Many novel location-based services (LBS) such as a friend finder service require knowledge about the positions of mobile users. Usually, location services are used to manage these positions, and for providing basic functionality like spatial range queries or spatial events to the LBS. Managing and using the positions of mobile users raises privacy issues, in particular, if the providers of LBS and location services are only partially trusted. Many different approaches for preserving a user's privacy have been proposed in the literature, e.g. location obfuscation and the k-anonymity concept. However, most of them are not suitable if both LBS and location service providers are non-trusted. In contrast to these approaches, we present a novel approach for the secure management of private position information in partially trusted system environments. The main contribution in this paper is a position sharing concept which allows for the distribution of position information (shares) of strictly limited accuracy onto several location servers of different providers. With this approach, a compromised server will only reveal information of limited accuracy. Moreover, we will show how position shares of coarse granularity from multiple location servers can be fused into information of higher precision to satisfy the accuracy requirements of different LBS.

This paper introduces mechanisms for the automated detection of mobile objects in urban areas. Widely available devices such as mobile phones with integrated proximity sensors such as RFID readers or Bluetooth cooperatively perform sensing operations to discover mobile objects. In this paper, we propose a coverage metric for assessing the completeness of sensing that considers spatial and temporal aspects. To maximize coverage while minimizing energy consumption of mobile nodes, we propose both a centralized and a distributed coordination algorithm for selecting nodes that need to sense. Moreover, we present strategies that allow selected nodes to perform efficient sense operations. By extensive simulations, we show that distributed coordination achieves drastic energy savings of up to 63%, while limiting the coverage loss to 13%. Moreover, we show that the centralized algorithm loses less than 1% coverage compared to the maximum possible coverage.

Distributed Hash Table (DHT)-based peer-to-peer information discovery systems have emerged as highly scalable systems for information storage and discovery in massively distributed networks. Originally DHTs supported only point queries. However, recently they have been extended to support more complex queries, such as multiattribute range (MAR) queries. Generally, the support for MAR queries over DHTs has been provided either by creating an individual index for each data attribute or by creating a single index using the combination of all data attributes. In contrast to these approaches, we propose to create and modify indices using the attribute combinations that dynamically appear in MAR queries in the system. In this paper, we present an adaptive information discovery system that adapts the set of indices according to the dynamic set of MAR queries in the system. The main contribution of this paper is a four-phase index adaptation process. Our evaluations show that the adaptive information discovery system continuously optimizes the overall system performance for MAR queries. Moreover, compared to a non-adaptive system, our system achieves several orders of magnitude improved performance.

The use of RFID devices for real-time production monitoring in modern factories is impeded by the inherent unreliability of RFID devices. In this paper we present a consistency stack that conceptually divides the different consistency issues in production monitoring into separate layers. In addition to this we have built a consistency management framework to ensure consistent real-time production monitoring, using unreliable RFID devices. In detail, we deal with the problem of detecting object sequences by a set of unreliable RFID readers that are installed along production lines. We propose a probabilistic sequence detection algorithm that assigns probabilities to objects detected by RFID devices and provides probabilistic guarantees regarding the real-time sequences of objects on the production lines.

In this paper we introduce mechanisms for automated mapping of urban areas that provide a virtual sensor abstraction to the applications. We envision a participatory system that exploits widely available devices as mobile phones to cooperatively read environmental conditions as air quality or noise pollution, and map these measurements to stationary virtual sensors. We propose spatial and temporal coverage metrics for measuring the quality of acquired sensor data that reflect the conditions of urban areas and the uncontrolled movement of nodes. To achieve quality requirements and efficiency in terms of energy consumption, this paper presents two algorithms for coordinating sensing. The first is based on a central control instance, which assigns sensing tasks to mobile nodes based on movement predictions. The second algorithm is based on coordination of mobile nodes in an ad-hoc network. By extensive simulations, we show that these algorithms achieve a high quality of readings, which is about 95% of the maximum possible. Moreover, the algorithms achieve a very high energy efficiency allowing for drastic savings compared to uncoordinated sensing.

