Frank Dürr

On location models for ubiquitous computing

Common queries regarding information processing in ubiquitous computing are based on the location of physical objects. No matter whether it is the next printer, next restaurant, or a 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.

A classification of location privacy attacks and approaches

In recent years, location-based services have become very popular, mainly driven by the availability of modern mobile devices with integrated position sensors. Prominent examples are points of interest finders or geo-social networks such as Facebook Places, Qype, and Loopt. However, providing such services with private user positions may raise serious privacy concerns if these positions are not protected adequately. Therefore, location privacy concepts become mandatory to ensure the user’s acceptance of location-based services. Many different concepts and approaches for the protection of location privacy have been described in the literature. These approaches differ with respect to the protected information and their effectiveness against different attacks. The goal of this paper is to assess the applicability and effectiveness of location privacy approaches systematically. We first identify different protection goals, namely personal information (user identity), spatial information (user position), and temporal information (identity/position + time). Secondly, we give an overview of basic principles and existing approaches to protect these privacy goals. In a third step, we classify possible attacks. Finally, we analyze existing approaches with respect to their protection goals and their ability to resist the introduced attacks.

StreamShaper: Coordination algorithms for participatory mobile urban sensing

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.

Remote real-time trajectory simplification

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.

Efficient real-time trajectory tracking

Moving objects databases (MOD) manage trajectory information of vehicles, animals, and other mobile objects. A crucial problem is how to efficiently track an object’s trajectory in real-time, in particular if the trajectory data is sensed at the mobile object and thus has to be communicated over a wireless network. We propose a family of tracking protocols that allow trading the communication cost and the amount of trajectory data stored at a MOD off against the spatial accuracy. With each of these protocols, the MOD manages a simplified trajectory that does not deviate by more than a certain accuracy bound from the actual movement. Moreover, the different protocols enable several trade-offs between computational costs, communication cost, and the reduction in the trajectory data: Connection-Preserving Dead Reckoning minimizes the communication cost using dead reckoning, a technique originally designed for tracking an object’s current position. Generic Remote Trajectory Simplification (GRTS) further separates between tracking of the current position and simplification of the past trajectory and can be realized with different line simplification algorithms. For both protocols, we discuss how to bound the space consumption and computing time at the moving object and thereby present an effective compression technique to optimize the reduction performance of real-time line simplification in general. Our evaluations with hundreds of real GPS traces show that a realization of GRTS with a simple simplification heuristic reaches 85–90% of the best possible reduction rate, given by retrospective offline simplification. A realization with the optimal line simplification algorithm by Imai and Iri even reaches more than 97% of the best possible reduction rate.

The power of software-defined networking: line-rate content-based routing using OpenFlow

A lot of research effort has been invested to support efficient content-based routing. Nevertheless, practitioners often fall back to far less expressive communication paradigms like multicast groups. The benefits of content-based routing in minimizing bandwidth consumption are often rendered useless by simpler communication paradigms that rely on line-rate processing of data packets at the switches of the network providers. Contrary content-based routing protocols face the inherent overhead in matching the content of events against subscriptions leading to far lower throughput rates and higher end-to-end delays. However, recent trends in networking such as software defined networking in combination with network virtualization have tremendous potential to change the picture. In our opinion this will significantly increase acceptance of sophisticated middleware like content-based routing in the future. To support our claims we outline in this paper a reference architecture that may be used to build middleware for Future Internet applications. Furthermore, we provide a solution for realizing content-based routing at line-rate relying on this reference architecture and illustrate research problems that need to be addressed.

Position sharing for location privacy in non-trusted systems

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 users 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.

PShare: Position sharing for location privacy based on multi-secret sharing

Location-based applications such as Facebook Places, Foursquare, or Loopt attract millions of users by implementing point of interest finders, friend finders, geosocial networking, etc. Typically, these applications act as clients to a location service such as Google Latitude or Yahoo Fire Eagle, which manage mobile object positions and ensure the scalability to provide various clients with mobile object positions. However, exposing precise user positions raises user privacy concerns, especially if location service providers are not fully trusted, and private position information could be “lost”, leaked, stolen, etc. To enable the secure management of private user positions on non-trusted location servers (LSs), we present novel position sharing approaches based on the concept of multi-secret sharing. Our approaches split up a precise user position into position shares, which are distributed to different LSs of different providers such that a compromised provider only reveals user positions with degraded precision. On the other hand, clients can combine several shares queried from different LSs to increase their provided precision without the need to store precise information at a single LS. We propose two position sharing approaches: PShare-SLM is the first position sharing approach presented so far for symbolic location models. For geometric location models, we present PShare-GLM, which improves existing geometric position sharing approaches [1] by considering continuous position updates and by increasing the robustness against various attacks.

A Sensor Network Abstraction for Flexible Public Sensing Systems

Public Sensing is a new paradigm for developing large-scale sensor networks at low cost by utilizing mobile phones that are already surrounding us in our everyday lives. In this paper we present a sensor network abstraction layer for creating flexible public sensing systems that can execute arbitrary queries. To this effect we develop several algorithms to select mobile nodes for executing a query. These algorithms allow a user to define a trade-off between quality and efficiency of query execution by choosing an appropriate algorithm. Our evaluations show that we can achieve a 99% increase in efficiency with the most efficient approaches and only about 10% decrease in result quality under worst conditions.

Participatory sensing algorithms for mobile object discovery in urban areas

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.