18,061 research outputs found
Multi-Agent Approach to Modeling and Implementing Fault-Tolerance in Reactive Autonomic Systems
Recently, autonomic computing has been proposed as a promising solution for software complexity in IT industry. As an autonomic approach, the Reactive Autonomic Systems Framework (RASF) proposes a formal modeling based on mathematical category theory, which addresses the self-* properties of reactive autonomic systems in a more abstract level.
This thesis is about the specification and implementation of the reactive autonomic systems (RAS) through multi-agent approach by laying emphasis on the fault-tolerance property of RAS. Furthermore, this thesis proposes a model-driven approach to transform the RAS model to agent templates in multi-agent model using Extensible Stylesheet Language Transformation (XSLT). The multi-agent approach in this research is implemented by Jadex, a high-level Java-based agent programming language. The intelligent agents are created in Jadex based on the Belief-Desire-Intension (BDI) agent architecture. The approach is illustrated on a case study
A Formal Approach to Specification, Analysis and Implementation of Policy-Based Systems
The design of modern computing systems largely exploits structured sets of declarative rules called policies. Their principled use permits controlling a wide variety of system aspects and achieving separation of concerns between the managing and functional parts of systems.
These so-called policy-based systems are utilised within different application domains, from network management and autonomic computing to access control and emergency handling. The various policy-based proposals from the literature lack however a comprehensive methodology supporting the whole life-cycle of system development: specification, analysis and implementation. In this thesis we propose formally-defined tool-assisted methodologies for supporting the development of policy-based access control and autonomic computing systems.
We first present FACPL, a formal language that defines a core, yet expressive syntax for the specification of attribute-based access control policies. On the base of its denotational semantics, we devise a constraint-based analysis approach that enables the automatic verification of different properties of interest on policies.
We then present PSCEL, a FACPL-based formal language for the specification of autonomic computing systems. FACPL policies are employed to enforce authorisation controls and context-dependent adaptation strategies. To statically point out the effects of policies on system behaviours, we rely again on a constraint-based analysis approach and reason on progress properties of PSCEL systems.
The implementation of the languages and their analyses provides us some practical software tools. The effectiveness of the proposed solutions is illustrated through real-world case studies from the e-Health and autonomic computing domains
Semantic-based policy engineering for autonomic systems
This paper presents some important directions in the use of ontology-based semantics in achieving the vision of Autonomic Communications. We examine the requirements of Autonomic Communication with a focus on the demanding needs of ubiquitous computing environments, with an emphasis on the requirements shared with Autonomic Computing. We observe that ontologies provide a strong mechanism for addressing the heterogeneity in user task requirements, managed resources, services and context. We then present two complimentary approaches that exploit ontology-based knowledge in support of autonomic communications: service-oriented models for policy engineering and dynamic semantic queries using content-based networks. The paper concludes with a discussion of the major research challenges such approaches raise
Modeling adaptation with a tuple-based coordination language
In recent years, it has been argued that systems and applications, in order to deal with their increasing complexity, should be able to adapt their behavior according to new requirements or environment conditions. In this paper, we present a preliminary investigation aiming at studying how coordination languages and formal methods can contribute to a better understanding, implementation and usage of the mechanisms and techniques for adaptation currently proposed in the literature. Our study relies on the formal coordination language Klaim as a common framework for modeling some adaptation techniques, namely the MAPE-K loop, aspect- and context-oriented programming
Modeling Adaptation with Klaim
In recent years, it has been argued that systems and applications, in order to deal with their increasing complexity, should be able to adapt their behavior according to new requirements or environment conditions. In this paper, we present an investigation aiming at studying how coordination languages and formal methods can contribute to a better understanding, implementation and use of the mechanisms and techniques for adaptation currently proposed in the literature. Our study relies on the formal coordination language Klaim as a common framework for modeling some well-known adaptation techniques: the IBM MAPE-K loop, the Accord component-based framework for architectural adaptation, and the aspect- and context-oriented programming paradigms. We illustrate our approach through a simple example concerning a data repository equipped with an automated cache mechanism
Dynamic integration of context model constraints in web service processes
Autonomic Web service composition has been a challenging topic for some years. The context in which composition takes places determines essential aspects. A context model can provide meaningful composition information for services process composition. An ontology-based approach for context information integration is the basis of a constraint approach to dynamically integrate context validation into service processes. The dynamic integration of context constraints into an orchestrated service process is a necessary direction to achieve autonomic service composition
Developing Experimental Models for NASA Missions with ASSL
NASA's new age of space exploration augurs great promise for deep space
exploration missions whereby spacecraft should be independent, autonomous, and
smart. Nowadays NASA increasingly relies on the concepts of autonomic
computing, exploiting these to increase the survivability of remote missions,
particularly when human tending is not feasible. Autonomic computing has been
recognized as a promising approach to the development of self-managing
spacecraft systems that employ onboard intelligence and rely less on control
links. The Autonomic System Specification Language (ASSL) is a framework for
formally specifying and generating autonomic systems. As part of long-term
research targeted at the development of models for space exploration missions
that rely on principles of autonomic computing, we have employed ASSL to
develop formal models and generate functional prototypes for NASA missions.
This helps to validate features and perform experiments through simulation.
Here, we discuss our work on developing such missions with ASSL.Comment: 7 pages, 4 figures, Workshop on Formal Methods for Aerospace (FMA'09
A Middleware Framework for Constraint-Based Deployment and Autonomic Management of Distributed Applications
We propose a middleware framework for deployment and subsequent autonomic
management of component-based distributed applications. An initial deployment
goal is specified using a declarative constraint language, expressing
constraints over aspects such as component-host mappings and component
interconnection topology. A constraint solver is used to find a configuration
that satisfies the goal, and the configuration is deployed automatically. The
deployed application is instrumented to allow subsequent autonomic management.
If, during execution, the manager detects that the original goal is no longer
being met, the satisfy/deploy process can be repeated automatically in order to
generate a revised deployment that does meet the goal.Comment: Submitted to Middleware 0
Incorporating prediction models in the SelfLet framework: a plugin approach
A complex pervasive system is typically composed of many cooperating
\emph{nodes}, running on machines with different capabilities, and pervasively
distributed across the environment. These systems pose several new challenges
such as the need for the nodes to manage autonomously and dynamically in order
to adapt to changes detected in the environment. To address the above issue, a
number of autonomic frameworks has been proposed. These usually offer either
predefined self-management policies or programmatic mechanisms for creating new
policies at design time. From a more theoretical perspective, some works
propose the adoption of prediction models as a way to anticipate the evolution
of the system and to make timely decisions. In this context, our aim is to
experiment with the integration of prediction models within a specific
autonomic framework in order to assess the feasibility of such integration in a
setting where the characteristics of dynamicity, decentralization, and
cooperation among nodes are important. We extend an existing infrastructure
called \emph{SelfLets} in order to make it ready to host various prediction
models that can be dynamically plugged and unplugged in the various component
nodes, thus enabling a wide range of predictions to be performed. Also, we show
in a simple example how the system works when adopting a specific prediction
model from the literature
- âŠ