Peer-to-peer (P2P) networks allow for efficient information discovery in large-scale distributed systems. Although point queries are well supported by current P2P systems – in particular systems based on distributed hash tables (DHTs) –, providing efficient support for more complex queries remains a challenge. Our research focuses on the efficient support for multi-attribute range (MAR) queries over DHT-based information discovery systems. Traditionally, the support for MAR queries over DHTs has been provided either by creating an individual index for each data attribute or by creating a single index using the combination of all data attributes. In contrast to these approaches, we propose to create a set of indices over selected attribute combinations. In order to limit the overhead induced by index maintenance, the total number of created indices has to be limited. Thus, the resulting problem is to create a limited number of indices such that the overall system performance is optimal for MAR queries. In this paper, we propose an index recommendation tool that implements heuristic solutions to this NP-hard problem. Our evaluations show that these heuristics lead to a close-to-optimal system performance for MAR queries.

Application areas like global sensor networks and data stream processing involve the on-line processing of large amounts of data in an overlay network of operators on top of the Internet infrastructure. Trying to fulfill QoS guarantees in such networks is a challenging task that should be realized under the requirement for optimal usage of common resources in the network. Therefore in this paper, we formalize a constrained optimization problem for the placement of operators in an overlay network which strives for satisfying user QoS constraints subject to latency, while minimizing the network load induced by the deployment of the operators in the network. Since the initial problem is NP-hard, we solve at a first step the problem in an intermediate continuous latency space and then we map the continuous solution to its discrete variant. Our evaluations provide an analysis about the inherent interdepedence between the two metrics, network usage and latency, subject to this paper and furthermore shows that our algorithm achieves a good balance between the user requirements and the usage of the network resources.

Scaling heterogeneous information systems (HIS) to thousands of sources poses particular challenges to source discovery. It requires a powerful formalism for describing the contents of the sources in a concise manner and for formulating compatible queries as well as a suitable structure for indexing and retrieving the source descriptions efficiently. We propose an extended logic-based description formalism for large-scale HIS with structured sources and a shared ontology. The formalism refines existing approaches that describe the sources by constraints on the attribute value ranges in several ways: It allows for complex, nested descriptions based on defined classes. It supports alternative descriptions to express that a source may be discovered by different combinations of constraints. Finally, it allows to adjust between positive matching, similar to keyword-based discovery, and negative matching, as used in existing logic-based approaches. We further propose the SDC-Tree for indexing such source descriptions. To allow for efficient discovery, the SDC-Tree features multidimensional indexing capabilities for the different attributes and the IS-A hierarchy of the shared ontology, but also incorporates the existence or absence of constraints. For this purpose, it supports three different types of node split operations which exploit the expressiveness of the description formalism. Therefore, we also propose a generic split algorithm which can be used with arbitrary ontologies.

Processing streams of data in an overlay network of operators distributed over a wide-area network is a common idea shared by different applications such as distributed event correlation systems and large-scale sensor networks. In order to utilize network resources efficiently and allow for the parallel deployment of a large number of large-scale operator networks, suitable placement algorithms are vital that place operators on physical nodes. In this paper, we present a distributed placement algorithm that minimizes the bandwidth-delay product of data streams between operators of the network in order to reduce the induced network load. Since the fundamental optimization problem is NP-hard, we propose a heuristic solution. First, we calculate an optimal solution in an intermediate continuous search space, called latency space. Subsequently the continuous solution is mapped to the physical network. Our evaluations show that this algorithm reduces the resulting network load significantly compared to state of the art algorithms and achieves results close to the optimum.

A context-based communication system enables the indirect addressing and routing of messages according to the users' contexts. This provides, for example, the means to send a message to all students on campus who attend a certain class, with information about an upcoming exam. However, for a targeted forwarding of messages towards users, the routers need information about the context of connected users. Global knowledge, i.e., each router knowing about every user, is not scalable, though, because of the necessary update messages to keep this information up-to-date. To address this challenge, a router can aggregate similar contexts and only provide such an aggregated view to neighboring routers. In this paper, we present an approach to aggregate similar contexts, based on a similarity measure for user contexts. The algorithm can be adjusted according to the observed messages and user contexts in the system by specifying a similarity threshold to determine when contexts are aggregated. The aggregation of user contexts improves the scalability of our approach by significantly reducing the load of context updates by up to 30%, depending on the usage of the system. This improvement comes at the cost of a negligible increase in false positive messages due to the loss of information used for forwarding messages.

