Monty Beuster

S2B2: Blackboard for Transparent Data and Control Access in Heterogeneous Sensing Systems

This paper presents concept and first implementation of a sensor system blackboard concept (S2B2). S2B2 is designed as a data store surrounded by software modules that operate on the blackboard. The blackboard is implemented as the only communication medium between modules within the sensor node. Modules can also transparently communicate with other modules even if they are hosted on a remote, different type of sensor node thus allowing true heterogeneity. The S2B2 module concept enables fine-grained decoupling of software functionality and separation of concerns. This allows rapid prototyping of functionality and simplifies real-time testing and debugging. The S2B2 provides the basis for integration of PC based and sensor node based applications. This paper introduces concept and architecture of S2B2 and shows the potential of the approach by presenting an example implementation. First results show that the system shortens programming time by at least 30%.

Matrix Routing -- An Interference Range Insensitive Routing Protocol for Wireless Sensor Networks

Interference ranges can dramatically affect the throughput in wireless sensor networks. While the transmission range defines the maximum physical range of a radio signal the interference range determines the area in which other nodes will be prevented from successful receiving or transmitting signals. In this paper we present an initial self organizing routing protocol for wireless sensor networks, named Matrix Routing, which is maximally insensitive even to high interference disturbances. Matrix routing is predictable, proactive but not table driven, needs minimum hardware and computational power and does not require transmission of routing packets. The protocol is characterized by zero overhearing costs and minimal idle listening. The paper shows a proof of concept, evaluates potential of our algorithm and discusses strength, limitations and application areas.

Audio fingerprinting in UbiComp environments — performance measurements and applications

We propose an audio-based mechanism for device authentication. The method is feasible with low-end microphones and can be extended to further UbiComp application domains as improved location estimation of sensor nodes or alarming. Measurement results obtained in a preparatory study demonstrate the performance of the approach.

Quality of Location: Estimation, system integration and application

Accurate location measurement is an important research topic in pervasive computing systems and applications. To achieve high performance measurements, the knowledge of the quality of a measurement, a sensor cue, or an inferred location value is required. This paper presents a novel approach in the deliverance of an independent, unified quality of location (QoL) value for location systems. The proposed approach is highly flexible, independent of technology and location inference mechanisms and approaches, integrable into any existing location system, and does neither require knowledge of sensor, nor of application characteristics. The paper proposes both a method to retrieve QoL for a given system, and shows its application in a setting using a simple ultrasound location system. Retrieving QoL requires a multi step process including a unsupervised subtractive clustering method for initial learning, and a supervised network based fuzzy inference systems (ANFIS) for refinement of the parameters. The approach described can be used in settings using heterogeneous systems, devices, and sensors. It is also usable at any abstraction layer and is able to run on small sensor node devices. Technical foundations of the algorithms are an adaptive network based fuzzy inference systems (ANFIS). In this paper we will show the technical principles, its application and evaluate the performance of the system.

Developing a virtual environment for better sensory perception

In sensor networks different types of sensors are used to capture events, recognize contexts, derive states of objects or monitor processes within application scenarios. We envision the use of the presented technology in areas that are very complex, e.g. in industrial applications. The presented system uses sensor information from wireless sensor nodes that are forwarded and aggregated in an information processing system. The high density of both number of sensors and overall sensor readings leads to an information overload situation, where it is difficult for a human to perceive detailed information using text based information input. We propose the use of a virtual environment - SensorRAUM - for improved sensory perception.

Search space size and context prediction

We discuss impacts of the prediction search space size on accuracy and robustness of context prediction approaches. Additionally, the impact on error detection and correction capabilities are considered. Conclusions are experimentally verified in a realistic ubiquitous setting.

Using auction based group formation for collaborative networking in Ubicomp

In many Ubicomp scenarios tiny wireless embedded sensor devices are used, and devices often collaborate to accomplish a common goal. This paper presents a group formation method designed for collaboration of devices. The paper analysis requirements for typical application scenarios, and then presents the general concept of the group formation process. The proposed formation method is a variant of an auction-based algorithm. The algorithm works fully distributed and is based on individual, private believes of the devices in the auctioneered item - e.g. a sensor value. The paper introduces the algorithm and analyses its effects analytically and in simulation. We show, that fully distributed operation, high robustness in the case of network failures and extreme low resource (energy) consumption can be obtained. We introduce an application case and present results from a real-world implementation.

Regulation of Electricity Markets with Ubiquitous Computing

We present a system that helps energy suppliers to smoothen the total peak load by generating price incentives for consumers. Consumers in turn get fine grained cost sensitive control of energy consumption of the past, present and future with a precise real-time overview of all devices in their household, company or industry. Pricing information of the energy provider and external sources is processed by our system and will help customers minimizing their energy costs. Sensor nodes are basis of the system enabling the collection of power consumption and other (e.g. temperature) information. They are involved in the decision support (e.g. delay activities for a certain time). Moreover the energy supplier can use the system to cut off certain devices that were negotiated and accepted by the consumer. The system is focussed on the demand side but benefits both.