Coordination of Independent Loops in Self-Adaptive Systems

Panerati, Jacopo; Maggio, Martina; Carminati, Matteo; Sironi, Filippo; Triverio, Marco; Santambrogio, Marco D.

doi:10.1145/2611563

Cited by 4 publications

(2 citation statements)

References 27 publications

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“…Self-adaptive computers possess ad hoc capabilities—e.g. sensors, actuators, and decision making loops [ 32 ]—that allow them to express autonomous behaviours. Because they do not require the supervision of a human operator, these systems are especially suitable for critical, advanced applications such as space systems and robotic exploration.…”

Section: Application Scenariosmentioning

confidence: 99%

Assessing the resilience of stochastic dynamic systems under partial observability

et al. 2018

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Resilience is a property of major interest for the design and analysis of generic complex systems. A system is resilient if it can adjust in response to disruptive shocks, and still provide the services it was designed for, without interruptions. In this work, we adapt a formal definition of resilience for constraint-based systems to a probabilistic framework derived from hidden Markov models. This allows us to more realistically model the stochastic evolution and partial observability of many complex real-world environments. Within this framework, we propose an efficient and exact algorithm for the inference queries required to construct generic property checking. We show that the time complexity of this algorithm is on par with other state-of-the-art inference queries for similar frameworks (that is, linear with respect to the time horizon). We also provide considerations on the specific complexity of the probabilistic checking of resilience and its connected properties, with particular focus on resistance. To demonstrate the flexibility of our approach and to evaluate its performance, we examine it in four qualitative and quantitative example scenarios: (1) disaster management and damage assessment; (2) macroeconomics; (3) self-aware, reconfigurable computing for aerospace applications; and (4) connectivity maintenance in robotic swarms.

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Section: Application Scenariosmentioning

confidence: 99%

Assessing the resilience of stochastic dynamic systems under partial observability

et al. 2018

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“…The more recent work by Panerati et al [17] applied a reinforcement learningbased approach to determine the appropriate configuration for coordinating multiple autonomic managers. In this context, we share the same problem motivation as addressed in our previous work [10].…”

Section: Related Workmentioning

confidence: 99%

Decentralized Planning for Self-Adaptation in Multi-cloud Environment

Ismail

Cardellini

2015

Communications in Computer and Information Science

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Abstract. The runtime management of Internet of Things (IoT) oriented applications deployed in multi-clouds is a complex issue due to the highly heterogeneous and dynamic execution environment. To effectively cope with such an environment, the cross-layer and multi-cloud effects should be taken into account and a decentralized self-adaptation is a promising solution to maintain and evolve the applications for quality assurance. An important issue to be tackled towards realizing this solution is the uncertainty effect of the adaptation, which may cause negative impact to the other layers or even clouds. In this paper, we tackle such an issue from the planning perspective, since an inappropriate planning strategy can fail the adaptation outcome. Therefore, we present an architectural model for decentralized self-adaptation to support the crosslayer and multi-cloud environment. We also propose a planning model and method to enable the decentralized decision making. The planning is formulated as a Reinforcement Learning problem and solved using the Q-learning algorithm. Through simulation experiments, we conduct a study to assess the effectiveness and sensitivity of the proposed planning approach. The results show that our approach can potentially reduce the negative impact on the cross-layer and multi-cloud environment.

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Trading off power and fault-tolerance in real-time embedded systems

Panerati

Beltrame

2015

2015 NASA/ESA Conference on Adaptive Hardware and Systems (AHS)

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Coordination of Independent Loops in Self-Adaptive Systems

Cited by 4 publications

References 27 publications

Assessing the resilience of stochastic dynamic systems under partial observability

Assessing the resilience of stochastic dynamic systems under partial observability

Decentralized Planning for Self-Adaptation in Multi-cloud Environment

Trading off power and fault-tolerance in real-time embedded systems

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