Wireless Mesh Networks are cost-efficient medium-scale networks that have the potential to serve as an infrastructure for advanced location-based services. As a basis for these services we present a routing algorithm that allows to address intuitive symbolic coordinates. This algorithm is based on a proactively maintained geographic routing structure that mimics the structure of a symbolic location model. Message forwarding is done greedily along short paths defined by a symbolic location model and if this fails, through an hierarchical overlay network built by selected mesh routers. We show how a geocast communication mechanism that allows to send messages to all hosts within a specific location can be implemented with this routing algorithm. In extensive evaluations we show that a low proactive routing overhead allows to achieve high message delivery rates even in case of mobility. Moreover, we show that the paths achieved are only 25% longer than the theoretic optimal paths for a wide range of simulation settings.

Context aware systems use context information to adapt their behaviour accordingly. In order to derive high level context information from low level context, such as sensor values, context reasoning methods that correlate observable context information, are necessary. Several context reasoning mechanisms have been proposed in the literature. Usually these mechanisms are centralized, leading to suboptimal utilization of network resources and poor system performance in case of large-scale scenarios. Therefore to increase the scalability of context reasoning systems the development of methods that distribute the reasoning process is necessary. Existing distributed approaches are method specific and do not provide a generic formalization for distributed reasoning. In this paper we introduce a novel system which enables distributed context reasoning in a generic way that is independent of the reasoning algorithm.

Mobile clients in context-aware systems benefit from the indirect addressing of users via their context (contextcast), such as addressing messages to all users in downtown Toronto whose age is below 35. There is, however, almost no support for a temporal decoupling in such a contextcast system, i.e., the addressing of users that were or will be in a certain context in the past or future, respectively. This could for instance be used to distribute the minutes of a meeting to all people who attended the meeting in room 1.138, 3 days ago, between 1 and 3 pm. To enable a context-aware communication system to address messages with temporal relations, especially those contexts in the past, the system needs to manage information about user context histories. This poses the risk that the system can be abused to profile users, which would most probably hinder acceptance. Therefore, privacy aspects need to be considered in the core design of such a system. We present an extension to our earlier work, which allows a temporal decoupling of messages and users and requires very little additional overhead to manage historic context information. The solution includes mechanisms to efficiently disseminate messages to both users with past and future contexts, while effectively preventing user profiling through the use of virtual identities.

In this paper, we present a Peer-to-Peer (P2P) spatial information discovery system that enables spatial range queries over Distributed Hash Tables (DHTs). Our system utilizes a less-distorting octahedral map projection in contrast to the quadrilateral projections used by majority of the previously proposed systems, to represent the spatial information. We also introduce a Space-Filling Curve (SFC)-based data placement strategy that reduces the probability of data hot-spots in the network. Moreover, we show that our system achieves scalable resolution of location-based range queries by utilizing a tree-based query optimization algorithm. Compared to the basic query resolution algorithm, the query optimization algorithm reduces the average number of parallel messages used to resolve a query, by a factor of 96%.

The dissemination of messages according to clients' contexts (i.e., location and other attributes) opens up new possibilities in context-aware systems. While geocast or content-based publish/subscribe forward messages according to client location or attributes, respectively, neither uses a combination of the two. In this paper, we present this new communication paradigm and the challenges it poses. We also extend concepts from publish/subscribe networks to efficiently deal with highly dynamic user location to lower update rates by approximating the user's location. This reduces update rates by between 25% and 90%, depending on the granularity of the approximation.

In this paper we introduce a novel scenario for environmental sensing based on the combination of simple and cheap RFID-based sensors and mobile devices like mobile phones with integrated RFID readers. We envision a system, where the mobile nodes cooperatively read sensors installed in the environment as they pass by and transmit the data to a server infrastructure. To achieve quality requirements on the one hand, and on the other hand efficiency in terms of communication cost and energy consumption, this paper presents several algorithms for coordinating update operations. Mobile nodes form an ad-hoc network for the cooperative management of requested update times to meet the desired update interval and to avoid redundant sensor reading and collisions during read operations. Besides this decentralized coordination algorithm, we also show a complementary algorithm that exploits infrastructure based coordination. By extensive simulations we show that our algorithms achieve a high quality of sensor updates where nearly 100% of the possible updates are performed. Moreover, the algorithms achieve a very high energy efficiency allowing for several hundred hours of operation assuming a typical battery of a mobile phone.

