Mariachiara Puviani

On Self-Adaptation, Self-Expression, and Self-Awareness in Autonomic Service Component Ensembles

Software systems operating in open-ended and unpredictable environments have to become autonomic, i.e., capable of dynamically adapting their behavior in response to changing situations. To this end, key research issues include: (i) framing the schemes that can facilitate components (or ensembles of) to exhibit self-adaptive behaviors, (ii) identifying mechanisms to enable components or ensembles to self-express the most suitable adaptation scheme, and (iii) acquiring the proper degree of self-awareness to enable putting in action self-adaptation and self-expression schemes. In this position paper, with the help of a representative case study, we frame and discuss the above issues, survey the state of the art in the area, and sketch the main research challenges that will be faced in the ASCENS project towards the definition of a fully-fledged framework for autonomic services.

The Autonomic Cloud: A Vision of Voluntary, Peer-2-Peer Cloud Computing

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.

A taxonomy of architectural patterns for self-adaptive systems

Autonomic systems are able to adapt themselves to unpredicted and unexpected situations. Such adaptation capabilities can reside in individual components as well as in ensembles of components. In particular, a variety of different architectural patterns can be conceived to support self-adaptation at the level both of components and of ensembles. In this paper, we propose a classification of such self-adaptation patterns -- for both the component level and the system level -- by means of a taxonomy organized around the locus in which the feedback loops promoting adaptation reside. We show that the proposed classification covers most self-adaptation patterns, and enables deriving further ones by applying a simple set of composition mechanisms. Three examples of existing patterns of the taxonomy are detailed in the paper to show the applicability of the approach. As discussed in the paper, the advantage of the proposed classification is twofold: it enables identifying the (possibly common) properties of the existing self-adaptation patterns; and, consequently, it can help developers in choosing the most appropriate self-adaptation patterns for the development of autonomic systems.

The Ensemble Development Life Cycle and Best Practices for Collective Autonomic Systems

Collective autonomic systems are adaptive, open-ended, highly parallel, interactive and distributed software systems. Their key features are so-called self-* properties, such as self-awareness, self-adaptation, self-expression, self-healing and self-management. We propose a software development life cycle that helps developers to engineer adaptive behavior and to address the issues posed by the diversity of self-* properties. The life cycle is characterized by three feedback loops, i.e. based on verification at design time, based on monitoring and awareness in the runtime, and the feedback provided by runtime data to the design phases. We illustrate how the life cycle can be instantiated using specific languages, methods and tools developed within the ASCENS project. In addition, a pattern catalog for the development of collective autonomic systems is presented to ease the engineering process.

A method fragments approach to methodologies for engineering self-organizing systems

This article summarizes five relevant methods for developing self-organizing multiagent systems. It identifies their most relevant aspects and provides a description of each one under the form of method fragments expressed using SPEM (Software and System Process Engineering Metamodel). The use of a “metamodel” to describe fragments facilitates the comparison of the methods and their respective fragments. These fragments can be combined and be part of a more general ad hoc methodology, created according to the needs of the designer. Self-organizing traffic lights controllers and self-organizing displays are chosen as case studies to illustrate the methods and to underline which fragments are important for self-organizing systems. Finally, we illustrate how to augment PASSI2, an agent-based methodology which does not consider self-organization aspects, with some of the identified fragments for self-organization.

Methodologies for Self-Organising Systems: A SPEM Approach

We define ’SPEM fragments’ of five methods for developing self-organising multi-agent systems. Self-organising traffic lights controllers provide an application scenario.

The Autonomic Cloud

The cloud case study within ASCENS explores the vision of an autonomic cloud, which is a cloud providing 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. As such, the autonomic cloud thus requires a certain degree of self-awareness, monitoring, and self-adaptation to reach its goals, which has been achieved with the integration of ASCENS methods and techniques.

Is Self-Expression Useful? Evaluation by a Case Study

In the context of adaptive component-based systems, self-expression is the capability of changing the adaptation pattern at run-time when some changes occur in the system itself or in its environment. Even if functional requirements can be met without changing the adaptation pattern, the achievement of non-functional requirements, such as performance, can benefit from a change of adaptation pattern. The aim of this paper is to show, by means of a case study in swarm robotics, that a change of adaptation pattern can affect the performance of a system. In particular we show that the change of adaptation pattern can be useful in adaptive component-based systems to react to changes in the situation of the environment.

Formalising adaptation patterns for autonomic ensembles

Autonomic behavior and self-adaptation in software can be supported by several architectural design patterns. In this paper we illustrate how some of the component- and ensemble-level adaptation patterns proposed in the literature can be rendered in SCEL, a formalism devised for modeling autonomic systems. Specifically, we present a compositional approach: first we show how a single generic component is modelled in SCEL, then we show that each pattern is rendered as the (parallel) composition of the SCEL terms corresponding to the involved components (and, possibly, to their environment). Notably, the SCEL terms corresponding to the patterns only differ from each other for the definition of the predicates identifying the targets of attribute-based communication. This enables autonomic ensembles to dynamically change the pattern in use by simply updating components’ predicate definitions, as illustrated by means of a case study from the robotics domain.

Enabling Self-Expression: The Use of Roles to Dynamically Change Adaptation Patterns

Self-expression is the capability of a system of changing its adaptation pattern at runtime, this can lead to better performance still keeping the achievement of the global goal in a Collective Adaptive System (CAS). In this paper, we show how self-expression can be achieved by means of roles. Developers can embed the adaptation logic in pieces of software that represent roles that system units can play: by changing the roles at runtime, the adaptation pattern changes as a consequence. Exploiting a swarm robotics case study, we show the applicability of our approach and the improvement of the performances with respect to keeping the same pattern during the execution.