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Ein sehr großer Anteil der in Rechensystemen auftretenden Fehler ereignet sich im Speicher. In dieser Arbeit wird ein zerlegungsorientiertes Modell entwickelt, das die Wechselwirkungen zwischen Speicherfehlern und Systemleistung untersucht. Zunächst wird das Speicherverhalten eines Auftrags durch ein mehrphasiges Independent-Reference-Modell charakterisiert. Dies dient als Grundlage eines Modells zum Auftreten von Störungen, in das Lastcharakteristika wie die Auftrags-Verweildauer, die Seitenzugriffs-Rate und die Paging-Rate eingehen. Anschließend kann die Wahrscheinlichkeit, mit der ein Speicherfehler entdeckt wird, berechnet werden. Die zur Behandlung von Speicherfehlern erforderlichen Maßnahmen bestimmen die mittlere durch Fehler induzierte Last. Die Wechselwirkungen zwischen Fehler- und Leistungsverhalten werden durch ein System nichtlinearer Gleichung beschrieben, für dessen Lösung ein iteratives Verfahren abgeleitet wird. Abschließend wird mit ausführlichen Beispielen das Modell erläutert und der Einfluß einiger Modell-Parameter auf Leistungs- und Zuverlässigkeitskenngrößen untersucht.
Das Kapitel (aus dem Buch "Mikrorechner-Systeme : Mikroprozessoren, Speicher, Peripherie", siehe Quelle) behandelt verschiedene Konzepte der Speicherverwaltung und stellt Bausteine vor, die diese Verwaltung hardwaremäßig durchführen. Außerdem werden verschiedene Maßnahmen zur Hardware-Unterstützung von Mikroprozessor-Betriebssystemen beschrieben.
Nowadays, smartphones and sensor devices can provide a variety of information about a user’s current situation. So far, many recommender systems neglect this kind of information and thus cannot provide situationspecific recommendations. Situation-aware recommender systems adapt to changes in the user’s environment and therefore are able to offer recommendations that are more appropriate for the current situation. In this paper, we present a software architecture that enables situation awareness for arbitrary recommendation techniques. The proposed system considers both (semi-)static user profiles and volatile situational knowledge to obtain meaningful recommendations. Furthermore, the implementation of the architecture in a museum of natural history is presented, which uses Complex Event Processing to achieve situation awareness.
In service-oriented architectures the management of services is a crucial task during all stages of IT operations. Based on a case study performed for a group of finance companies the different aspects of service management are presented. First, the paper discusses how services must be described for management purposes. In particular, a special emphasis is placed on the integration of legacy/non web services. Secondly, the service lifecycle that underlies service management is presented. Especially, the relation to SOA governance and an appropriate tool support by registry repositories is outlined.
In this article, we present the software architecture of a new generation of advisory systems using Intelligent Agent and Semantic Web technologies. Multi-agent systems provide a well-suited paradigm to implement negotiation processes in a consultancy situation. Software agents act as clients and advisors, using their knowledge to assist human users. In the presented architecture, the domain knowledge is modeled semantically by means of XML-based ontology languages such as OWL. Using an inference engine, the agents reason, based on their knowledge to make decisions or proposals. The agent knowledge consists of different types of data: on the one hand, private data, which has to be protected against unauthorized access; and on the other hand, publicly accessible knowledge spread over different Web sites. As in a real consultancy, an agent only reveals sensitive private data, if they are indispensable for finding a solution. In addition, depending on the actual consultancy situation, each agent dynamically expands its knowledge base by accessing OWL knowledge sources from the Internet. Due to the standardization of OWL, knowledge models easily can be shared and accessed via the Internet. The usefulness of our approach is proved by the implementation of an advisory system in the Semantic E-learning Agent (SEA) project, whose objective is to develop virtual student advisers that render support to university students in order to successfully organize and perform their studies.
In this paper, we consider the route coordination problem in emergency evacuation of large smart buildings. The building evacuation time is crucial in saving lives in emergency situations caused by imminent natural or man-made threats and disasters. Conventional approaches to evacuation route coordination are static and predefined. They rely on evacuation plans present only at a limited number of building locations and possibly a trained evacuation personnel to resolve unexpected contingencies. Smart buildings today are equipped with sensory infrastructure that can be used for an autonomous situation-aware evacuation guidance optimized in real time. A system providing such a guidance can help in avoiding additional evacuation casualties due to the flaws of the conventional evacuation approaches. Such a system should be robust and scalable to dynamically adapt to the number of evacuees and the size and safety conditions of a building. In this respect, we propose a distributed route recommender architecture for situation-aware evacuation guidance in smart buildings and describe its key modules in detail. We give an example of its functioning dynamics on a use case.
In recent years, multiple efforts for reducing energy usage have been proposed. Especially buildings offer high potentials for energy savings. In this paper, we present a novel approach for intelligent energy control that combines a simple infrastructure using low cost sensors with the reasoning capabilities of Complex Event Processing. The key issues of the approach are a sophisticated semantic domain model and a multi-staged event processing architecture leading to an intelligent, situation-aware energy management system.
Complex Event Processing (CEP) has been established as a well-suited software technology for processing high-frequent data streams. However, intelligent stream based systems must integrate stream data with semantical background knowledge. In this work, we investigate different approaches on integrating stream data and semantic domain knowledge. In particular, we discuss from a software engineering per- spective two different architectures: an approach adding an ontology access mechanism to a common Continuous Query Language (CQL) is compared with C-SPARQL, a streaming extension of the RDF query language SPARQL.
In huge warehouses or stockrooms, it is often very difficult to find a certain item, because it has been misplaced and is therefore not at its assumed position. This position paper presents an approach on how to coordinate mobile RFID agents using a blackboard architecture based on Complex Event Processing.
Smart Cities require reliable means for managing installations that offer essential services to the citizens. In this paper we focus on the problem of evacuation of smart buildings in case of emergencies. In particular, we present an abstract architecture for situation-aware evacuation guidance systems in smart buildings, describe its key modules in detail, and provide some concrete examples of its structure and dynamics.