782,680 research outputs found
Self-Organization in Peer-to-Peer Systems
Peer-to-Peer Systems are about community-based cooperations. The peers share responsibilities and benefits by cooperating in a distributed and decentralized environment. To carry out tasks sensibly, however, a more or less rigid order is required for efficiency and reliability reasons. This order can be partially imposed from the outside, for example within so-called "structed" Peer-to-Peer systems. A common approach here is the use of Distributed Hash Tables. Alternatively, Peer-to-Peer systems can be "unstructured" in the sense that an useful order emerges from own internal processes. Unstructured and structured Peer-to-Peer systems rely both on a more or less decentralized overlay management. Self-organization, therefore, is a key to the success of Peer-to-Peer systems in various forms. This presentation gives an overview of the role of self-organization in Peer-to-Peer systems
Towards Automotive Embedded Systems with Self-X Properties
With self-adaptation and self-organization new paradigms for the management of distributed systems have been introduced. By enhancing the automotive software system with self-X capabilities, e.g. self-healing, self-configuration and self-optimization, the complexity is handled while increasing the flexibility, scalability and dependability of these systems. In this chapter we present an approach for enhancing automotive systems with self-X properties. At first, we discuss the benefits of providing automotive software systems with self-management capabilities and outline concrete use cases. Afterwards, we will discuss requirements and challenges for realizing adaptive automotive embedded systems
Adapting Quality Assurance to Adaptive Systems: The Scenario Coevolution Paradigm
From formal and practical analysis, we identify new challenges that
self-adaptive systems pose to the process of quality assurance. When tackling
these, the effort spent on various tasks in the process of software engineering
is naturally re-distributed. We claim that all steps related to testing need to
become self-adaptive to match the capabilities of the self-adaptive
system-under-test. Otherwise, the adaptive system's behavior might elude
traditional variants of quality assurance. We thus propose the paradigm of
scenario coevolution, which describes a pool of test cases and other
constraints on system behavior that evolves in parallel to the (in part
autonomous) development of behavior in the system-under-test. Scenario
coevolution offers a simple structure for the organization of adaptive testing
that allows for both human-controlled and autonomous intervention, supporting
software engineering for adaptive systems on a procedural as well as technical
level.Comment: 17 pages, published at ISOLA 201
Universality in spectral condensation
Self-organization is the spontaneous formation of spatial, temporal, or spatiotemporal patterns in complex systems far from equilibrium. During such self-organization, energy distributed in a broadband of frequencies gets condensed into a dominant mode, analogous to a condensation phenomenon. We call this phenomenon spectral condensation and study its occurrence in fluid mechanical, optical and electronic systems. We define a set of spectral measures to quantify this condensation spanning several dynamical systems. Further, we uncover an inverse power law behaviour of spectral measures with the power corresponding to the dominant peak in the power spectrum in all the aforementioned systems
Assessing self-organization and emergence in Evolvable Assembly Systems (EAS)
Dissertação para obtenção do Grau de Mestre em
Engenharia Electrotécnica e de ComputadoresThere is a growing interest from industry in the applications of distributed IT. Currently, most modern plants use distributed controllers either to control production processes, monitor them or both.
Despite the efforts on the last years to improve the implementation of the new manufacturing paradigms, the industry is still mainly using traditional controllers. Now, more than ever, with an economic crisis the costumers are searching for cheap and customized products, which represents a great opportunity for the new paradigms to claim their space in the market.
Most of the research on distributed manufacturing is regarding the control and communication infrastructure. They are key aspects for self-organization and there is a lack of study on the metrics that regulate the self-organization and autonomous response of modern production paradigms.
This thesis presents a probabilistic framework that promotes self-organization on a multiagent system based on a new manufacturing concept, the Evolvable Assembly Systems/Evolvable Production Systems. A methodology is proposed to assess the impact of self-organization on the system behavior, by the application of the probabilistic framework that has the dual purpose of controlling and explaining the system dynamics.
The probabilistic framework shows the likelihood of some resources being allocated
to the production process. This information is constantly updated and exchanged by the
agents that compose the system. The emergent effect of this self-organization dynamic is
an even load balancing across the system without any centralized controller.
The target systems of this work are therefore small systems with small production
batches but with a high variability of production conditions and products.
The agents that compose the system originated in the agent based architecture of the FP7-IDEAS proejct. This work has extended these agents and the outcome has been tested in the IDEAS demonstrators, as the changes have been incorporated in the latest version of the architecture, and in a simulation and more controlled environment were the proposed metric and its influence were assessed
Universality in spectral condensation
Self-organization is the spontaneous formation of spatial, temporal, or
spatiotemporal patterns in complex systems far from equilibrium. During such
self-organization, energy distributed in a broadband of frequencies gets
condensed into a dominant mode, analogous to a condensation phenomena. We call
this phenomenon spectral condensation and study its occurrence in fluid
mechanical, optical and electronic systems. We define a set of spectral
measures to quantify this condensation spanning several dynamical systems.
Further, we uncover an inverse power law behaviour of spectral measures with
the power corresponding to the dominant peak in the power spectrum in all the
aforementioned systems.Comment: 5 pages, 3 figure
Toward multi-target self-organizing pursuit in a partially observable Markov game
The multiple-target self-organizing pursuit (SOP) problem has wide
applications and has been considered a challenging self-organization game for
distributed systems, in which intelligent agents cooperatively pursue multiple
dynamic targets with partial observations. This work proposes a framework for
decentralized multi-agent systems to improve intelligent agents' search and
pursuit capabilities. We model a self-organizing system as a partially
observable Markov game (POMG) with the features of decentralization, partial
observation, and noncommunication. The proposed distributed algorithm: fuzzy
self-organizing cooperative coevolution (FSC2) is then leveraged to resolve the
three challenges in multi-target SOP: distributed self-organizing search (SOS),
distributed task allocation, and distributed single-target pursuit. FSC2
includes a coordinated multi-agent deep reinforcement learning method that
enables homogeneous agents to learn natural SOS patterns. Additionally, we
propose a fuzzy-based distributed task allocation method, which locally
decomposes multi-target SOP into several single-target pursuit problems. The
cooperative coevolution principle is employed to coordinate distributed
pursuers for each single-target pursuit problem. Therefore, the uncertainties
of inherent partial observation and distributed decision-making in the POMG can
be alleviated. The experimental results demonstrate that distributed
noncommunicating multi-agent coordination with partial observations in all
three subtasks are effective, and 2048 FSC2 agents can perform efficient
multi-target SOP with almost 100% capture rates
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