43,211 research outputs found
Multi Site Coordination using a Multi-Agent System
A new approach of coordination of decisions in a multi site system is
proposed. It is based this approach on a multi-agent concept and on the
principle of distributed network of enterprises. For this purpose, each
enterprise is defined as autonomous and performs simultaneously at the local
and global levels. The basic component of our approach is a so-called Virtual
Enterprise Node (VEN), where the enterprise network is represented as a set of
tiers (like in a product breakdown structure). Within the network, each partner
constitutes a VEN, which is in contact with several customers and suppliers.
Exchanges between the VENs ensure the autonomy of decision, and guarantiee the
consistency of information and material flows. Only two complementary VEN
agents are necessary: one for external interactions, the Negotiator Agent (NA)
and one for the planning of internal decisions, the Planner Agent (PA). If
supply problems occur in the network, two other agents are defined: the Tier
Negotiator Agent (TNA) working at the tier level only and the Supply Chain
Mediator Agent (SCMA) working at the level of the enterprise network. These two
agents are only active when the perturbation occurs. Otherwise, the VENs
process the flow of information alone. With this new approach, managing
enterprise network becomes much more transparent and looks like managing a
simple enterprise in the network. The use of a Multi-Agent System (MAS) allows
physical distribution of the decisional system, and procures a heterarchical
organization structure with a decentralized control that guaranties the
autonomy of each entity and the flexibility of the network
Beliefs and Conflicts in a Real World Multiagent System
In a real world multiagent system, where the
agents are faced with partial, incomplete and
intrinsically dynamic knowledge, conflicts are
inevitable. Frequently, different agents have
goals or beliefs that cannot hold simultaneously.
Conflict resolution methodologies have to be
adopted to overcome such undesirable occurrences.
In this paper we investigate the application of
distributed belief revision techniques as the support
for conflict resolution in the analysis of the
validity of the candidate beams to be produced
in the CERN particle accelerators.
This CERN multiagent system contains a higher
hierarchy agent, the Specialist agent, which
makes use of meta-knowledge (on how the conflicting
beliefs have been produced by the other
agents) in order to detect which beliefs should be
abandoned. Upon solving a conflict, the Specialist
instructs the involved agents to revise their
beliefs accordingly.
Conflicts in the problem domain are mapped into
conflicting beliefs of the distributed belief revision
system, where they can be handled by
proven formal methods. This technique builds
on well established concepts and combines them
in a new way to solve important problems. We
find this approach generally applicable in several
domains
DISCO: Distributed Multi-domain SDN Controllers
Modern multi-domain networks now span over datacenter networks, enterprise
networks, customer sites and mobile entities. Such networks are critical and,
thus, must be resilient, scalable and easily extensible. The emergence of
Software-Defined Networking (SDN) protocols, which enables to decouple the data
plane from the control plane and dynamically program the network, opens up new
ways to architect such networks. In this paper, we propose DISCO, an open and
extensible DIstributed SDN COntrol plane able to cope with the distributed and
heterogeneous nature of modern overlay networks and wide area networks. DISCO
controllers manage their own network domain and communicate with each others to
provide end-to-end network services. This communication is based on a unique
lightweight and highly manageable control channel used by agents to
self-adaptively share aggregated network-wide information. We implemented DISCO
on top of the Floodlight OpenFlow controller and the AMQP protocol. We
demonstrated how DISCO's control plane dynamically adapts to heterogeneous
network topologies while being resilient enough to survive to disruptions and
attacks and providing classic functionalities such as end-point migration and
network-wide traffic engineering. The experimentation results we present are
organized around three use cases: inter-domain topology disruption, end-to-end
priority service request and virtual machine migration
Virtual Reality Games for Motor Rehabilitation
This paper presents a fuzzy logic based method to track user satisfaction without the need for devices to monitor users physiological conditions. User satisfaction is the key to any product’s acceptance; computer applications and video games provide a unique opportunity to provide a tailored environment for each user to better suit their needs. We have implemented a non-adaptive fuzzy logic model of emotion, based on the emotional component of the Fuzzy Logic Adaptive Model of Emotion (FLAME) proposed by El-Nasr, to estimate player emotion in UnrealTournament 2004. In this paper we describe the implementation of this system and present the results of one of several play tests. Our research contradicts the current literature that suggests physiological measurements are needed. We show that it is possible to use a software only method to estimate user emotion
Data centric trust evaluation and prediction framework for IOT
© 2017 ITU. Application of trust principals in internet of things (IoT) has allowed to provide more trustworthy services among the corresponding stakeholders. The most common method of assessing trust in IoT applications is to estimate trust level of the end entities (entity-centric) relative to the trustor. In these systems, trust level of the data is assumed to be the same as the trust level of the data source. However, most of the IoT based systems are data centric and operate in dynamic environments, which need immediate actions without waiting for a trust report from end entities. We address this challenge by extending our previous proposals on trust establishment for entities based on their reputation, experience and knowledge, to trust estimation of data items [1-3]. First, we present a hybrid trust framework for evaluating both data trust and entity trust, which will be enhanced as a standardization for future data driven society. The modules including data trust metric extraction, data trust aggregation, evaluation and prediction are elaborated inside the proposed framework. Finally, a possible design model is described to implement the proposed ideas
Ensuring Cyber-Security in Smart Railway Surveillance with SHIELD
Modern railways feature increasingly complex embedded computing systems for surveillance, that are moving towards fully wireless smart-sensors. Those systems are aimed at monitoring system status from a physical-security viewpoint, in order to detect intrusions and other environmental anomalies. However, the same systems used for physical-security surveillance are vulnerable to cyber-security threats, since they feature distributed hardware and software architectures often interconnected by ‘open networks’, like wireless channels and the Internet. In this paper, we show how the integrated approach to Security, Privacy and Dependability (SPD) in embedded systems provided by the SHIELD framework (developed within the EU funded pSHIELD and nSHIELD research projects) can be applied to railway surveillance systems in order to measure and improve their SPD level. SHIELD implements a layered architecture (node, network, middleware and overlay) and orchestrates SPD mechanisms based on ontology models, appropriate metrics and composability. The results of prototypical application to a real-world demonstrator show the effectiveness of SHIELD and justify its practical applicability in industrial settings
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