Autonomic computing - that is, the development of software and hardware systems featuring a certain degree of self-awareness and self-adaptability - is a field with many application areas and many technical difficulties. In this paper, we explore the idea of an autonomic cloud in the form of a platform-as-a-service computing infrastructure which, contrary to the usual practice, does not consist of a well-maintained set of reliable high-performance computers, but instead is formed by a loose collection of voluntarily provided heterogeneous nodes which are connected in a peer-to-peer manner. Such an infrastructure must deal with network resilience, data redundancy, and failover mechanisms for executing applications. We discuss possible solutions and methods which help developing such (and similar) systems. The described approaches are developed in the EU project ASCENS
The challenge of developing dynamically-evolving resilient distributed systems that are composed of autonomous components has been partially addressed by introducing the concept of component ensembles. Nevertheless, systematic design of complex ensemble-based systems is still a pressing issue. This stems from the fact that contemporary design methods do not scale in terms of the number and complexity of ensembles and components, and do not efficiently cope with the dynamism involved. To address this issue, we present a novel methodInvariant Refinement Method (IRM) -for designing ensemblebased component systems by building on goal-based requirements elaboration, while integrating component architecture design and software control system design.
International audienceDesign of self-adaptive software-intensive Cyber-Physical Systems (siCPS) operating in dynamic environments is a significant challenge when a sufficient level of dependability is required. This stems partly from the fact that the concerns of self-adaptivity and dependability are to an extent contradictory. In this paper, we introduce IRM-SA (Invariant Refinement Method for Self-Adaptation) – a design method and associated formally grounded model targeting siCPS – that addresses self-adaptivity and supports dependability by providing traceability between system requirements, distinct situations in the environment, and predefined configurations of system architecture. Additionally, IRM-SA allows for architecture self-adaptation at runtime and integrates the mechanism of predictive monitoring that deals with operational uncertainty. As a proof of concept, it was implemented in DEECo, a component framework that is based on dynamic ensembles of components. Furthermore, its feasibility was evaluated in experimental settings assuming decentralized system operation
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