247,037 research outputs found
Towards a Staging Environment for the Internet of Things
Internet of Things (IoT) applications promise to make many aspects of our
lives more efficient and adaptive through the use of distributed sensing and
computing nodes. A central aspect of such applications is their complex
communication behavior that is heavily influenced by the physical environment
of the system. To continuously improve IoT applications, a staging environment
is needed that can provide operating conditions representative of deployments
in the actual production environments -- similar to what is common practice in
cloud application development today. Towards such a staging environment, we
present Marvis, a framework that orchestrates hybrid testbeds, co-simulated
domain environments, and a central network simulation for testing distributed
IoT applications. Our preliminary results include an open source prototype and
a demonstration of a Vehicle-to-everything (V2X) communication scenario
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 zugänglich.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
Distributed Learning System Design: A New Approach and an Agenda for Future Research
This article presents a theoretical framework designed to guide distributed learning design, with the goal of enhancing the effectiveness of distributed learning systems. The authors begin with a review of the extant research on distributed learning design, and themes embedded in this literature are extracted and discussed to identify critical gaps that should be addressed by future work in this area. A conceptual framework that integrates instructional objectives, targeted competencies, instructional design considerations, and technological features is then developed to address the most pressing gaps in current research and practice. The rationale and logic underlying this framework is explicated. The framework is designed to help guide trainers and instructional designers through critical stages of the distributed learning system design process. In addition, it is intended to help researchers identify critical issues that should serve as the focus of future research efforts. Recommendations and future research directions are presented and discussed
Towards Adaptable and Adaptive Policy-Free Middleware
We believe that to fully support adaptive distributed applications,
middleware must itself be adaptable, adaptive and policy-free. In this paper we
present a new language-independent adaptable and adaptive policy framework
suitable for integration in a wide variety of middleware systems. This
framework facilitates the construction of adaptive distributed applications.
The framework addresses adaptability through its ability to represent a wide
range of specific middleware policies. Adaptiveness is supported by a rich
contextual model, through which an application programmer may control precisely
how policies should be selected for any particular interaction with the
middleware. A contextual pattern mechanism facilitates the succinct expression
of both coarse- and fine-grain policy contexts. Policies may be specified and
altered dynamically, and may themselves take account of dynamic conditions. The
framework contains no hard-wired policies; instead, all policies can be
configured.Comment: Submitted to Dependable and Adaptive Distributed Systems Track, ACM
SAC 200
Organization of Multi-Agent Systems: An Overview
In complex, open, and heterogeneous environments, agents must be able to
reorganize towards the most appropriate organizations to adapt unpredictable
environment changes within Multi-Agent Systems (MAS). Types of reorganization
can be seen from two different levels. The individual agents level
(micro-level) in which an agent changes its behaviors and interactions with
other agents to adapt its local environment. And the organizational level
(macro-level) in which the whole system changes it structure by adding or
removing agents. This chapter is dedicated to overview different aspects of
what is called MAS Organization including its motivations, paradigms, models,
and techniques adopted for statically or dynamically organizing agents in MAS.Comment: 12 page
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