Michal Kit

DEECO: an ensemble-based component system

The recent increase in the ubiquity and connectivity of computing devices allows forming large-scale distributed systems that respond to and influence activities in their environment. Engineering of such systems is very complex because of their inherent dynamicity, open-endedness, and autonomicity. In this paper we propose a new class of component systems (Ensemble-Based Component Systems - EBCS) which bind autonomic components with cyclic execution via dynamic component ensembles controlling data exchange. EBCS combine the key ideas of agents, ensemble-oriented systems, and control systems into software engineering concepts based on autonomic components. In particular, we present an instantiation of EBCS - the DEECo component model. In addition to DEECo main concepts, we also describe its computation model and mapping to Java. Lastly, we outline the basic principles of the EBCS/DEECo development process.

A Life Cycle for the Development of Autonomic Systems: The E-mobility Showcase

Component ensembles are a promising way of building self-aware autonomic adaptive systems. This approach has been promoted by the EU project ASCENS, which develops the core idea of ensembles by providing rigorous semantics as well as models and methods for the whole development life cycle of an ensemble-based system. These methods specifically address adaptation, self-awareness, self-optimization, and continuous system evolution. In this paper, we demonstrate the key concepts and benefits of the ASCENS approach in the context of intelligent navigation of electric vehicles (e-Mobility), which itself is one of the three key case studies of the project.

Towards Dependable Emergent Ensembles of Components: The DEECo Component Model

In the domain of dynamically evolving distributed systems composed of autonomous and (self-) adaptive components, the task of systematically managing the design complexity of their communication and composition is a pressing issue. This stems from the dynamic nature of such systems, where components and their bindings may appear and disappear without anticipation. To address this challenge, we propose employing separation of concerns via a mechanism of dynamic implicit bindings with implicit communication. This way, we strive for dynamically formed, implicitly interacting groups - ensembles - of autonomous components. In this context, we introduce the DEECo component model, where such bindings, as well as the associated communication, are managed in an automated way, enabling transparent handling of the dynamic changes in the system.

Self-adaptation in software-intensive cyber-physical systems

A method for designing self-adaptive software-intensive cyber-physical systems.System variability is described by alternative invariant decompositions.Traceability between system requirements and runtime entities is preserved. Design 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.

An architecture framework for experimentations with self-adaptive cyber-physical systems

Recent advances in embedded devices capabilities and wireless networks paved the way for creating ubiquitous Cyber-Physical Systems (CPS) grafted with self-configuring and self-adaptive capabilities. As these systems need to strike a balance between dependability, open-endedness and adaptability, and operate in dynamic and opportunistic environments, their design and development is particularly challenging. We take an architecture-based approach to this problem and advocate the use of component-based abstractions and related machinery to engineer self-adaptive CPS. Our approach is structured around DEECo -- a component framework that introduces the concept of component ensembles to deal with the dynamicity of CPS at the middleware level. DEECo provides the architecture abstractions of autonomous components and component ensembles on top of which different adaptation techniques can be deployed. This makes DEECo a vehicle for seamless experiments with self-adaptive systems where the physical distribution and mobility of nodes, and the limited data availability play an important role.

The Invariant Refinement Method

The chapter describes IRM, a method that guides the design of smart-cyber physical systems that are built according to the autonomic service-component paradigm. IRM is a requirements-oriented design method that focuses on distributed collaboration. It relies on the invariant concept to model both high-level system goals and low-level software obligations. In IRM, high-level invariants are iteratively decomposed into more specific sub-invariants up to the level that they can be operationalized by autonomous components and component collaborations (ensembles). We present the main concepts behind the method, as well the main decomposition patterns that back up the design process, and illustrate them in the ASCENS e-mobility case study.

Gossiping Components for Cyber-Physical Systems

Developing software for dynamic cyber-physical systems (CPS) is a complex task. One has to deal with the dynamicity and unreliability of the physical environment where the software resides in, while, at the same time, provide sufficient levels of dependability and scalability. Although emerging software engineering abstractions, such as dynamic ad-hoc component ensembles, provide a convenient way to structure software for dynamic CPS, they need to be mapped to robust decentralized execution schemes in real-life settings. A particular challenge in this context is the robust distributed data dissemination in dynamic networks. Gossip-based communication stands as a promising solution to this challenge. We argue, that exploitation of application-specific information, software architecture in particular, has a large potential for improving the robustness and performance of gossip-based communication. This paper proposes a synergy between high-level architectural models and low-level communication models to effectively enable application-specific gossiping in component-based systems. The synergy is exemplified on the DEECo component model which is tailored to the needs and specifics of CPS, and evaluated on an emergency coordination case study with realistic network configurations.

DEECo: an ecosystem for cyber-physical systems

In this work we tackle the problem of designing and developing software-intensive cyber-physical systems (CPS), which are large distributed systems of collaborating elements that closely interact with the physical world, such as intelligent transportation systems and crowdsourcing applications. Due to their specific constraints, such as extreme dynamism and continuous evolution of the physical substratum, and requirements, such us open-endedness and adaptability, CPS introduce many new challenges for software engineering. In response, we present a tailored ecosystem of software engineering models, methods, and tools. This ecosystem is centered on the DEECo component model, which we have proposed specifically for architecting software-intensive CPS.

Software Abstractions for Component Interaction in the Internet of Things

Component ensembles provide expressive abstractions that address challenges in engineering software architectures for Internet of Things and cyber-physical systems, particularly when combined with mobile ad hoc networks. A case study in collaborative parking demonstrates the open-endedness of component ensembles and their ability to self-adapt.

Towards Performance-Aware Engineering of Autonomic Component Ensembles

Ensembles of autonomic components are a novel software engineering paradigm for development of open-ended distributed highly dynamic software systems e.g. smart cyber-physical systems. Recent research centered around the concept of ensemble-based systems resulted in design and development models that aim to systematize and simplify the engineering process of autonomic components and their ensembles. These methods highlight the importance of covering both the functional concepts and the non-functional properties, specifically performance-related aspects of the future systems. In this paper we propose an integration of the emerging techniques for performance assessment and awareness into different stages of the development process. Our goal is to aid both designers and developers of autonomic component ensembles with methods providing performance awareness throughout the entire development life cycle including runtime.