61,612 research outputs found
Applying autonomy to distributed satellite systems: Trends, challenges, and future prospects
While monolithic satellite missions still pose significant advantages in terms of accuracy and
operations, novel distributed architectures are promising improved flexibility, responsiveness,
and adaptability to structural and functional changes. Large satellite swarms, opportunistic satellite
networks or heterogeneous constellations hybridizing small-spacecraft nodes with highperformance
satellites are becoming feasible and advantageous alternatives requiring the adoption
of new operation paradigms that enhance their autonomy. While autonomy is a notion that
is gaining acceptance in monolithic satellite missions, it can also be deemed an integral characteristic
in Distributed Satellite Systems (DSS). In this context, this paper focuses on the motivations
for system-level autonomy in DSS and justifies its need as an enabler of system qualities. Autonomy
is also presented as a necessary feature to bring new distributed Earth observation functions
(which require coordination and collaboration mechanisms) and to allow for novel structural
functions (e.g., opportunistic coalitions, exchange of resources, or in-orbit data services). Mission
Planning and Scheduling (MPS) frameworks are then presented as a key component to implement
autonomous operations in satellite missions. An exhaustive knowledge classification explores the
design aspects of MPS for DSS, and conceptually groups them into: components and organizational
paradigms; problem modeling and representation; optimization techniques and metaheuristics;
execution and runtime characteristics and the notions of tasks, resources, and constraints.
This paper concludes by proposing future strands of work devoted to study the trade-offs of
autonomy in large-scale, highly dynamic and heterogeneous networks through frameworks that
consider some of the limitations of small spacecraft technologies.Postprint (author's final draft
Scheduling Activity in an Agent Architecture
Proceedings of the AISB’00 Symposium on AI Planning and Intelligent Agents. Birmingham, UK, 17-20 April, 2000.Agents for applications in dynamic environments require artificial intelligence techniques to solve problems to achieve their objectives. For example, they must develop plans of actions to carry out missions in their environment, in other words, to achieve some state in the world. But also, the agents must fulfill real-time requirements that arise because the characteristics of the applications and the dynamism of the environment. In this paper we analyze the use of a schedule of activity in an agent architecture to control the resources (time) needed by agents to accomplish their objectives.Publicad
On the tailoring of CAST-32A certification guidance to real COTS multicore architectures
The use of Commercial Off-The-Shelf (COTS) multicores in real-time industry is on the rise due to multicores' potential performance increase and energy reduction. Yet, the unpredictable impact on timing of contention in shared hardware resources challenges certification. Furthermore, most safety certification standards target single-core architectures and do not provide explicit guidance for multicore processors. Recently, however, CAST-32A has been presented providing guidance for software planning, development and verification in multicores. In this paper, from a theoretical level, we provide a detailed review of CAST-32A objectives and the difficulty of reaching them under current COTS multicore design trends; at experimental level, we assess the difficulties of the application of CAST-32A to a real multicore processor, the NXP P4080.This work has been partially supported by the Spanish Ministry of Economy and Competitiveness (MINECO) under grant
TIN2015-65316-P and the HiPEAC Network of Excellence.
Jaume Abella has been partially supported by the MINECO under Ramon y Cajal grant RYC-2013-14717.Peer ReviewedPostprint (author's final draft
- …