Moving objects databases (MODs) have been proposed for managing trajectory data, an important kind of information for pervasive applications. To save storage capacity, a MOD generally stores simplified trajectories only. A simplified trajectory approximates the actual trajectory of the mobile object according to a certain accuracy bound. In order to minimize the costs of communicating position information between mobile object and MOD, the trajectory simplification should be performed by the mobile object. To assure that the MOD always has a valid simplified trajectory of the remote object, we propose the generic remote trajectory simplification protocol (GRTS) allowing for computing and managing a simplified trajectory in such a system in real-time. We show how to combine GRTS with existing line simplification algorithms for computing the simplified trajectory and analyze trade-offs between the different algorithms. Our evaluations show that GRTS outperforms the two existing approaches by a factor of two and more in terms of reduction efficiency. Moreover, on average, the reduction efficiency of GRTS is only 12% worse compared to optimal offline simplification.

In this paper, we present the system design and evaluation of a Space-Filling Curve (SFC)-based P2P information discovery system OID. The OID system uses multiple SFCs to significantly optimize the performance of multi-attribute range queries, particularly for applications with a large number of data attributes where a single big SFC-based index is inefficient. The basic idea is to have multiple SFCbased indices and select the best one to perform a query. We also introduce two tree-based query optimizations that increase the scalability of the system.

Space-partitioned Moving Objects Databases (SP-MODs) allow for the scalable, distributed management of large sets of mobile objects' trajectories by partitioning the trajectory data to a network of database servers. Processing a spatio-temporal query q therefore requires efficiently routing q to the servers storing the affected trajectory segments. With a coordinate-based query - like a spatio-temporal range query - the relevant servers are directly determined by the queried range. However, with trajectory-based queries - like retrieving the distance covered by a certain object during a given time interval - the relevant servers depend on actual movement of the queried object. Therefore, efficient routing mechanisms for trajectory-based queries are an important challenge in SP-MODs. In this paper, we present the Distributed Trajectory Index (DTI) that allows for such efficient query routing by creating an overlay network for each trajectory. We further present an enhanced index called DTI+S. It accelerates the processing of queries on aggregates of dynamic attributes, like the maximum speed during a time interval, by augmenting DTI with summaries of trajectory segments. Our simulations with a network of 1000 database servers show that DTI+S can reduce the overall processing time by more than 98%.

In diesem Artikel stellen wir ein neuartiges kontextbezogenes Kommunikationsparadigma namens Contextcast vor. Contextcast ermöglicht das selektive Senden von Nachrichten an Teilnehmer mit einem bestimmten Kontext, wobei der Kontext eines Teilnehmers beispielsweise durch seinen Aufenthaltsort, seine Interessen oder seine Situation bestimmt ist. Typische Anwendungen für Contextcast sind die gezielte Verteilung von Warnmeldungen, Touristeninformationen oder Veranstaltungshinweise. Wir präsentieren zunächst Konzepte zur effizienten Vermittlung von ortsbezogenen Informationen (Geocast) und diskutieren anschließend notwendige Erweiterungen für die effiziente Realisierung der Contextcast-Kommunikation.

Moving objects databases (MODs) store objects’ trajectories by spatiotemporal polylines that approximate the actual movements given by sequences of sensed positions. Determining such a polyline with as few vertices as possible under the constraint that it does not deviate by more than a certain accuracy bound epsilon from the sensed positions is an algorithmic problem known as trajectory reduction. A specific challenge is online trajectory reduction, i.e. continuous reduction with position sensing in realtime. This particularly is required for moving objects with embedded position sensors whose movements are tracked and stored by a remote MOD. In this paper, we present Connection-preserving Dead Reckoning (CDR), a new approach for online trajectory reduction. It outperforms the existing approaches by 30 to 50%. CDR requires the moving objects to temporally store some of the previously sensed positions. Although the storage consumption of CDR generally is small, it is not bounded. We therefore further present CDRM whose storage allocation and execution time per position fix can be adjusted and limited. Even with very limited storage allocations of less than 1 kB CDRM outperforms the existing approach by 20 to 40%.

In this paper, we propose an overlay network supporting world-wide geographic messaging. Our approach is based on hierarchical symbolic coordinates like /usa/fl/miami/. Although hierarchical network topologies lend themselves to the implementation of such overlay networks, they may lead to bottlenecks at the root of the hierarchy, long message paths, and inefficient bandwidth utilization. To avoid these problems, we propose an overlay network that adapts its structure to the users' communication patterns by dynamically adding shortcut links to the hierarchy leading to a routing mesh. We present an algorithm that carefully selects shortcuts based on their utility to assure short message paths on the one hand and to reduce the induced overhead on the other hand. Through simulations we show that this approach decreases the average path length significantly and reduces network load to about 50% compared to hierarchical routing.

