1,955 research outputs found
A Generic Agent Organisation Framework For Autonomic Systems
Autonomic computing is being advocated as a tool for managing large, complex computing systems. Specifically, self-organisation provides a suitable approach for developing such autonomic systems by incorporating self-management and adaptation properties into large-scale distributed systems. To aid in this development, this paper details a generic problem-solving agent organisation framework that can act as a modelling and simulation platform for autonomic systems. Our framework describes a set of service-providing agents accomplishing tasks through social interactions in dynamically changing organisations. We particularly focus on the organisational structure as it can be used as the basis for the design, development and evaluation of generic algorithms for self-organisation and other approaches towards autonomic systems
Autonomic management of multiple non-functional concerns in behavioural skeletons
We introduce and address the problem of concurrent autonomic management of
different non-functional concerns in parallel applications build as a
hierarchical composition of behavioural skeletons. We first define the problems
arising when multiple concerns are dealt with by independent managers, then we
propose a methodology supporting coordinated management, and finally we discuss
how autonomic management of multiple concerns may be implemented in a typical
use case. The paper concludes with an outline of the challenges involved in
realizing the proposed methodology on distributed target architectures such as
clusters and grids. Being based on the behavioural skeleton concept proposed in
the CoreGRID GCM, it is anticipated that the methodology will be readily
integrated into the current reference implementation of GCM based on Java
ProActive and running on top of major grid middleware systems.Comment: 20 pages + cover pag
Towards adaptive multi-robot systems: self-organization and self-adaptation
Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugÀnglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.The development of complex systems ensembles that operate in uncertain environments is a major challenge. The reason for this is that system designers are not able to fully specify the system during specification and development and before it is being deployed. Natural swarm systems enjoy similar characteristics, yet, being self-adaptive and being able to self-organize, these systems show beneficial emergent behaviour. Similar concepts can be extremely helpful for artificial systems, especially when it comes to multi-robot scenarios, which require such solution in order to be applicable to highly uncertain real world application. In this article, we present a comprehensive overview over state-of-the-art solutions in emergent systems, self-organization, self-adaptation, and robotics. We discuss these approaches in the light of a framework for multi-robot systems and identify similarities, differences missing links and open gaps that have to be addressed in order to make this framework possible
Towards formal models and languages for verifiable Multi-Robot Systems
Incorrect operations of a Multi-Robot System (MRS) may not only lead to
unsatisfactory results, but can also cause economic losses and threats to
safety. These threats may not always be apparent, since they may arise as
unforeseen consequences of the interactions between elements of the system.
This call for tools and techniques that can help in providing guarantees about
MRSs behaviour. We think that, whenever possible, these guarantees should be
backed up by formal proofs to complement traditional approaches based on
testing and simulation.
We believe that tailored linguistic support to specify MRSs is a major step
towards this goal. In particular, reducing the gap between typical features of
an MRS and the level of abstraction of the linguistic primitives would simplify
both the specification of these systems and the verification of their
properties. In this work, we review different agent-oriented languages and
their features; we then consider a selection of case studies of interest and
implement them useing the surveyed languages. We also evaluate and compare
effectiveness of the proposed solution, considering, in particular, easiness of
expressing non-trivial behaviour.Comment: Changed formattin
The evolution of tropos: Contexts, commitments and adaptivity
Software evolution is the main research focus of the Tropos group at University of Trento (UniTN): how do we build systems that are aware of their requirements, and are able to dynamically reconïŹgure themselves in response to changes in context (the environment within which they operate) and requirements. The purpose of this report is to offer an overview of ongoing work at UniTN. In particular, the report presents ideas and results of four lines of research: contextual requirements modeling and reasoning, commitments and goal models, developing self-reconïŹgurable systems, and requirements awareness
QoE-centric management of multimedia networks through cooperative control loops
The Internet has evolved from a service to transport simple text files into a platform for transporting a variety of complex multimedia services. The initial centralized management systems were not designed and are therefore not able to perform efficient management of Quality of Experience (QoE) for these complex services. Deploying an autonomic management system resolves these complexity issues and allows efficient resource allocation based on the service type, end-user requirements and device characteristics. However, existing autonomic management systems only allow limited cooperation between different autonomic elements (AE), which limits their capabilities to provide end-to-end QoE assurance. This research will therefore design cooperative AEs, optimize their organization and provide cooperative allocation algorithms to optimize end-to-end QoE
- âŠ