomposition with binary decision diagrams; and on automated rare event simulation to analyze low-probability failures in a variant of dynamic fault trees with repairs. In close cooperation with the German Aerospace Center (DLR), MISSION researchers developed an approach for analysing and deriving FDIR concepts for systems whose error behaviour is represented by dynamic fault trees.
By the end of the project, we expect novel results on resource-aware scheduling, learning models for resource dynamics in an automated fashion leveraging machine learning technology, all while taking clearly quantified uncertainty about aspects of modelling and unpredictable environments into account. We will scale up our reliability analysis methodology and extend the corresponding algorithmic toolbox with automated synthesis techniques. Our work on space communication links will go deeper into the protocol layers to further boost performance and reliability. All of the project's activities will be built upon a new modelling language with a compositional semantics, which integrates the efforts in the projects various research areas and provides to the public a library of formal models for space components.
Through its scientific breakthroughs, but also by teaching a new generation of space engineers and computer scientists in further MISSION Summer Schools, MISSION will deliver an ecosystem of easy-to-use methods and software tools to the New Space industry that is founded on solid algorithmic science.
By the end of the project, we expect novel results on resource-aware scheduling, learning models for resource dynamics in an automated fashion leveraging machine learning technology, all while taking clearly quantified uncertainty about aspects of modelling and unpredictable environments into account. We will scale up our reliability analysis methodology and extend the corresponding algorithmic toolbox with automated synthesis techniques. Our work on space communication links will go deeper into the protocol layers to further boost performance and reliability. All of the project's activities will be built upon a new modelling language with a compositional semantics, which integrates the efforts in the projects various research areas and provides to the public a library of formal models for space components.
Through its scientific breakthroughs, but also by teaching a new generation of space engineers and computer scientists in further MISSION Summer Schools, MISSION will deliver an ecosystem of easy-to-use methods and software tools to the New Space industry that is founded on solid algorithmic science.