Nowadays most context-aware applications are independent proprietary pieces of software. A general framework or middleware deployed in the field does not exist; therefore the implementation of context-aware applications and services assumes the development of the whole application stack for each application. Along these development issues, deployment and privacy problems are to be solved. This imposes the following challenges concerning a middleware for context-aware applications: (1) We need an architecture that allows to implement and deploy services easily on the network. (2) We need a user interface that is widespread, well known to users and allows to mange one’s privacy settings for every single service transparently. In this paper we describe our middleware’s architecture for context-aware applications, based on messenger protocols.

Geocast, which allows for forwarding messages to hosts residing at specified geographic areas, is a promising communication paradigm with a wide range of applications. Geocast target areas can be specified either by geometric figures or symbolic addresses, such as /usa/fl/miami/market-street. In this paper, we present a novel geocast routing protocol for symbolically addressed messages. Compared to geocast protocols based on geometric information, our protocol can operate on simple symbolic location models, and message forwarding does not require costly geometric operations. The proposed protocol is based on an overlay network that is mapped to an IP-based network infrastructure. The overlay network is structured in a hierarchical fashion, to ensure a scalable global geocast service supporting also large target areas. Although our protocol does not rely on a layer 3 multicast protocol, we also show how to improve the performance of message forwarding by integrating a light-weight layer 3 multicast protocol. Our evaluations of the protocol underline the scalability of our approach and show good routing quality leading to short message paths.

In diesem Beitrag wird aufgezeigt, welche Möglichkeiten sich durch den Einsatz task-orientierter, explorativer Anwendungen im Umfeld einer Smart Factory ergeben. Nach einer kurzen Charakterisierung dieser Anwendungsklasse wird ein Szenario geschildert, das Wartungsaufgaben in einer Fabrik mit diesen Konzepten löst. Daraus ergibt sich die Vision einer Smart Factory, in der die Geschäftsprozesse über ein Kontextmodell mit den technischen Prozessen der Produktionsstraße gekoppelt werden.

Geocast is used to send messages to all hosts located in a geographic area. This target area can be defined either by geometric figures like polygons or by symbolic addresses like city names or room numbers. Geographic routing algorithms, which forward messages based on geographic information, can be used to forward geocast messages. If routing of symbolically addressed messages is based on geometric coordinates, complex mappings between symbolic addresses and their geometric extent as well as complex geometric operations are required. Therefore, we propose a routing algorithm for symbolically addressed geocast messages that operates directly on a symbolic location model. This approach does not require any geometric information for message forwarding, and forwarding decisions can be realized efficiently by comparably simple operations.

Die rasant fortschreitende Entwicklung von drahtloser Kommunikation, Positionierungssystemen und Rechnertechnologie sowie deren Integration in multifunktionale Endgeräte unterstützt die vielversprechende neue Anwendungsklasse der ortsbezogenen Systeme. Ortsinformation kann von solchen Anwendungen genutzt werden, um ihr Verhalten dem aktuellen Standort der Benutzer oder auch anderer Objekte anzupassen. Heute schon bieten Netzbetreiber so genannte ``Location-based Services'' an, die primär Navigationsfunktionen und eine ortsbezogene Selektion von Informationen unterstützen. Ortsinformation kann aber auch auf der Systemebene gewinnbringend verwendet werden, etwa zur Bereitstellung neuer ortsbezogener Kommunikationskonzepte oder zur Optimierung der Kommunikation. In diesem Beitrag wird der Begriff der ortsbezogene Anwendungen erläutert und Anwendungen dieser Art am Beispiel existierender Systeme kurz skizziert. Außerdem werden zwei Beispiele für die Nutzung von Ortsinformation auf Systemebene gegeben, die Geocast-Kommunikation und ein Hoarding-Verfahren.

Geographic communication (geocast) is used to send messages to geographic areas, e.g. to distribute warning messages or other information within these areas. It is based on a location model which is used to determine a message's target area and the receivers' positions and therefore has strong influence on the achievable granularity of geographic addressing. A hybrid location model and and a fine-grained addressing scheme for geocast based on this model are presented in this paper which support two- and three-dimensional geometric locations as well as symbolic locations like room numbers, embedded local coordinate systems, and mobile target areas like trains.

The rapid development of mobile communication networks and the availability of miniaturized and inexpensive sensor technology allow for the development of multifunctional mobile devices that are able to collect and communicate context information. We also currently see a clear trend towards the integration of embedded systems including sensors into ßmart`` everyday things, which is also referred to as Ubiquitous Computing. The deployment of sensor technology allows for so-called context-aware applications, going far beyond of providing mobile access to information and computing resources. Context-aware applications exploit captured sensor information to adapt to the current situation of mobile users. For instance, the information offered to a user may depend on his current location, and the way how it is presented to him may depend on the speed he moves, whether he is on its own or with others, and so on. In this paper, we characterize context-aware applications and present the vision of a digital world model as the foundation for this class of applications. Further, the paper discusses the benefits and reseach challenges associated with digital world models, which allow applications to take into account the state of the real world and react to state changes.

GeoCast provides the functionality of sending messages to everyone in a specific area. So far, only the addressing of larger two-dimensional areas was possible. For the use in an urban environment it is crucial that small and three-dimensional areas can be addressed. For example, GeoCast can then be used to send lecture notes to all in a classroom. In this paper we describe a fine-grained addressing concept for GeoCast that supports such areas. In addition we present an architecture that allows the use of that addressing concept together with the GeoRouting-approach developed by Navas and Imielinski. We also present some modifications necessary to enhance the scalability of GeoCast.

Ortsbezogene Anwendungen versorgen Benutzer mit Diensten und Informationen in Abhängigkeit ihrer aktuellen Position. Beispiele sind im Bereich der Telematikdienste, Touristenführer und Informationsdienste zu finden. Anwendungen können sich an den Ort oder ganz allgemein an den Kontext des Benutzers anpassen, indem sie ortsspezifische Informationen anzeigen oder Daten der jeweiligen Situation entsprechend präsentieren. Es existieren verschieden Ansätze und Architekturen, um ortsbezogene Anwendungen zu realisieren. In diesem Beitrag stellen wir unterschiedliche Ansätze vor, diskutieren deren Vor- und Nachteile und leiten daraus ein abstraktes Anwendungsmodell für ortsbezogene Anwendungen ab. Des Weiteren stellen wir Entwicklungswerkzeuge vor, die wir auf Basis dieses Anwendungsmodells konzipiert haben. Die Kombination aus Anwendungsmodell und spezialisierten Werkzeugen wird die Entwicklung ortsbezogener Anwendungen systematisieren und wesentlich vereinfachen.

Common queries regarding information processing in ubiquitous computing are based on the location of physical objects. No matter if the next printer, next restaurant, or friend is searched for, a notion of distances between objects is required. A search for all objects in a certain geographic area requires the possibility to define spatial ranges and spatial inclusion of locations. In this paper we discuss general properties of symbolic and geometric coordinates. Based on that, we present an overview of existing location models allowing for position, range, and nearest neighbor queries. The location models are classified according to their suitability with respect to the query processing and the involved modeling effort along with other requirements. Besides an overview of existing location models and approaches the classification of location models with respect to application requirements can assist developers in their design decisions.

Advances in sensor technology, wireless communication, and mobile devices lead to the proliferation of sensors in our physical environment. At the same time detailed digital models of buildings, towns, or even the globe become widely available. Integrating the huge amount of sensor data into spatial models results in highly dynamic models of the real world, often called context models. A wide range of applications can substantially benefit from context models. However, context data are inherently associated with uncertainty. In general, quality of context information has to be taken into account by both context management and applications. For example, the accuracy, completeness, and trustworthiness of spatial context information such as street or building data are very important for navigation and guidance systems. QuaCon 2009 was the first international scientific meeting that specifically focused on the different aspects of quality of context data. Research in context management and, in particular, context quality, requires an interdisciplinary approach. Therefore, the QuaCon workshop aimed to bring together researchers from various fields to discuss approaches to context quality and to make a consolidated contribution toward an integrated way of treating this topic. We received 19 high-quality paper submissions by researchers from Europe, USA, and Asia. The International Program Committee selected 11 papers for presentation at the workshop. Additionally, five invited contributions by internationally renowned experts in the field were included in the workshop program. The presentations at the workshop showed many facets of quality of context from different research fields including context data management, spatial models, context reasoning, privacy, and system frameworks. The lively discussions underlined the great interest in this topic and in particular led to a deeper understanding of the relations between the various aspects of quality of context. The success of QuaCon 2009 was the result of a team effort. We are grateful to the members of the Program Committee and the external reviewers for their thorough and timely reviews as well as to the authors for their high-quality submissions and interesting talks. We would like to extend special thanks to our invited speakers for their excellent and inspiring keynotes. Finally, we wish to thank all persons involved in the organization of the QuaCon 2009 workshop who did really a great job.

Geocast protocols can be used to send messages to all receivers in a geographic target area. In this paper we present geocast routing algorithms for Wireless Mesh Networks that are tailored to symbolic addressing using symbolic location names like floor or room numbers. Since in particular indoors no geometric information is available, our algorithms use symbolic location models to derive directional information for routing. Moreover, we show how to integrate geometric and symbolic geographic routing algorithms into a hybrid routing approach which is applicable to larger areas consisting of symbolically and geometrically defined locations.

Position information of moving as well as stationary objects is generally subject to uncertainties due to inherent measuring errors of positioning technologies, explicit tolerances of position update protocols, and approximations by interpolation algorithms. There exist a variety of approaches for specifying these uncertainties by mathematical uncertainty models such as tolerance regions or the Dilution of Precision (DOP) values of GPS. In this paper we propose a principled generic uncertainty model that integrates the different approaches and derive a comprehensive query interface for processing spatial queries on uncertain position information of different sources based on this model. Finally, we show how to implement our approach with prevalent existing uncertainty models.

Dieser Beitrag beschreibt die Verteilung kontextbezogener Informationen mittels eines erweiterten Instant-Messaging-Dienstes. Dieser Dienst ermöglicht das Senden von Nachrichten an alle Teilnehmer, die einen bestimmten Kontext besitzen und sich z.B. an einem bestimmten Ort aufhalten oder bestimmte Interessen besitzen. Als Basis dient das Extensible Messaging and Presence Protokoll (XMPP) sowie ein XMPP-basierter Instant-Messaging-Dienst. Wir beschreiben Protokoll- und Architekturerweiterungen für die Integration von Kontextinformationen in das XMPP-Protokoll und die Server-Infrastruktur. Der erweiterte Dienst unterstützt insbesondere die Server-seitige Filterung von Nachrichten aufgrund von Kontextinformationen und ermöglicht dadurch die effiziente Nachrichtenverteilung.

Verbindet man die Position eines Benutzers mit weiteren Attributen wie beispielsweise Typ, Alter oder Status zu seinem Kontext, so ergeben sich daraus interessante neue Anwendungsmöglichkeiten. In diesem Artikel soll ein Verfahren vorgestellt werden, wie ein solcher Kontext benutzt werden kann, um Nachrichten an bestimmte Gruppen von Benutzern – bestimmt durch ihren Kontext – zu versenden. Ein solcher Kommunikationsmechanismus könnte beispielsweise eingesetzt werden, um Verkehrsnachrichten gezielt an alle Fahrzeuge innerhalb eines bestimmten Gebietes und mit einer bestimmten Fahrtrichtung zu übermitteln.

In this paper we present the Nexus Platform for context-aware applications. This platform allows to share the effort of setting up a global and detailed context model between different providers by federating their partial models. Applications can query data directly, use push-based communication through an event service, or use value-added services like a navigation or map service for special tasks. Additional context-aware services like hoarding or geocast can be implemented on basis of the platform. For the latter we present different approaches for addressing and efficient message forwarding based on the Nexus Platform.

Position information of moving objects plays a vital role in many pervasive applications. Therefore, moving objects databases (MODs), which can manage trajectory data of a number objects, are used in many pervasive systems. A crucial problem with MODs is how to efficiently track a remote object's trajectory in real-time, i.e. how to continuously report the sensed trajectory data to the MOD with minimal effort. For this purpose, we present a prototypical implementation of the Generic Remote Trajectory Simplification (GRTS) protocol, which optimizes storage consumption, processing, and communication costs. Our prototypical system includes a fully functional MOD as well as map-based mobile applications for subnotebooks and smartphones to illustrate the functioning of GRTS.